CVE-2021-37655: TensorFlow GPU - Out-of-Bounds Read Vulnerability
Summary
CVE-2021-37655: TensorFlow is an end-to-end open source platform for machine learning. Affects tensorflow-gpu across 3 version ranges.
< 01cff3f986259d661103412a20745928c727326f
>= 2.3.0, < 2.3.4
>= 2.4.0, < 2.4.3
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-2021-37655 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 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 (CVE-2021-37655) in TensorFlow GPU arises from incomplete validation of the relationship between the shapes of indices and updates in the tf.raw_ops.ResourceScatterUpdate function. By sending invalid arguments, an attacker can trigger a read from outside the bounds of heap allocated data. The implementation fails to check that the shape of indices is a prefix of the shape of updates, which can lead to broadcasting issues. This vulnerability can be exploited to read sensitive data or cause a denial-of-service condition.
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 provided for this vulnerability. However, users can mitigate the risk by ensuring that they only use valid arguments when invoking the tf.raw_ops.ResourceScatterUpdate function. It is recommended to validate the shapes of indices and updates before passing them to the function.
Conclusion
The vulnerability (CVE-2021-37655) in TensorFlow GPU exposes users to the risk of out-of-bounds reads and potential data exposure or denial-of-service attacks. It is crucial for users to update their TensorFlow GPU package to the patched versions once they are released. For further support on 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.
This vulnerability can be exploited by an attacker to read sensitive data or cause a denial-of-service condition in TensorFlow GPU.
The vulnerability affects TensorFlow GPU versions 2.3.0 and above. Specifically, versions 2.3.0 to 2.3.4, 2.4.0 to 2.4.3, and 2.5.1 are affected.
To fix this vulnerability, users should update their TensorFlow GPU package to the patched versions once they are released. The fix will be included in TensorFlow 2.6.0 and cherrypicked to TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4.
While there is no specific workaround provided, users can mitigate the risk by ensuring they only use valid arguments when invoking the vulnerable function and validating the shapes of indices and updates.
References
Related vulnerabilities
Recent vulnerabilities recorded for tensorflow-gpu.
