Segfault due to missing support for quantized types
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):
```python
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](https://github.com/tensorflow/tensorflow/blob/f3b9bf4c3c0597563b289c0512e98d4ce81f886e/tensorflow/python/eager/pywrap_tfe_src.cc#L480-L482) to [ParseDimensionValue](https://github.com/tensorflow/tensorflow/blob/f3b9bf4c3c0597563b289c0512e98d4ce81f886e/tensorflow/python/eager/pywrap_tfe_src.cc#L296-L320) for the py_value argument. Then, this is dereferenced, resulting in segfault.
We have patched the issue in GitHub commit [237822b59fc504dda2c564787f5d3ad9c4aa62d9](https://github.com/tensorflow/tensorflow/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.
Please 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.
This vulnerability has been reported by Hong Jin from Singapore Management University.
This issue can be reached with local access to the system, attack complexity is low, an attacker needs low-level privileges on the target. No user interaction is required. The scope is unchanged, so the impact stays within the vulnerable component. Rated impact: confidentiality none, integrity none, availability high.
The score comes from this vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
CVE-2022-29205 is classified as CWE-476: NULL Pointer Dereference. A pointer that can be null is used without a check, crashing the process.
CVE-2022-29205 is recorded against 3 packages.
Published on 9 July 2026 and last revised on 13 July 2026. A public exploit is known to exist, which raises the urgency of patching considerably. A vendor advisory or fix has been published. Record sourced from OSV.
github.com (Web)
nvd.nist.gov (Advisory)
github.com (Web)
github.com (Package)
github.com (Web)
github.com (Web)
github.com (Web)
github.com (Web)
github.com (Web)
github.com (Web)
pypi.org (Package)
github.com (Advisory)
tensorflow has other advisories on record. If you are patching this one, these are worth checking on the same host:
These advisories are the same class of weakness (CWE-476: NULL Pointer Dereference) in other software:
Details
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
Affected Packages
| Software | From version | Fixed in |
|---|---|---|
| tensorflow | 2.8.0 | 2.8.1 |
| tensorflow-cpu | 2.8.0 | 2.8.1 |
| tensorflow-gpu | 2.8.0 | 2.8.1 |
References
Similar Threats
Exploit Protection
CVE-2022-29205 carries CVSS 5.0 Medium rating and a public exploit already exists. BotEraser checks your installation against this and other known CVE records, and blocks IPs associated with exploit activity.
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ⓘ Data Notice: The information presented above has been compiled from publicly available internet sources. Boteraser aggregates this data solely for informational purposes and does not independently classify, evaluate, or endorse any findings about the vulnerabilities listed. The accuracy and completeness of this information is the sole responsibility of the original publishers. Boteraser and its operators accept no liability for any decisions made based on this data.
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