CVE-2021-37680: TensorFlow GPU - Division by Zero Vulnerability
Summary
CVE-2021-37680: TensorFlow is an end-to-end open source platform for machine learning. Affects tensorflow-gpu across 3 version ranges.
>= 2.3.0, < 2.3.4
>= 2.4.0, < 2.4.3
< 718721986aa137691ee23f03638867151f74935f
Fixed in 2.3.4 or 2.4.3, depending on the release line you run. How to fix ↓
Also tracked for
- tensorflow · Bitnami
- tensorflow · PyPI
- tensorflow · PyPI
- tensorflow-cpu · PyPI
The same CVE-2021-37680 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 end-to-end open source platform for machine learning. It provides a comprehensive ecosystem of tools, libraries, and resources for building and deploying machine learning models. TensorFlow GPU is a specific package that enables GPU acceleration for TensorFlow. It allows users to leverage the power of GPUs to accelerate their machine learning workflows.
Vulnerability Detail
The vulnerability identified as CVE-2021-37680 affects the fully connected layers implementation in TFLite, a component of TensorFlow GPU. The vulnerability arises due to a division by zero error in the code. An attacker could exploit this vulnerability to cause a denial of service (DoS) condition or potentially execute arbitrary code. The vulnerability has been patched in the latest version of TensorFlow, and fixes have been backported to previous versions 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.
-
>= 2.3.0, < 2.3.42.3.4pip install --upgrade "tensorflow-gpu==2.3.4" -
>= 2.4.0, < 2.4.32.4.3pip install --upgrade "tensorflow-gpu==2.4.3"
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 mentioned for this vulnerability. However, users can mitigate the risk by ensuring they update to the patched versions of TensorFlow GPU as soon as possible.
Conclusion
The division by zero vulnerability in TensorFlow GPU has been identified and patched in the latest versions. It is crucial for users to update their installations to the patched versions to mitigate the risk of exploitation. For further support and assistance with vulnerability remediation, please contact DevNack.com.
See every vulnerability recorded for tensorflow-gpu →
FAQ
TensorFlow GPU is a package that enables GPU acceleration for TensorFlow, allowing users to leverage the power of GPUs for faster machine learning computations.
The vulnerability could lead to a denial of service (DoS) condition or potential execution of arbitrary code if exploited by an attacker.
The vulnerability affects TensorFlow GPU versions 2.3.0 and above, including versions 2.3.4, 2.4.3, 2.5.1, and prior to 2.6.0.
Yes, the vulnerability has been patched in TensorFlow GPU version 2.6.0. Fixes have also been backported to versions 2.5.1, 2.4.3, and 2.3.4.
Users can update their TensorFlow GPU installations by following the official upgrade instructions provided by the TensorFlow project.
References
Related vulnerabilities
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