CVE-2021-29603: TensorFlow-GPU Out-of-Bounds Write Vulnerability
Summary
CVE-2021-29603: TensorFlow is an end-to-end open source platform for machine learning. Affects tensorflow-gpu across 5 version ranges.
< 2.1.4
>= 2.2.0, < 2.2.3
>= 2.3.0, < 2.3.3
>= 2.4.0, < 2.4.2
< c59c37e7b2d563967da813fa50fe20b21f4da683
Fixed in 4 releases; the minimum fixed version depends on the release line you run. How to fix ↓
Also tracked for
- tensorflow · Bitnami
- tensorflow · PyPI
- tensorflow · PyPI
- tensorflow-cpu · PyPI
The same CVE-2021-29603 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 community resources that enable researchers and developers to build and deploy machine learning models. TensorFlow-GPU is a variant of TensorFlow that leverages GPU acceleration for faster training and inference. This vulnerability affects the TensorFlow-GPU package.
Vulnerability Detail
A specially crafted TFLite model can trigger an out-of-bounds write on the heap in the TFLite implementation of ArgMin/ArgMax. The issue arises when the axis_value parameter is not within the range of 0 and the number of dimensions of the input tensor. In such cases, the condition in the code is never true, causing the code to write beyond the last valid element of the output_dims->data array. This vulnerability can potentially lead to memory corruption and may be exploited by an attacker to execute arbitrary code or crash the application.
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.
-
< 2.1.42.1.4pip install --upgrade "tensorflow-gpu==2.1.4" -
>= 2.2.0, < 2.2.32.2.3pip install --upgrade "tensorflow-gpu==2.2.3" -
>= 2.3.0, < 2.3.32.3.3pip install --upgrade "tensorflow-gpu==2.3.3" -
>= 2.4.0, < 2.4.22.4.2pip install --upgrade "tensorflow-gpu==2.4.2"
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Workaround
There is no known workaround for this vulnerability. It is recommended to apply the provided fix by updating to a patched version of TensorFlow-GPU.
Conclusion
The TensorFlow-GPU package is vulnerable to an out-of-bounds write issue in the TFLite implementation of ArgMin/ArgMax. This vulnerability can be mitigated by updating to a patched version of TensorFlow-GPU. It is recommended to upgrade to TensorFlow-GPU 2.5.0 or one of the backported patched versions (2.4.2, 2.3.3, 2.2.3, or 2.1.4). For further support on vulnerability remediation, please contact DevNack.com.
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FAQ
TensorFlow is an open source platform for machine learning that provides a comprehensive set of tools and libraries for building and deploying machine learning models.
TensorFlow-GPU is a variant of TensorFlow that leverages GPU acceleration for faster training and inference.
An out-of-bounds write vulnerability occurs when a program writes data beyond the boundaries of a buffer or array, potentially overwriting adjacent memory and leading to memory corruption or other security issues.
This vulnerability can be exploited by an attacker to execute arbitrary code or crash the application, potentially leading to a denial-of-service condition or other security breaches.
You can use the Vulert Playground at Vulert Scanner to check if your application is affected by this vulnerability. Simply provide your Pipfile.lock file, and Vulert will analyze it for open-source vulnerabilities in real-time.
References
Related vulnerabilities
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