Assertion failure based denial of service in Tensorflow
Moderate severity
GitHub Reviewed
Published
Feb 2, 2022
in
tensorflow/tensorflow
•
Updated Feb 3, 2023
Description
Published by the National Vulnerability Database
Feb 3, 2022
Reviewed
Feb 3, 2022
Published to the GitHub Advisory Database
Feb 9, 2022
Last updated
Feb 3, 2023
Impact
The implementation of
*Bincount
operations allows malicious users to cause denial of service by passing in arguments which would trigger aCHECK
-fail:There are several conditions that the input arguments must satisfy. Some are not caught during shape inference and others are not caught during kernel implementation. This results in
CHECK
failures later when the output tensors get allocated.Patches
We have patched the issue in GitHub commit 7019ce4f68925fd01cdafde26f8d8c938f47e6f9.
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.
Attribution
This vulnerability has been reported by Faysal Hossain Shezan from University of Virginia.
References