CVE-2022-23571: Reachable Assertion in TensorFlow
Summary
CVE-2022-23571: Reachable Assertion in Tensorflow. Affects tensorflow across 3 version ranges.
< 2.5.3
>= 2.6.0, < 2.6.3
>= 2.7.0, < 2.7.1
Fixed in 2.5.3, 2.6.3 or 2.7.1, depending on the release line you run. How to fix ↓
Also tracked for
- tensorflow · Bitnami
- tensorflow-gpu · PyPI
- tensorflow-cpu · PyPI
The same CVE-2022-23571 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 developed by Google. It provides a comprehensive ecosystem of tools, libraries, and resources for building and deploying machine learning models. TensorFlow is widely used in various domains, including research, industry, and academia. However, a vulnerability has been discovered in TensorFlow that can lead to denial of service attacks.
Vulnerability Detail
The vulnerability in TensorFlow arises when decoding a tensor from protobuf. In certain cases, a CHECK assertion can be invalidated based on user-controlled arguments. This can occur when the tensors have an invalid dtype and 0 elements or an invalid shape. Attackers can exploit this vulnerability to cause denial of service in TensorFlow processes. The impact of this vulnerability can be significant, as it can disrupt the functioning of TensorFlow-based applications and systems.
How To Fix
Latest published version: 2.21.0 as of 22 Oct 2026
pip install --upgrade "tensorflow==2.21.0"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.
-
< 2.5.32.5.3pip install --upgrade "tensorflow==2.5.3" -
>= 2.6.0, < 2.6.32.6.3pip install --upgrade "tensorflow==2.6.3" -
>= 2.7.0, < 2.7.12.7.1pip install --upgrade "tensorflow==2.7.1"
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Workaround
There is no specific workaround mentioned for this vulnerability. The recommended approach is to update TensorFlow to the patched versions.
Conclusion
The vulnerability in TensorFlow can result in denial of service attacks, impacting the availability and functioning of TensorFlow-based applications and systems. It is crucial to update TensorFlow to the patched versions or apply the provided patches to mitigate the risk. For further support on vulnerability remediation, you can contact DevNack.com.
See every vulnerability recorded for tensorflow →
FAQ
The vulnerability can lead to denial of service attacks in TensorFlow processes, potentially disrupting the functioning of TensorFlow-based applications and systems.
To fix this vulnerability, update TensorFlow to version 2.8.0 or apply the respective patches for versions 2.5.3, 2.6.3, and 2.7.1.
No specific workarounds are mentioned for this vulnerability. Updating TensorFlow to the patched versions is the recommended approach.
This vulnerability does not directly lead to data compromise. However, denial of service attacks can disrupt the availability and functioning of TensorFlow-based systems.
There is no specific information provided about active exploitation of this vulnerability. However, it is important to update TensorFlow installations to mitigate the risk.
References
Related vulnerabilities
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