--- name: reverse-engineering-ransomware-encryption-routine description: Reverse engineer ransomware encryption routines to identify cryptographic algorithms, key generation flaws, and potential decryption opportunities using static and dynamic analysis. domain: cybersecurity subdomain: malware-analysis tags: - ransomware - encryption - reverse-engineering - cryptanalysis - aes - rsa - decryption - malware-analysis version: '1.0' author: mahipal license: Apache-2.0 d3fend_techniques: - File Metadata Consistency Validation - Content Format Conversion - File Content Analysis - Platform Hardening - File Format Verification nist_csf: - DE.AE-02 - RS.AN-03 - ID.RA-01 - DE.CM-01 --- # Reverse Engineering Ransomware Encryption Routine ## Overview Modern ransomware uses hybrid encryption combining symmetric algorithms (AES-256-CBC/CTR, ChaCha20, Salsa20) for file encryption with asymmetric algorithms (RSA-2048/4096, Curve25519) for key protection. The encryption routine typically generates a random symmetric key per file, encrypts file contents, then encrypts the symmetric key with the attacker's embedded public key. Reverse engineering these routines identifies the specific algorithms, key derivation methods, initialization vectors, file targeting patterns, and potential implementation flaws that could enable decryption without paying the ransom. Notable examples include Rhysida (AES-256-CTR + RSA-4096), Qilin.B (AES-256-CTR with AES-NI or ChaCha20 fallback), and Medusa (AES-256 + RSA). ## When to Use - When performing authorized security testing that involves reverse engineering ransomware encryption routine - When analyzing malware samples or attack artifacts in a controlled environment - When conducting red team exercises or penetration testing engagements - When building detection capabilities based on offensive technique understanding ## Prerequisites - IDA Pro or Ghidra for static disassembly - x64dbg/WinDbg for dynamic debugging - Python 3.9+ with `pycryptodome`, `pefile` - Understanding of AES, RSA, ChaCha20, Curve25519 algorithms - Knowledge of Windows CryptoAPI and CNG (BCrypt) functions - Sandbox environment for safe execution ## Key Concepts ### Hybrid Encryption Model Ransomware generates a unique AES key and IV for each file. The file content is encrypted with this symmetric key. The symmetric key is then encrypted with the attacker's RSA public key (embedded in the binary or fetched from C2). The encrypted key is appended or prepended to the encrypted file. Only the attacker holding the RSA private key can decrypt the per-file symmetric keys. ### Cryptographic API Identification Windows ransomware typically uses CryptoAPI (`CryptAcquireContext`, `CryptGenKey`, `CryptEncrypt`) or CNG (`BCryptGenerateSymmetricKey`, `BCryptEncrypt`). Some use OpenSSL or custom implementations. Identifying these API calls provides immediate insight into the algorithm, key size, and mode of operation. ### Implementation Flaws Decryption opportunities arise from: hardcoded encryption keys, weak PRNG for key generation (using `GetTickCount` or `time()` as seed), reuse of IVs across files, ECB mode usage, keys remaining in memory post-encryption, and race conditions where keys can be captured during encryption. ## Workflow ### Step 1: Identify Cryptographic Functions ```python #!/usr/bin/env python3 """Identify cryptographic functions in ransomware PE files.""" import pefile import sys CRYPTO_APIS = { # Windows CryptoAPI "CryptAcquireContextA": "CryptoAPI context acquisition", "CryptAcquireContextW": "CryptoAPI context acquisition", "CryptGenKey": "Key generation", "CryptDeriveKey": "Key derivation", "CryptEncrypt": "Encryption operation", "CryptDecrypt": "Decryption operation", "CryptImportKey": "Key import (public key?)", "CryptExportKey": "Key export", "CryptGenRandom": "Random number generation", "CryptCreateHash": "Hash creation", "CryptHashData": "Hashing operation", # Windows CNG (BCrypt) "BCryptOpenAlgorithmProvider": "CNG algorithm initialization", "BCryptGenerateSymmetricKey": "CNG symmetric key generation", "BCryptEncrypt": "CNG encryption", "BCryptDecrypt": "CNG decryption", "BCryptGenerateKeyPair": "CNG key pair generation", "BCryptImportKeyPair": "CNG key import", # OpenSSL "EVP_EncryptInit_ex": "OpenSSL encrypt init", "EVP_EncryptUpdate": "OpenSSL encrypt update", "EVP_EncryptFinal_ex": "OpenSSL encrypt final", "RSA_public_encrypt": "OpenSSL RSA encryption", "AES_set_encrypt_key": "OpenSSL AES key setup", # File operations "CreateFileW": "File open (target files)", "ReadFile": "File read (before encryption)", "WriteFile": "File write (after encryption)", "FindFirstFileW": "File enumeration (targeting)", "FindNextFileW": "File enumeration", "MoveFileW": "File rename (extension change)", "DeleteFileW": "File deletion (originals)", } AES_SBOX = bytes([ 0x63, 0x7c, 0x77, 0x7b, 0xf2, 0x6b, 0x6f, 0xc5, 0x30, 0x01, 0x67, 0x2b, 0xfe, 0xd7, 0xab, 0x76, ]) CHACHA20_CONSTANT = b"expand 32-byte k" def analyze_imports(filepath): """Analyze PE imports for cryptographic APIs.""" try: pe = pefile.PE(filepath) except pefile.PEFormatError: print("[-] Not a valid PE file") return print("[+] Cryptographic API Analysis") print("=" * 60) crypto_imports = [] if hasattr(pe, 'DIRECTORY_ENTRY_IMPORT'): for entry in pe.DIRECTORY_ENTRY_IMPORT: dll = entry.dll.decode('utf-8', errors='replace') for imp in entry.imports: if imp.name: name = imp.name.decode('utf-8', errors='replace') if name in CRYPTO_APIS: desc = CRYPTO_APIS[name] crypto_imports.append((dll, name, desc)) print(f" [{dll}] {name}: {desc}") if not crypto_imports: print(" No known crypto APIs found in imports") print(" Malware may use custom implementation or dynamic loading") return crypto_imports def find_crypto_constants(filepath): """Search for embedded cryptographic constants.""" with open(filepath, 'rb') as f: data = f.read() print("\n[+] Cryptographic Constants Search") print("=" * 60) # AES S-Box offset = data.find(AES_SBOX) if offset != -1: print(f" AES S-Box found at offset 0x{offset:x}") # ChaCha20/Salsa20 constant offset = data.find(CHACHA20_CONSTANT) if offset != -1: print(f" ChaCha20 constant at offset 0x{offset:x}") # RSA public key markers rsa_markers = [ b'-----BEGIN PUBLIC KEY-----', b'-----BEGIN RSA PUBLIC KEY-----', b'\x30\x82', # ASN.1 SEQUENCE ] for marker in rsa_markers: offset = data.find(marker) if offset != -1: print(f" RSA key marker at offset 0x{offset:x}") # Common ransomware file extension patterns import re ext_pattern = re.compile(rb'\.\w{3,10}(?=\x00)', re.IGNORECASE) extensions = set() for match in ext_pattern.finditer(data): ext = match.group().decode('ascii', errors='replace').lower() target_exts = [ '.doc', '.docx', '.xls', '.xlsx', '.pdf', '.ppt', '.jpg', '.png', '.sql', '.mdb', '.bak', '.zip', ] if ext in target_exts: extensions.add(ext) if extensions: print(f"\n Target file extensions: {', '.join(sorted(extensions))}") if __name__ == "__main__": if len(sys.argv) < 2: print(f"Usage: {sys.argv[0]} ") sys.exit(1) analyze_imports(sys.argv[1]) find_crypto_constants(sys.argv[1]) ``` ### Step 2: Analyze Encryption Flow ```python def analyze_encryption_pattern(filepath): """Analyze file encryption patterns from ransomware artifacts.""" import os import struct with open(filepath, 'rb') as f: data = f.read() file_size = len(data) print(f"\n[+] Encrypted File Analysis: {filepath}") print(f" Size: {file_size:,} bytes") # Check for appended key material (common pattern) # Many ransomware families append encrypted key at end of file tail_sizes = [256, 512, 1024, 2048] # Common RSA ciphertext sizes for size in tail_sizes: if file_size > size + 16: tail = data[-size:] # High entropy suggests encrypted data entropy = calculate_entropy(tail) if entropy > 7.5: print(f" Possible encrypted key ({size} bytes) " f"at end of file (entropy: {entropy:.2f})") # Check for header modifications # Many ransomware prepend metadata header = data[:64] print(f" First 16 bytes: {header[:16].hex()}") # Check if original file header is preserved known_headers = { b'PK': 'ZIP/Office', b'\x89PNG': 'PNG', b'\xff\xd8\xff': 'JPEG', b'%PDF': 'PDF', b'\xd0\xcf\x11\xe0': 'OLE (DOC/XLS)', } for magic, ftype in known_headers.items(): if header.startswith(magic): print(f" Original format preserved: {ftype}") break else: print(" Original header destroyed/encrypted") def calculate_entropy(data): """Calculate Shannon entropy of data.""" from collections import Counter import math if not data: return 0 freq = Counter(data) length = len(data) entropy = -sum( (count / length) * math.log2(count / length) for count in freq.values() ) return entropy ``` ## Validation Criteria - Cryptographic algorithms identified (AES, RSA, ChaCha20, etc.) - Key size and mode of operation determined - Key generation method analyzed for potential weaknesses - Per-file key encryption scheme documented - File targeting patterns and extension list extracted - Embedded public keys extracted for infrastructure correlation - Potential decryption opportunities assessed ## References - [Morphisec - Breaking Down Ransomware Encryption](https://www.morphisec.com/blog/breaking-down-ransomware-encryption-key-strategies-algorithms-and-implementation-trends/) - [Emsisoft - Ransomware Encryption Methods](https://www.emsisoft.com/en/blog/27649/ransomware-encryption-methods/) - [Halcyon Ransomware Power Rankings Q4-2024](https://www.halcyon.ai/raas-mq/power-rankings-ransomware-malicious-quartile-q4-2024) - [No More Ransom Project](https://www.nomoreransom.org/) - [MITRE ATT&CK T1486 - Data Encrypted for Impact](https://attack.mitre.org/techniques/T1486/)