CVE-2021-41205: TensorFlow CPU - Out-of-Bounds Read in QuantizeAndDequantizeV* Operations

tensorflow-cpu Updated 02 Oct 2025

Summary

05/11/2021

Disclosed on

CVE-2021-41205

CVE

Yes i

Fix available

Unrated

Severity

Not published

CVSS Score

CVE-2021-41205: TensorFlow is an open source platform for machine learning. Affects tensorflow-cpu across 5 version ranges.

< 2.4.4 >= 2.5.0, < 2.5.2 >= 2.6.0, < 2.6.1 >= 2.7.0rc0, < 2.7.0 < 7cf73a2274732c9d82af51c2bc2cf90d13cd7e6d

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-2021-41205 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 open source platform for machine learning. It provides a comprehensive ecosystem of tools, libraries, and resources for developing and deploying machine learning models. TensorFlow CPU is a specific package within TensorFlow that focuses on running TensorFlow on CPUs. It is widely used in various industries and research domains for machine learning tasks.

Vulnerability Detail

The vulnerability identified as CVE-2021-41205 affects the shape inference functions for the QuantizeAndDequantizeV* operations in TensorFlow CPU. This issue can trigger a read outside the bounds of a heap-allocated array. An attacker could potentially exploit this vulnerability to read sensitive information or cause a denial of service. The vulnerability has been assigned the identifier PYSEC-2021-615 and is also tracked as GHSA-49rx-x2rw-pc6f. The issue has been fixed in TensorFlow 2.7.0, and the fix has been backported to TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these versions are still within the supported range.

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.

< 2.4.4 2.4.4

pip install --upgrade "tensorflow-cpu==2.4.4"

>= 2.5.0, < 2.5.2 2.5.2

pip install --upgrade "tensorflow-cpu==2.5.2"

>= 2.6.0, < 2.6.1 2.6.1

pip install --upgrade "tensorflow-cpu==2.6.1"

>= 2.7.0rc0, < 2.7.0 2.7.0

pip install --upgrade "tensorflow-cpu==2.7.0"

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. The recommended approach is to update to the fixed versions of TensorFlow CPU as mentioned in the 'how_to_fix' section.

Conclusion

In conclusion, the vulnerability identified as CVE-2021-41205 affects TensorFlow CPU versions 2.4.4, 2.5.2, 2.6.1, and 2.7.0rc0. It is crucial to update to the fixed versions (2.7.0, 2.6.1, 2.5.2, or 2.4.4) to address this vulnerability and mitigate the risk of exploitation. For further support and assistance in vulnerability remediation, you can reach out to DevNack.com.

See every vulnerability recorded for tensorflow-cpu →

FAQ

What is TensorFlow CPU?

TensorFlow CPU is a package within TensorFlow that focuses on running TensorFlow on CPUs. It provides the necessary components and optimizations for efficient execution of machine learning models on CPU architectures.

What are the possible consequences of this vulnerability?

This vulnerability can potentially be exploited by an attacker to read sensitive information or cause a denial of service. It is important to update to the fixed versions to mitigate the risk of exploitation.

Which versions of TensorFlow CPU are affected?

The vulnerability affects TensorFlow CPU versions 2.4.4, 2.5.2, 2.6.1, and 2.7.0rc0. It is recommended to update to the fixed versions mentioned in the 'how_to_fix' section.

Is there a workaround available for this vulnerability?

No specific workaround is mentioned for this vulnerability. Updating to the fixed versions is the recommended approach.

Where can I find more information about this vulnerability?

You can find more information about this vulnerability in the official TensorFlow advisory database. The source link is provided in the 'affected' section of this report.

References

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