CVE-2020-26267: TensorFlow GPU - Unvalidated DataFormatVecPermute API

tensorflow-gpu Updated 02 Oct 2025

Summary

10/12/2020

Disclosed on

CVE-2020-26267

CVE

Yes i

Fix available

Unrated

Severity

Not published

CVSS Score

CVE-2020-26267: In affected versions of TensorFlow the tf.raw_ops.DataFormatVecPermute API does not validate the src_format and dst_format attributes. Affects tensorflow-gpu across 6 version ranges.

< 1.15.5 >= 2.0.0, < 2.0.4 >= 2.1.0, < 2.1.3 >= 2.2.0, < 2.2.2 >= 2.3.0, < 2.3.2 < ebc70b7a592420d3d2f359e4b1694c236b82c7ae

Fixed in 5 releases; the minimum fixed version depends on the release line you run. How to fix ↓

Also tracked for

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

The same CVE-2020-26267 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 machine learning framework widely used for building and training neural networks. It provides a comprehensive ecosystem of tools, libraries, and resources for developing and deploying machine learning models. TensorFlow GPU is a variant of TensorFlow that leverages the power of GPUs for accelerated computation. It allows users to train and run machine learning models on GPU devices, enabling faster and more efficient processing of large datasets. However, a vulnerability has been discovered in TensorFlow GPU that affects versions 1.15.5, 2.0.4, 2.1.3, 2.2.2, 2.3.2, and 2.4.0.

Vulnerability Detail

The vulnerability, identified as CVE-2020-26267, resides in the tf.raw_ops.DataFormatVecPermute API of TensorFlow GPU. This API does not properly validate the src_format and dst_format attributes, assuming that they define a permutation of NHWC (number of samples, height, width, and channels). As a result, uninitialized memory accesses, reads outside of bounds, and crashes can occur. These memory-related issues can potentially lead to information disclosure, data corruption, or denial of service. The vulnerability has been fixed in the aforementioned versions of TensorFlow GPU.

How To Fix

Latest published version: 2.12.0 as of 22 Oct 2026

pip install --upgrade "tensorflow-gpu==2.12.0"

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.

< 1.15.5 1.15.5

pip install --upgrade "tensorflow-gpu==1.15.5"

>= 2.0.0, < 2.0.4 2.0.4

pip install --upgrade "tensorflow-gpu==2.0.4"

>= 2.1.0, < 2.1.3 2.1.3

pip install --upgrade "tensorflow-gpu==2.1.3"

>= 2.2.0, < 2.2.2 2.2.2

pip install --upgrade "tensorflow-gpu==2.2.2"

>= 2.3.0, < 2.3.2 2.3.2

pip install --upgrade "tensorflow-gpu==2.3.2"

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Workaround

There is no known workaround for this vulnerability. It is crucial to update TensorFlow GPU to the patched versions as soon as possible to mitigate the risk of exploitation.

Conclusion

In conclusion, the vulnerability in TensorFlow GPU's tf.raw_ops.DataFormatVecPermute API can lead to memory-related issues and potential security risks. It is crucial to update TensorFlow GPU to the patched versions to mitigate these risks. For further support and assistance in vulnerability remediation, please contact DevNack.com.

See every vulnerability recorded for tensorflow-gpu →

FAQ

What is TensorFlow GPU?

TensorFlow GPU is a variant of TensorFlow that utilizes GPUs for accelerated computation, enabling faster training and inference of machine learning models.

What is the tf.raw_ops.DataFormatVecPermute API?

The tf.raw_ops.DataFormatVecPermute API is a function in TensorFlow GPU that allows for permutation of data formats, specifically NHWC, which represents the order of dimensions in a tensor (number of samples, height, width, and channels).

What are the potential consequences of this vulnerability?

The vulnerability can result in uninitialized memory accesses, reads outside of bounds, and crashes. These memory-related issues can lead to information disclosure, data corruption, or denial of service.

Which versions of TensorFlow GPU are affected?

The vulnerability affects versions 1.15.5, 2.0.4, 2.1.3, 2.2.2, 2.3.2, and 2.4.0 of TensorFlow GPU.

How can I update TensorFlow GPU to the patched version?

Users can update TensorFlow GPU to the patched versions (1.15.5, 2.0.4, 2.1.3, 2.2.2, 2.3.2, or 2.4.0) by using the package manager or manually downloading and installing the updated version from the official TensorFlow repository.

References

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