CVE-2022-23576: Integer overflow in Tensorflow

Published Feb 4, 2022
·
Updated

Impact The implementation of OpLevelCostEstimator::CalculateOutputSize is vulnerable to an integer overflow if an attacker can create an operation which would involve tensors with large enough number of elements: cc for (const auto& dim : outputshape.dim()) { outputsize = dim.size(); } Here, we can have a large enough number of dimensions in outputshape.dim() or just a small number of dimensions being large enough to cause an overflow in the multiplication.

Patches We have patched the issue in GitHub commit b9bd6cfd1c50e6807846af9a86f9b83cafc9c8ae.

The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.

For more information Please consult our security guide for more information regarding the security model and how to contact us with issues and questions.

Other sources

Tensorflow is an Open Source Machine Learning Framework. The implementation of OpLevelCostEstimator::CalculateOutputSize is vulnerable to an integer overflow if an attacker can create an operation which would involve tensors with large enough number of elements. We can have a large enough number of dimensions in outputshape.dim() or just a small number of dimensions being large enough to cause an overflow in the multiplication. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.

NVD

Affected Software

12 affected componentsFixes available
pip/tensorflow-gpu=2.7.0
2.7.1
pip/tensorflow-gpu>=2.6.0<2.6.3
2.6.3
pip/tensorflow-gpu<2.5.3
2.5.3
pip/tensorflow-cpu=2.7.0
2.7.1
pip/tensorflow-cpu>=2.6.0<2.6.3
2.6.3
pip/tensorflow-cpu<2.5.3
2.5.3
pip/tensorflow=2.7.0
2.7.1
pip/tensorflow>=2.6.0<2.6.3
2.6.3
pip/tensorflow<2.5.3
2.5.3
Google TensorFlow<=2.5.2
Google TensorFlow>=2.6.0<=2.6.2
Google TensorFlow=2.7.0

Event History

Feb 4, 2022
CVE Published
via MITRE·10:32 PM
Data Sourced
via MITRE·10:32 PM
DescriptionSeverityWeakness
Feb 10, 2022
Advisory Published
via GitHub·12:32 AM

Frequently Asked Questions

1

What is the severity of CVE-2022-23576?

CVE-2022-23576 is rated as high severity due to the integer overflow vulnerability that can lead to denial of service.

2

How do I fix CVE-2022-23576?

To remediate CVE-2022-23576, upgrade to TensorFlow version 2.7.1 or later.

3

Which versions of TensorFlow are affected by CVE-2022-23576?

CVE-2022-23576 affects TensorFlow versions up to 2.5.2, versions 2.6.0 to 2.6.2, and version 2.7.0.

4

What component of TensorFlow is affected by CVE-2022-23576?

The vulnerability in CVE-2022-23576 affects the OpLevelCostEstimator component in TensorFlow.

5

Can CVE-2022-23576 lead to remote code execution?

No, CVE-2022-23576 primarily leads to denial of service rather than remote code execution.

Contact

SecAlerts Pty Ltd.
132 Wickham Terrace
Fortitude Valley,
QLD 4006, Australia
info@secalerts.co
By using SecAlerts services, you agree to our services end-user license agreement. This website is safeguarded by reCAPTCHA and governed by the Google Privacy Policy and Terms of Service. All names, logos, and brands of products are owned by their respective owners, and any usage of these names, logos, and brands for identification purposes only does not imply endorsement. If you possess any content that requires removal, please get in touch with us.
© 2026 SecAlerts Pty Ltd.
ABN: 70 645 966 203, ACN: 645 966 203