id: PYSEC-2026-3234
published: "2026-07-13T14:19:42.659799Z"
modified: "2026-07-13T16:07:13.372561Z"
aliases:
- CVE-2022-36005
- GHSA-r26c-679w-mrjm
summary: TensorFlow vulnerable to `CHECK` fail in `FakeQuantWithMinMaxVarsGradient`
details: "### Impact\nWhen `tf.quantization.fake_quant_with_min_max_vars_gradient` receives input `min` or `max` that is nonscalar, it gives a `CHECK` fail that can trigger a denial of service attack.\n```python\nimport tensorflow as tf\nimport numpy as np \narg_0=tf.constant(value=np.random.random(size=(2, 2)), shape=(2, 2), dtype=tf.float32)\narg_1=tf.constant(value=np.random.random(size=(2, 2)), shape=(2, 2), dtype=tf.float32)\narg_2=tf.constant(value=np.random.random(size=(2, 2)), shape=(2, 2), dtype=tf.float32)\narg_3=tf.constant(value=np.random.random(size=(2, 2)), shape=(2, 2), dtype=tf.float32)\narg_4=8\narg_5=False\narg_6=''\ntf.quantization.fake_quant_with_min_max_vars_gradient(gradients=arg_0, inputs=arg_1,\nmin=arg_2, max=arg_3, num_bits=arg_4, narrow_range=arg_5, name=arg_6)\n```\n\n### Patches\nWe have patched the issue in GitHub commit [f3cf67ac5705f4f04721d15e485e192bb319feed](https://github.com/tensorflow/tensorflow/commit/f3cf67ac5705f4f04721d15e485e192bb319feed).\n\nThe fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range.\n\n\n### For more information\nPlease consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.\n\n\n### Attribution\nThis vulnerability has been reported by\n - 刘力源, Information System & Security and Countermeasures Experiments Center, Beijing Institute of Technology\n - Neophytos Christou, Secure Systems Labs, Brown University\n"
affected:
- package:
    name: tensorflow
    ecosystem: PyPI
    purl: pkg:pypi/tensorflow
  ranges:
  - type: ECOSYSTEM
    events:
    - introduced: "0"
    - fixed: 2.7.2
    - introduced: 2.8.0
    - fixed: 2.8.1
    - introduced: 2.9.0
    - fixed: 2.9.1
  versions:
  - 0.12.0
  - 0.12.1
  - 1.0.0
  - 1.0.1
  - 1.1.0
  - 1.10.0
  - 1.10.1
  - 1.11.0
  - 1.12.0
  - 1.12.2
  - 1.12.3
  - 1.13.1
  - 1.13.2
  - 1.14.0
  - 1.15.0
  - 1.15.2
  - 1.15.3
  - 1.15.4
  - 1.15.5
  - 1.2.0
  - 1.2.1
  - 1.3.0
  - 1.4.0
  - 1.4.1
  - 1.5.0
  - 1.5.1
  - 1.6.0
  - 1.7.0
  - 1.7.1
  - 1.8.0
  - 1.9.0
  - 2.0.0
  - 2.0.1
  - 2.0.2
  - 2.0.3
  - 2.0.4
  - 2.1.0
  - 2.1.1
  - 2.1.2
  - 2.1.3
  - 2.1.4
  - 2.2.0
  - 2.2.1
  - 2.2.2
  - 2.2.3
  - 2.3.0
  - 2.3.1
  - 2.3.2
  - 2.3.3
  - 2.3.4
  - 2.4.0
  - 2.4.1
  - 2.4.2
  - 2.4.3
  - 2.4.4
  - 2.5.0
  - 2.5.1
  - 2.5.2
  - 2.5.3
  - 2.6.0
  - 2.6.0rc0
  - 2.6.0rc1
  - 2.6.0rc2
  - 2.6.1
  - 2.6.2
  - 2.6.3
  - 2.6.4
  - 2.6.5
  - 2.7.0
  - 2.7.0rc0
  - 2.7.0rc1
  - 2.7.1
  - 2.8.0
  - 2.9.0
references:
- type: WEB
  url: https://github.com/tensorflow/tensorflow/security/advisories/GHSA-r26c-679w-mrjm
- type: ADVISORY
  url: https://nvd.nist.gov/vuln/detail/CVE-2022-36005
- type: WEB
  url: https://github.com/tensorflow/tensorflow/commit/f3cf67ac5705f4f04721d15e485e192bb319feed
- type: PACKAGE
  url: https://github.com/tensorflow/tensorflow
- type: WEB
  url: https://github.com/tensorflow/tensorflow/releases/tag/v2.10.0
- type: PACKAGE
  url: https://pypi.org/project/tensorflow
- type: ADVISORY
  url: https://github.com/advisories/GHSA-r26c-679w-mrjm
severity:
- type: CVSS_V3
  score: CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H