CVE-2022-29205: TensorFlow GPU Segfault Due to Missing Support for Quantized Types
Summary
CVE-2022-29205: Segfault due to missing support for quantized types. Affects tensorflow-gpu across 3 version ranges.
< 2.6.4
>= 2.7.0, < 2.7.2
>= 2.8.0, < 2.8.1
Fixed in 2.6.4, 2.7.2 or 2.8.1, depending on the release line you run. How to fix ↓
Also tracked for
- tensorflow · PyPI
- tensorflow-cpu · PyPI
- tensorflow · Bitnami
- tensorflow · PyPI
The same CVE-2022-29205 is tracked separately for each ecosystem and vendor. Its fix information is the same; the package and affected versions differ.
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Background
TensorFlow is an open-source machine learning framework that provides a comprehensive ecosystem for building and deploying machine learning models. It supports various operations and data types, including quantized types, which are essential for optimizing performance in resource-constrained environments. However, certain operations in TensorFlow, particularly those accessed through the compatibility module (tf.compat.v1), lack support for quantized types, leading to potential vulnerabilities.
Vulnerability Detail
The vulnerability arises from the lack of support for quantized types in specific TensorFlow operations. When users attempt to call these operations with quantized types, a null pointer is passed to the underlying implementation, resulting in a segmentation fault (segfault). This can lead to denial of service, as the application may crash unexpectedly. The issue is particularly critical for applications relying on TensorFlow's compatibility layer, which may not have been fully migrated to support the newer features introduced in TensorFlow 2.x.
How To Fix
Latest published version: 2.12.0 as of 22 Oct 2026
pip install --upgrade "tensorflow-gpu==2.12.0"Upgrading to it may include breaking changes; the versions below are the minimum fixed release for this vulnerability.
If you can't move to the latest
The minimum fixed version depends on the release line you run.
-
< 2.6.42.6.4pip install --upgrade "tensorflow-gpu==2.6.4" -
>= 2.7.0, < 2.7.22.7.2pip install --upgrade "tensorflow-gpu==2.7.2" -
>= 2.8.0, < 2.8.12.8.1pip install --upgrade "tensorflow-gpu==2.8.1"
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Workaround
As a temporary workaround, avoid using the affected operations with quantized types until the package is updated. For example, instead of using the placeholder_with_default function with quantized types, consider using standard data types until the patch is applied. Here is an example of how to modify the code:
import numpy as np import tensorflow as tf
Use a standard data type instead of quantized type
placeholder = tf.compat.v1.placeholder_with_default(input=np.array([2]), shape=[1])
Conclusion
In summary, CVE-2022-29205 is a significant vulnerability in TensorFlow GPU that can lead to application crashes due to unsupported quantized types in certain operations. Users are advised to update their TensorFlow packages to the latest patched versions to mitigate this risk.
See every vulnerability recorded for tensorflow-gpu →
FAQ
CVE-2022-29205 is a vulnerability in TensorFlow GPU that can cause a segmentation fault due to missing support for quantized types in certain operations.
If your application uses TensorFlow operations that lack support for quantized types, it may crash unexpectedly, leading to denial of service.
Affected versions include TensorFlow 2.6.0 to 2.8.0. The vulnerability is fixed in versions 2.6.4, 2.7.2, 2.8.1, and 2.9.0.
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The CVSS score for this vulnerability is 5.5, indicating a moderate level of risk.
References
Related vulnerabilities
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