CVE-2022-21727: Integer Overflow in TensorFlow
Summary
CVE-2022-21727: Integer overflow 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-2022-21727 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 supports various platforms and programming languages, making it widely used in both research and production environments. However, a vulnerability has been discovered in TensorFlow that could potentially lead to security issues.
Vulnerability Detail
The vulnerability, identified as CVE-2022-21727, is an integer overflow weakness in the implementation of shape inference for the Dequantize function in TensorFlow. The issue arises from the mishandling of the axis argument, which can be manipulated by an attacker to trigger an integer overflow. This vulnerability can be exploited to execute arbitrary code or cause a denial-of-service (DoS) condition. The impact of this vulnerability is rated as HIGH with a CVSS score of 7.6.
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
As a temporary workaround, users can avoid using the Dequantize function with the vulnerable axis argument. If the function is necessary, it is advised to validate and sanitize the axis input to ensure it falls within the acceptable range.
Conclusion
The vulnerability in TensorFlow (CVE-2022-21727) poses a significant risk to systems utilizing the affected versions. It is crucial to update TensorFlow to the patched versions to mitigate the vulnerability. For further support and assistance in vulnerability remediation, please contact DevNack.com.
See every vulnerability recorded for tensorflow →
FAQ
TensorFlow is an open-source machine learning framework developed by Google. It provides tools and resources for building and deploying machine learning models.
The vulnerability allows an attacker to trigger an integer overflow, potentially leading to arbitrary code execution or a denial-of-service condition.
To fix the vulnerability, update TensorFlow to version 2.5.3, 2.6.3, 2.7.1, or later, following the official TensorFlow upgrade instructions.
As a temporary workaround, avoid using the Dequantize function with the vulnerable axis argument. Validate and sanitize the axis input if necessary.
For more information, refer to the official security guide provided by the TensorFlow team.
References
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