CVE-2022-23583: Denial of Service in TensorFlow
Summary
CVE-2022-23583: Tensorflow is an Open Source Machine Learning Framework. Affects tensorflow-cpu across 3 version ranges.
< 2.5.3
>= 2.6.0, < 2.6.3
< a7c02f1a9bbc35473969618a09ee5f9f5d3e52d9
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-gpu · PyPI
The same CVE-2022-23583 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 set of tools and libraries for building and training neural networks. TensorFlow supports various platforms and is known for its scalability and performance. However, a vulnerability has been discovered in TensorFlow that can lead to a denial of service attack.
Vulnerability Detail
The vulnerability in TensorFlow arises from a flaw in the handling of SavedModel files. By modifying the protobuf part corresponding to the tensor arguments, a malicious user can cause a CHECK failure when a binary operation is performed. This occurs when the dtype of the tensors no longer matches the expected dtype of the operation. As a result, the binary operator receives corrupted data, leading to type confusion and potential crashes. While most cases result in silent failures, there are scenarios where this vulnerability can be exploited to cause a denial of service.
How To Fix
Latest published version: 2.21.0 as of 22 Oct 2026
pip install --upgrade "tensorflow-cpu==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-cpu==2.5.3" -
>= 2.6.0, < 2.6.32.6.3pip install --upgrade "tensorflow-cpu==2.6.3"
Tip — Not sure which release line you're on? Vulert can find the fix for the version you are using. Scan free →
Workaround
There is no specific workaround provided for this vulnerability. It is recommended to update to the patched versions of TensorFlow as mentioned above.
Conclusion
The vulnerability in TensorFlow can be exploited to cause a denial of service attack by modifying SavedModel files. To protect against this vulnerability, it is crucial to update to the latest patched versions of TensorFlow. For further assistance and support in vulnerability remediation, please contact DevNack.com.
See every vulnerability recorded for tensorflow-cpu →
FAQ
TensorFlow is an open-source machine learning framework used for building and training neural networks.
A SavedModel is a serialization format used in TensorFlow to save and restore models, including their architecture, variables, and metadata.
A malicious user can modify the SavedModel file to alter the dtype of tensor arguments, causing type confusion and potential crashes when binary operations are performed.
The vulnerability can lead to a denial of service attack, potentially crashing TensorFlow applications.
Updating to the latest patched version of TensorFlow, such as TensorFlow 2.8.0, will mitigate the risk of this vulnerability.
References
Related vulnerabilities
Recent vulnerabilities recorded for tensorflow-cpu.
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