CVE-2021-29534: Denial of Service in TensorFlow

tensorflow-cpu Updated 02 Oct 2025

Summary

14/05/2021

Disclosed on

CVE-2021-29534

CVE

Yes i

Fix available

Unrated

Severity

Not published

CVSS Score

CVE-2021-29534: TensorFlow is an end-to-end open source platform for machine learning. Affects tensorflow-cpu 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 < 69c68ecbb24dff3fa0e46da0d16c821a2dd22d7c

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-2021-29534 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 industries and research domains for tasks such as image recognition, natural language processing, and recommendation systems.

Vulnerability Detail

The vulnerability identified as CVE-2021-29534 affects the TensorFlow package. It can be exploited by an attacker to trigger a denial of service (DoS) attack. The specific vulnerability lies in the tf.raw_ops.SparseConcat function. The implementation of this function uses the values specified in shapes[0] as dimensions for the output shape. However, the TensorShape constructor used in this implementation has a legacy implementation that uses a CHECK operation. This CHECK operation triggers when the InitDims function returns a non-OK status, leading to a DoS condition. The vulnerability can be exploited by an attacker to cause the affected TensorFlow application to crash or become unresponsive, disrupting its normal operation.

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.

< 2.2.0rc0 2.2.0rc0

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

>= 2.2.0, < 2.3.0rc0 2.3.0rc0

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

>= 2.3.0, < 2.3.4 2.3.4

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

>= 2.4.0, < 2.4.3 2.4.3

pip install --upgrade "tensorflow-cpu==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 mentioned for this vulnerability. Users are recommended to apply the provided patches or update their TensorFlow installations to the latest patched version.

Conclusion

The vulnerability identified as CVE-2021-29534 in TensorFlow can be exploited by an attacker to trigger a denial of service (DoS) attack. To mitigate this vulnerability, users of TensorFlow should update their installations to the latest patched version. The TensorFlow development team has released updates that include the necessary fixes. 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 building and deploying machine learning models.

What is the impact of this vulnerability?

This vulnerability can be exploited by an attacker to trigger a denial of service (DoS) attack, causing the affected TensorFlow application to crash or become unresponsive.

How can I fix this vulnerability?

To fix this vulnerability, users of TensorFlow are advised to update their installations to the latest patched version, which includes the necessary fixes.

Are older versions of TensorFlow affected?

Yes, older versions of TensorFlow, specifically versions 2.4.2, 2.3.3, 2.2.3, and 2.1.4, are also affected by this vulnerability. Users of these versions should update to the latest patched version.

Is there a workaround available?

There is no specific workaround mentioned for this vulnerability. Users are recommended to apply the provided patches or update their TensorFlow installations to the latest patched version.

References

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