CVE-2021-29585: TensorFlow GPU - Padding Computation Vulnerability
Summary
CVE-2021-29585: TensorFlow is an end-to-end open source platform for machine learning. Affects tensorflow-gpu across 5 version ranges.
>= 2.2.0, < 2.3.0rc0
< 2.2.0rc0
>= 2.3.0, < 2.3.4
>= 2.4.0, < 2.4.3
< 49847ae69a4e1a97ae7f2db5e217c77721e37948
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-2021-29585 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 developing and deploying machine learning models. TensorFlow GPU is a variant of TensorFlow that leverages GPU hardware for accelerated computation. It is widely used in various industries and research domains for training and inference of machine learning models.
Vulnerability Detail
The vulnerability (CVE-2021-29585) exists in the TFLite computation for size of output after padding in TensorFlow GPU. The function responsible for this computation, ComputeOutSize, does not validate the stride argument before performing a division operation. This allows an attacker to craft malicious models that can trigger a division by zero error, leading to potential crashes or undefined behavior. The vulnerability affects versions of TensorFlow GPU up to and including 2.4.3.
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.
-
< 2.2.0rc02.2.0rc0pip install --upgrade "tensorflow-gpu==2.2.0rc0" -
>= 2.2.0, < 2.3.0rc02.3.0rc0pip install --upgrade "tensorflow-gpu==2.3.0rc0" -
>= 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"
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Workaround
There is no known workaround for this vulnerability. It is recommended to apply the official fix by upgrading to the patched versions of TensorFlow GPU.
Conclusion
The padding computation vulnerability in TensorFlow GPU (CVE-2021-29585) can be mitigated by upgrading to the patched versions of TensorFlow. It is crucial to keep your machine learning environment up to date to ensure the security and stability of your models. For further support and assistance in vulnerability remediation, please contact DevNack.com.
See every vulnerability recorded for tensorflow-gpu →
FAQ
TensorFlow GPU is a variant of TensorFlow that utilizes GPU hardware for accelerated computation. It is commonly used for training and inference of machine learning models.
This vulnerability allows an attacker to craft malicious models that can trigger a division by zero error, potentially leading to crashes or undefined behavior.
Versions of TensorFlow GPU up to and including 2.4.3 are affected by this vulnerability.
Yes, the vulnerability has been fixed in TensorFlow 2.5.0. The fix has also been backported to TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3, and TensorFlow 2.1.4.
No, there is no known workaround for this vulnerability. It is recommended to upgrade to the patched versions of TensorFlow GPU.
References
Related vulnerabilities
Recent vulnerabilities recorded for tensorflow-gpu.
