CVE-2021-29557: Denial of Service in TensorFlow

tensorflow-cpu Updated 02 Oct 2025

Summary

14/05/2021

Disclosed on

CVE-2021-29557

CVE

Yes i

Fix available

Unrated

Severity

Not published

CVSS Score

CVE-2021-29557: TensorFlow is an end-to-end open source platform for machine learning. Affects tensorflow-cpu 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 < 7f283ff806b2031f407db64c4d3edcda8fb9f9f5

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-gpu · PyPI

The same CVE-2021-29557 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. However, a vulnerability has been discovered in TensorFlow that can lead to a denial of service (DoS) attack.

Vulnerability Detail

The vulnerability, identified as CVE-2021-29557, exists in the tf.raw_ops.SparseMatMul function of TensorFlow. An attacker can exploit this vulnerability by causing a runtime error related to fixed-point encoding (FPE). The error occurs due to a division by zero deep within the Eigen code, triggered when the b tensor is empty. This vulnerability can be exploited to cause a DoS condition in TensorFlow. The impact of this vulnerability can disrupt machine learning processes and potentially lead to service unavailability.

How To Fix

Latest published version: 2.21.0 as of 22 Oct 2026

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

>= 2.2.0, < 2.2.3 2.2.3

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

>= 2.3.0, < 2.3.3 2.3.3

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

>= 2.4.0, < 2.4.2 2.4.2

pip install --upgrade "tensorflow-cpu==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

No specific workaround has been provided for this vulnerability. The recommended solution is to update TensorFlow to the patched version.

Conclusion

The vulnerability in TensorFlow (CVE-2021-29557) can lead to a denial of service (DoS) condition. Users are advised to update their TensorFlow installations to the latest patched version as soon as it becomes available. This will ensure the security and stability of machine learning processes. For further support on vulnerability remediation, please contact DevNack.com.

See every vulnerability recorded for tensorflow-cpu →

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 to cause a denial of service (DoS) condition in TensorFlow, potentially disrupting machine learning processes and leading to service unavailability.

How can I fix this vulnerability?

To fix this vulnerability, users should update their TensorFlow installations to the latest patched version as soon as it becomes available. The TensorFlow development team has backported the fix to earlier versions as well.

Are all versions of TensorFlow affected?

No, not all versions of TensorFlow are affected. The vulnerability exists in TensorFlow versions 2.1.4 and above. Earlier versions are not impacted.

Is there a workaround for this vulnerability?

No specific workaround has been provided for this vulnerability. Updating TensorFlow to the patched version is the recommended solution.

References

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