Segfault due to missing support for quantized types
Impact
There is a potential for segfault / denial of service in TensorFlow by calling tf.compat.v1.* ops which don't yet have support for quantized types (added after migration to TF 2.x):
import numpy as np
import tensorflow as tf
tf.compat.v1.placeholder_with_default(input=np.array([2]),shape=tf.constant(dtype=tf.qint8, value=np.array([1])))In these scenarios, since the kernel is missing, a nullptr value is passed to ParseDimensionValue for the py_value argument. Then, this is dereferenced, resulting in segfault.
Patches
We have patched the issue in GitHub commit 237822b59fc504dda2c564787f5d3ad9c4aa62d9.
The fix will be included in TensorFlow 2.9.0. We will also cherrypick this commit on TensorFlow 2.8.1, TensorFlow 2.7.2, and TensorFlow 2.6.4, as these are also affected and still in supported range.
For more information
Please consult our security guide for more information regarding the security model and how to contact us with issues and questions.
Attribution
This vulnerability has been reported by Hong Jin from Singapore Management University.
Affected software
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| Platform | Package | Vulnerable versions | Fixed in |
|---|---|---|---|
| Python (PyPI) | tensorflow | < 2.6.4, >= 2.7.0, < 2.7.2, >= 2.8.0, < 2.8.1 | 2.6.4, 2.7.2, 2.8.1 |
| Python (PyPI) | tensorflow-cpu | < 2.6.4, >= 2.7.0, < 2.7.2, >= 2.8.0, < 2.8.1 | 2.6.4, 2.7.2, 2.8.1 |
| Python (PyPI) | tensorflow-gpu | < 2.6.4, >= 2.7.0, < 2.7.2, >= 2.8.0, < 2.8.1 | 2.6.4, 2.7.2, 2.8.1 |
References
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-54ch-gjq5-4976
- https://nvd.nist.gov/vuln/detail/CVE-2022-29205
- https://github.com/tensorflow/tensorflow/commit/237822b59fc504dda2c564787f5d3ad9c4aa62d9
- https://github.com/tensorflow/tensorflow
- https://github.com/tensorflow/tensorflow/blob/f3b9bf4c3c0597563b289c0512e98d4ce81f886e/tensorflow/python/eager/pywrap_tfe_src.cc#L296-L320
- https://github.com/tensorflow/tensorflow/blob/f3b9bf4c3c0597563b289c0512e98d4ce81f886e/tensorflow/python/eager/pywrap_tfe_src.cc#L480-L482
- https://github.com/tensorflow/tensorflow/releases/tag/v2.6.4
- https://github.com/tensorflow/tensorflow/releases/tag/v2.7.2
- https://github.com/tensorflow/tensorflow/releases/tag/v2.8.1
- https://github.com/tensorflow/tensorflow/releases/tag/v2.9.0
- https://pypi.org/project/tensorflow
- https://github.com/advisories/GHSA-54ch-gjq5-4976
- https://pypi.org/project/tensorflow-cpu
- https://pypi.org/project/tensorflow-gpu
- CVSS vector
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H- Weakness (CWE)
CWE-476, CWE-908- Platform
- Python (PyPI)
- Package
tensorflow, tensorflow-cpu, tensorflow-gpu- Disclosed
- 24.05.2022
- Updated
- 11.10.2026 14:18
Sources and licenses
OSV / GitHub Advisory Database - PYSEC-2026-3104 - PyPA Advisory Database; CC BY 4.0
OSV / GitHub Advisory Database - PYSEC-2026-3274 - PyPA Advisory Database; CC BY 4.0
OSV / GitHub Advisory Database - GHSA-54ch-gjq5-4976 - CC BY 4.0
OSV / GitHub Advisory Database - PYSEC-2026-950 - PyPA Advisory Database; CC BY 4.0
Vulnerability history: tensorflow-cpu
All published vulnerabilities of this package (Python (PyPI)), newest first. Shows whether this is a one-off slip or a package that needs watching.
- Total entries
- 430
- First → latest
- 04.2019 07.2024
- Without a fix
- 0
- Exploited in attacks
- 0
Severity breakdown
- Critical 6
- High 111
- Medium 208
- Low 105
Disclosures per year
- 2019: 7
- 2020: 35
- 2021: 200
- 2022: 166
- 2023: 21
- 2024: 1
- 2025: 0
- 2026: 0
-
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