Segfault if `tf.histogram_fixed_width` is called with NaN values in TensorFlow
Impact
The implementation of tf.histogram_fixed_width is vulnerable to a crash when the values array contain NaN elements:
import tensorflow as tf
import numpy as np
tf.histogram_fixed_width(values=np.nan, value_range=[1,2])
The implementation assumes that all floating point operations are defined and then converts a floating point result to an integer index:
index_to_bin.device(d) =
((values.cwiseMax(value_range(0)) - values.constant(value_range(0)))
.template cast<double>() /
step)
.cwiseMin(nbins_minus_1)
.template cast<int32>();
If values contains NaN then the result of the division is still NaN and the cast to int32 would result in a crash.
This only occurs on the CPU implementation.
Patches
We have patched the issue in GitHub commit e57fd691c7b0fd00ea3bfe43444f30c1969748b5.
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 externally via a GitHub issue.
Affected software
Click a technology to see all vulnerabilities affecting it.
| 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-xrp2-fhq4-4q3w
- https://nvd.nist.gov/vuln/detail/CVE-2022-29211
- https://github.com/tensorflow/tensorflow/issues/45770
- https://github.com/tensorflow/tensorflow/commit/e57fd691c7b0fd00ea3bfe43444f30c1969748b5
- https://github.com/tensorflow/tensorflow
- https://github.com/tensorflow/tensorflow/blob/f3b9bf4c3c0597563b289c0512e98d4ce81f886e/tensorflow/core/kernels/histogram_op.cc
- https://github.com/tensorflow/tensorflow/blob/f3b9bf4c3c0597563b289c0512e98d4ce81f886e/tensorflow/core/kernels/histogram_op.cc#L35-L74
- 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-gpu
- https://github.com/advisories/GHSA-xrp2-fhq4-4q3w
- https://pypi.org/project/tensorflow
- https://pypi.org/project/tensorflow-cpu
- CVSS vector
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H- Weakness (CWE)
CWE-20- 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-2026-1048 - PyPA Advisory Database; CC BY 4.0
OSV / GitHub Advisory Database - PYSEC-2026-3260 - PyPA Advisory Database; CC BY 4.0
OSV / GitHub Advisory Database - GHSA-xrp2-fhq4-4q3w - CC BY 4.0
OSV / GitHub Advisory Database - PYSEC-2026-3382 - PyPA Advisory Database; CC BY 4.0
Vulnerability history: tensorflow-gpu
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
- 427
- First → latest
- 04.2019 07.2024
- Without a fix
- 0
- Exploited in attacks
- 0
Severity breakdown
- Critical 6
- High 109
- Medium 207
- Low 105
Disclosures per year
- 2019: 7
- 2020: 35
- 2021: 200
- 2022: 166
- 2023: 18
- 2024: 1
- 2025: 0
- 2026: 0
-
Segfault if `tf.histogram_fixed_width` is called with NaN values in TensorFlow this entry
Know which vulnerabilities affect your application
With the DockRay integration and software inventory enabled, DockRay checks reported component versions against known vulnerabilities and notifies you about confirmed matches. Coverage depends on the supported technology and available advisory data.