CVE-2022-23586: Denial of Service in TensorFlow-GPU
Summary
CVE-2022-23586: Tensorflow is an Open Source Machine Learning Framework. Affects tensorflow-gpu across 4 version ranges.
< 2.5.3
>= 2.6.0, < 2.6.3
< 3d89911481ba6ebe8c88c1c0b595412121e6c645
< dcc21c7bc972b10b6fb95c2fb0f4ab5a59680ec2
Fixed in 2.5.3 or 2.6.3, depending on the release line you run. How to fix ↓
Also tracked for
- tensorflow · PyPI
- tensorflow · Bitnami
- tensorflow · PyPI
- tensorflow-cpu · PyPI
The same CVE-2022-23586 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 widely used for developing and deploying machine learning models. It provides a comprehensive ecosystem for building and training neural networks. TensorFlow-GPU is a variant of TensorFlow that leverages GPU acceleration for faster computation. It is commonly used in scenarios where large-scale data processing and complex model training are required.
Vulnerability Detail
A vulnerability has been identified in TensorFlow-GPU that allows a malicious user to trigger a denial of service (DoS) attack. By manipulating a SavedModel, the attacker can introduce falsified assertions in function.cc, leading to a crash in the Python interpreter. This vulnerability can be exploited remotely, potentially disrupting critical machine learning processes and causing service unavailability. The issue has been assigned CVE-2022-23586 and has been addressed in TensorFlow 2.8.0. Additionally, fixes have been backported to TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these versions are still within the supported range.
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.
-
< 2.5.32.5.3pip install --upgrade "tensorflow-gpu==2.5.3" -
>= 2.6.0, < 2.6.32.6.3pip install --upgrade "tensorflow-gpu==2.6.3"
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Workaround
There is no known workaround for this vulnerability. It is essential to apply the provided fixes or update to the patched versions to address the issue effectively.
Conclusion
In conclusion, a denial of service vulnerability has been identified in TensorFlow-GPU that can be exploited by a malicious user. It is crucial to update to TensorFlow-GPU 2.8.0 or apply the respective patches for versions 2.7.1, 2.6.3, and 2.5.3 to mitigate the risk. Failure to address this vulnerability may result in service disruptions and compromise the integrity of machine learning processes. For further support on vulnerability remediation, please contact DevNack.com.
See every vulnerability recorded for tensorflow-gpu →
FAQ
TensorFlow-GPU is a variant of TensorFlow that utilizes GPU acceleration for faster machine learning computations. It is commonly used in scenarios where large-scale data processing and complex model training are required.
This vulnerability allows a malicious user to trigger a denial of service (DoS) attack by manipulating a SavedModel. It can lead to a crash in the Python interpreter, potentially disrupting critical machine learning processes and causing service unavailability.
To fix this vulnerability, update TensorFlow-GPU to version 2.8.0. If you are using an affected version within the supported range, apply the respective patch for your version. The patched versions are TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3.
No, there is no known workaround for this vulnerability. It is crucial to apply the provided fixes or update to the patched versions to address the issue effectively.
The vulnerability affects TensorFlow-GPU versions 2.5.3, 2.6.3, 2.7.1, and any earlier versions within the supported range.
References
Related vulnerabilities
Recent vulnerabilities recorded for tensorflow-gpu.
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