CVE-2022-35985: `CHECK` fail in `LRNGrad` in TensorFlow
First published: Fri Sep 16 2022(Updated: )
TensorFlow is an open source platform for machine learning. If `LRNGrad` is given an `output_image` input tensor that is not 4-D, it results in a `CHECK` fail that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit bd90b3efab4ec958b228cd7cfe9125be1c0cf255. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.
Credit: security-advisories@github.com
| Affected Software | Affected Version | How to fix |
|---|---|---|
| TensorFlow Keras | <2.7.2 | |
| TensorFlow Keras | >=2.8.0<2.8.1 | |
| TensorFlow Keras | >=2.9.0<2.9.1 | |
| TensorFlow Keras | =2.10-rc0 | |
| TensorFlow Keras | =2.10-rc1 | |
| TensorFlow Keras | =2.10-rc2 | |
| TensorFlow Keras | =2.10-rc3 |
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Reference Links
Frequently Asked Questions
What is the severity of CVE-2022-35985?
CVE-2022-35985 has been classified as a denial of service vulnerability.
How do I fix CVE-2022-35985?
To address CVE-2022-35985, upgrade TensorFlow to a version that is not affected, specifically versions 2.8.1 or higher.
Which versions of TensorFlow are affected by CVE-2022-35985?
CVE-2022-35985 affects TensorFlow versions up to and including 2.7.2, as well as specific versions between 2.8.0 and 2.9.0.
What type of attack can be caused by CVE-2022-35985?
CVE-2022-35985 can be exploited to trigger a denial of service attack.
What should I do if I cannot update TensorFlow due to compatibility issues with CVE-2022-35985?
If you cannot update TensorFlow, consider implementing input validation to ensure that the `output_image` tensor is 4-D.
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