CVE-2022-23570: TensorFlow Null-Dereference Vulnerability
Summary
CVE-2022-23570: Null-dereference 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-2022-23570 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 enables developers to build and deploy machine learning models. It is widely used for various applications, including deep learning and neural networks. The framework allows for flexible model building and has a robust ecosystem of tools and libraries. However, TensorFlow has a vulnerability related to null-dereferencing when decoding tensors from protobuf, which can lead to application crashes.
Vulnerability Detail
The vulnerability arises when TensorFlow attempts to decode a tensor from protobuf and encounters missing attributes for mutable arguments in some operations. This situation is protected by a 'DCHECK' assertion, which is a no-op in production builds. As a result, if the assertion is not triggered, the code proceeds to dereference a null pointer, potentially leading to a crash. In debug builds, the assertion failure results in an immediate crash, making it critical for developers to address this issue.
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"
Tip — Not sure which release line you're on? Vulert can find the fix for the version you are using. Scan free →
Workaround
Currently, there are no specific workarounds mentioned for this vulnerability. The best course of action is to update to the patched versions of TensorFlow.
Conclusion
The null-dereference vulnerability in TensorFlow (CVE-2022-23570) poses a risk to applications using affected versions of the framework. It is crucial to update to the patched versions to mitigate the risk of crashes. Regular monitoring for vulnerabilities using tools like Vulert can help maintain application security.
See every vulnerability recorded for tensorflow →
FAQ
CVE-2022-23570 is a vulnerability in TensorFlow that can lead to null-dereference errors when decoding tensors from protobuf.
If your application uses an affected version of TensorFlow, it may crash during execution due to null-dereferencing, especially in production environments.
The affected versions are TensorFlow 2.5.3, 2.6.0, and 2.7.0. It is recommended to upgrade to 2.7.1 or higher.
You can use Vulert, which monitors and alerts for open-source vulnerabilities in real-time. You can check your application against this vulnerability using the Vulert playground without signing up.
The CVSS score for this vulnerability is 6.5, indicating a moderate severity level.
References
Related vulnerabilities
Recent vulnerabilities recorded for tensorflow.
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