CVE-2021-29615: TensorFlow GPU - Stack Overflow in ParseAttrValue

tensorflow-gpu Updated 02 Oct 2025

Summary

14/05/2021

Disclosed on

CVE-2021-29615

CVE

Yes i

Fix available

Unrated

Severity

Not published

CVSS Score

CVE-2021-29615: 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 < e07e1c3d26492c06f078c7e5bf2d138043e199c1

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-2021-29615 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 (CVE-2021-29615) in TensorFlow GPU arises from a stack overflow issue in the implementation of the ParseAttrValue function. This function, located in the attr_value_util.cc file, is responsible for parsing attribute values in TensorFlow. By providing a specially crafted input, an attacker can trigger a recursive call to ParseAttrValue, leading to a stack overflow. This vulnerability can potentially be exploited to execute arbitrary code or cause a denial-of-service (DoS) 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.

< 2.1.4 2.1.4

pip install --upgrade "tensorflow-gpu==2.1.4"

>= 2.2.0, < 2.2.3 2.2.3

pip install --upgrade "tensorflow-gpu==2.2.3"

>= 2.3.0, < 2.3.3 2.3.3

pip install --upgrade "tensorflow-gpu==2.3.3"

>= 2.4.0, < 2.4.2 2.4.2

pip install --upgrade "tensorflow-gpu==2.4.2"

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. It is recommended to apply the fix by upgrading to the patched versions of TensorFlow GPU.

Conclusion

The vulnerability (CVE-2021-29615) in TensorFlow GPU can lead to a stack overflow when parsing attribute values, potentially enabling arbitrary code execution or causing a denial-of-service condition. It is crucial to upgrade to the patched versions of TensorFlow GPU (2.5.0 or later) or apply the backported fixes in versions 2.4.2, 2.3.3, 2.2.3, or 2.1.4. Vulert's vulnerability monitoring service can help you identify if your application is affected by this vulnerability. For further support on vulnerability remediation, please contact DevNack.com.

See every vulnerability recorded for tensorflow-gpu →

FAQ

What is TensorFlow GPU?

TensorFlow GPU is a package that enables GPU acceleration for TensorFlow, allowing users to leverage the power of GPUs for faster machine learning computations.

What is the impact of this vulnerability?

This vulnerability can potentially be exploited by an attacker to execute arbitrary code or cause a denial-of-service (DoS) condition in systems using the affected versions of TensorFlow GPU.

Which versions of TensorFlow GPU are affected?

The vulnerability affects TensorFlow GPU versions 2.1.4 and above, including versions 2.2.3, 2.3.3, 2.4.2, and any versions prior to the fix in 2.5.0.

Are there any known instances of this vulnerability being exploited?

There are no known instances of this vulnerability being exploited in the wild at the time of this advisory.

How can I check if my application is affected?

You can use Vulert's vulnerability monitoring service to check if your application is affected by this vulnerability. Vulert analyzes your Pipfile.lock and provides real-time alerts for open-source vulnerabilities, including this one.

References

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