CVE-2021-41201: TensorFlow CPU - Uninitialized Variable Access in EinsumHelper::ParseEquation()

tensorflow-cpu Updated 02 Oct 2025

Summary

05/11/2021

Disclosed on

CVE-2021-41201

CVE

Yes i

Fix available

Unrated

Severity

Not published

CVSS Score

CVE-2021-41201: 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 < f09caa532b6e1ac8d2aa61b7832c78c5b79300c6

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-2021-41201 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 computations on CPUs. It is widely used in various industries and research fields for machine learning tasks.

Vulnerability Detail

The vulnerability (CVE-2021-41201) exists in TensorFlow CPU versions prior to 2.7.0. During execution, the EinsumHelper::ParseEquation() function is responsible for setting flags in the input_has_ellipsis vector and *output_has_ellipsis boolean to indicate the presence of ellipsis in the corresponding inputs and output. However, the code only sets these flags to true and never assigns them false. This leads to uninitialized variable access if callers assume that EinsumHelper::ParseEquation() always sets these flags. The impact of this vulnerability can vary depending on how the uninitialized variables are used by the callers, but it can potentially result in unexpected behavior, crashes, or even security vulnerabilities.

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 upgrade to the fixed version of TensorFlow CPU.

Conclusion

The vulnerability (CVE-2021-41201) in TensorFlow CPU versions prior to 2.7.0 can lead to uninitialized variable access, potentially resulting in unexpected behavior, crashes, or security vulnerabilities. It is crucial to upgrade to the fixed version of TensorFlow CPU (2.7.0 or later) or apply the backported fixes in versions 2.4.4, 2.5.2, or 2.6.1. For further support on 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 allows running TensorFlow computations on CPUs. It is designed for systems without GPU support or for scenarios where GPU acceleration is not required.

What is the impact of this vulnerability?

The impact of this vulnerability can vary depending on how the uninitialized variables are used by the callers. It can lead to unexpected behavior, crashes, or even security vulnerabilities.

Which versions of TensorFlow CPU are affected?

The vulnerability affects TensorFlow CPU versions prior to 2.7.0. Specifically, versions 2.4.4, 2.5.2, and 2.6.1 are also affected and have been patched.

How can I fix this vulnerability?

To fix this vulnerability, it is recommended to upgrade your TensorFlow CPU package to version 2.7.0 or later. Alternatively, you can also update to the backported fixes in versions 2.4.4, 2.5.2, or 2.6.1.

Is there a workaround available?

There is no specific workaround mentioned for this vulnerability. The recommended approach is to upgrade to the fixed version of TensorFlow CPU.

References

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