CVE-2022-21730: Out of bounds read in Tensorflow

Published Feb 3, 2022
·
Updated

Impact The implementation of FractionalAvgPoolGrad does not consider cases where the input tensors are invalid allowing an attacker to read from outside of bounds of heap:

python import tensorflow as tf

@tf.function def test(): y = tf.rawops.FractionalAvgPoolGrad( originputtensorshape=[2,2,2,2], outbackprop=[[[[1,2], [3, 4], [5, 6]], [[7, 8], [9,10], [11,12]]]], rowpoolingsequence=[-10,1,2,3], colpoolingsequence=[1,2,3,4], overlapping=True) return y test()

Patches We have patched the issue in GitHub commit 002408c3696b173863228223d535f9de72a101a9.

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 Yu Tian of Qihoo 360 AIVul Team.

Other sources

Tensorflow is an Open Source Machine Learning Framework. The implementation of FractionalAvgPoolGrad does not consider cases where the input tensors are invalid allowing an attacker to read from outside of bounds of heap. 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·10:48 AM
Data Sourced
via MITRE·10:48 AM
DescriptionSeverity
Feb 9, 2022
Advisory Published
via GitHub·06:29 PM

Frequently Asked Questions

1

What is the severity of CVE-2022-21730?

CVE-2022-21730 has been classified with a moderate severity level due to potential input validation issues.

2

How do I fix CVE-2022-21730?

To fix CVE-2022-21730, update TensorFlow to version 2.5.3, 2.6.3, or 2.7.1 depending on the version you are currently using.

3

What software is affected by CVE-2022-21730?

CVE-2022-21730 affects Google TensorFlow versions up to 2.5.2, and versions from 2.6.0 to 2.6.2, as well as version 2.7.0.

4

What type of vulnerability is CVE-2022-21730?

CVE-2022-21730 is primarily an input validation vulnerability within the `FractionalAvgPoolGrad` implementation.

5

Can CVE-2022-21730 cause application crashes?

Yes, CVE-2022-21730 can lead to potential application crashes if invalid input tensors are processed.

Contact

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