CVE-2021-29552: Denial of Service in TensorFlow

tensorflow-gpu Updated 02 Oct 2025

Summary

14/05/2021

Disclosed on

CVE-2021-29552

CVE

Yes i

Fix available

Unrated

Severity

Not published

CVSS Score

CVE-2021-29552: 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 < 704866eabe03a9aeda044ec91a8d0c83fc1ebdbe

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-2021-29552 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 is widely used in various industries and research domains for tasks such as image recognition, natural language processing, and recommendation systems.

Vulnerability Detail

The vulnerability identified as CVE-2021-29552 affects TensorFlow versions 2.1.4 to 2.4.3. It arises from a flaw in the implementation of the UnsortedSegmentJoin function. An attacker can exploit this vulnerability by controlling the values of the num_segments tensor argument. The implementation assumes that the num_segments tensor is a valid scalar, but if the tensor is empty, the validation check fails and leads to process termination. This vulnerability can be exploited to cause a denial of service (DoS) attack. The issue has been addressed in TensorFlow 2.5.0, and patches have been backported to TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3, and TensorFlow 2.1.4.

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.

< 2.2.0rc0 2.2.0rc0

pip install --upgrade "tensorflow-gpu==2.2.0rc0"

>= 2.2.0, < 2.3.0rc0 2.3.0rc0

pip install --upgrade "tensorflow-gpu==2.3.0rc0"

>= 2.3.0, < 2.3.4 2.3.4

pip install --upgrade "tensorflow-gpu==2.3.4"

>= 2.4.0, < 2.4.3 2.4.3

pip 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 known workaround for this vulnerability. It is recommended to apply the provided fix or update TensorFlow to the latest version.

Conclusion

The vulnerability identified as CVE-2021-29552 in TensorFlow can be exploited to cause a denial of service (DoS) attack. It is crucial to update TensorFlow to version 2.5.0 or apply the appropriate patches to mitigate the risk. Keeping software up to date is essential for maintaining the security and stability of TensorFlow-based applications. For further assistance or support in vulnerability remediation, please contact DevNack.com.

See every vulnerability recorded for tensorflow-gpu →

FAQ

What is TensorFlow?

TensorFlow is an open source platform for machine learning that provides a comprehensive set of tools and resources for developing and deploying machine learning models.

What is the impact of this vulnerability?

This vulnerability can be exploited by an attacker to cause a denial of service (DoS) attack, leading to process termination and potential disruption of TensorFlow-based applications.

Which versions of TensorFlow are affected?

The vulnerability affects TensorFlow versions 2.1.4 to 2.4.3. TensorFlow 2.5.0 and patched versions of TensorFlow 2.4.2, 2.3.3, 2.2.3, and 2.1.4 are not affected.

Is there a workaround available?

No, there is no known workaround for this vulnerability. It is recommended to update TensorFlow to the latest version or apply the provided patches.

How can I update TensorFlow?

Users can update TensorFlow by using the package manager or following the instructions provided by the TensorFlow project. It is important to keep the software up to date to mitigate the risk of this vulnerability.

References

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