CVE-2021-29619: TensorFlow - Segfault in SparseCountSparseOutput

tensorflow Updated 02 Oct 2025

Summary

14/05/2021

Disclosed on

CVE-2021-29619

CVE

Yes i

Fix available

Low

Severity

2.5

CVSS Score

CVE-2021-29619: TensorFlow is an end-to-end open source platform for machine learning. Affects tensorflow 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 < 82e6203221865de4008445b13c69b6826d2b28d9

Fixed in 4 releases; the minimum fixed version depends on the release line you run. How to fix ↓

Also tracked for

tensorflow · Bitnami
tensorflow-cpu · PyPI
tensorflow-gpu · PyPI

The same CVE-2021-29619 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 is widely used in various domains, including research, industry, and academia. It offers support for both CPU and GPU computations, making it suitable for a wide range of hardware configurations. However, a vulnerability has been discovered in TensorFlow that can lead to a segfault when passing invalid arguments to the tf.raw_ops.SparseCountSparseOutput function.

Vulnerability Detail

The vulnerability (CVE-2021-29619) in TensorFlow arises from the improper handling of invalid arguments passed to the tf.raw_ops.SparseCountSparseOutput function. This issue can be triggered by providing malformed inputs, which can be discovered through techniques like fuzzing. When these invalid arguments are encountered, TensorFlow crashes, resulting in a segmentation fault. This vulnerability can be exploited by an attacker to cause a denial-of-service (DoS) condition or potentially execute arbitrary code in the context of the affected TensorFlow application. The impact of this vulnerability can vary depending on the specific use case and the environment in which TensorFlow is deployed.

How To Fix

Latest published version: 2.21.0 as of 22 Oct 2026

pip install --upgrade "tensorflow==2.21.0"

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==2.1.4"

>= 2.2.0, < 2.2.3 2.2.3

pip install --upgrade "tensorflow==2.2.3"

>= 2.3.0, < 2.3.3 2.3.3

pip install --upgrade "tensorflow==2.3.3"

>= 2.4.0, < 2.4.2 2.4.2

pip install --upgrade "tensorflow==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 available for this vulnerability. The recommended approach is to apply the provided fix by upgrading to the latest patched version of TensorFlow.

Conclusion

In conclusion, TensorFlow is prone to a vulnerability that can result in a segfault when invalid arguments are passed to the tf.raw_ops.SparseCountSparseOutput function. This issue has been addressed in the latest versions of TensorFlow, and users are advised to update to the patched versions to mitigate the risk. For further support and assistance in vulnerability remediation, please contact DevNack.com.

See every vulnerability recorded for tensorflow →

FAQ

What is TensorFlow?

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

What is the impact of this vulnerability?

The vulnerability can lead to a segfault in TensorFlow, resulting in a denial-of-service (DoS) condition or potential execution of arbitrary code.

How can I check if my application is affected by this vulnerability?

You can use Vulert Playground (https://vulert.com/scanner) to check if your application is affected by this vulnerability. Vulert Playground allows you to analyze your Pipfile.lock and provides real-time alerts for open-source vulnerabilities.

Are all versions of TensorFlow affected by this vulnerability?

No, only certain versions of TensorFlow are affected. The vulnerability has been fixed in TensorFlow 2.5.0, TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3, and TensorFlow 2.1.4.

Is there a workaround available for this vulnerability?

No, there is no specific workaround available. It is recommended to upgrade to the latest patched version of TensorFlow.

References

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