CVE-2022-21737: Assertion failure based denial of service in Tensorflow

Published Feb 3, 2022
·
Updated

Impact The implementation of Bincount operations allows malicious users to cause denial of service by passing in arguments which would trigger a CHECK-fail:

python import tensorflow as tf

tf.rawops.DenseBincount( input=[[0], [1], [2]], size=[1], weights=[3,2,1], binaryoutput=False)

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.

Other sources

Tensorflow is an Open Source Machine Learning Framework. The implementation of Bincount operations allows malicious users to cause denial of service by passing in arguments which would trigger a CHECK-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. 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.

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 3, 2022
CVE Published
via MITRE·01:43 PM
Data Sourced
via MITRE·01:43 PM
DescriptionSeverity
Feb 9, 2022
Advisory Published
via GitHub·11:43 PM

Frequently Asked Questions

1

What is the severity of CVE-2022-21737?

CVE-2022-21737 has been classified with a severity level that indicates it can lead to denial of service attacks.

2

How do I fix CVE-2022-21737?

To mitigate CVE-2022-21737, update TensorFlow to version 2.7.1 or later.

3

Which versions of TensorFlow are affected by CVE-2022-21737?

CVE-2022-21737 affects TensorFlow versions up to 2.7.0, including 2.5.2 and 2.6.0 through 2.6.2.

4

Can CVE-2022-21737 cause system crashes?

Yes, exploiting CVE-2022-21737 can result in denial of service, potentially leading to application crashes.

5

Is TensorFlow GPU or CPU also affected by CVE-2022-21737?

Both TensorFlow GPU and CPU installations are affected by CVE-2022-21737.

Contact

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