CVE-2022-41900: FractionalMaxPool and FractionalAVGPool heap out-of-bounds acess in Tensorflow
First published: Fri Nov 18 2022(Updated: )
TensorFlow is an open source platform for machine learning. The security vulnerability results in FractionalMax(AVG)Pool with illegal pooling_ratio. Attackers using Tensorflow can exploit the vulnerability. They can access heap memory which is not in the control of user, leading to a crash or remote code execution. We have patched the issue in GitHub commit 216525144ee7c910296f5b05d214ca1327c9ce48. The fix will be included in TensorFlow 2.11.0. We will also cherry pick this commit on TensorFlow 2.10.1.
Credit: security-advisories@github.com
| Affected Software | Affected Version | How to fix |
|---|---|---|
| Google TensorFlow | <2.8.4 | |
| Google TensorFlow | >=2.9.0<2.9.3 | |
| Google TensorFlow | =2.10.0 |
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Reference Links
Frequently Asked Questions
What is CVE-2022-41900?
CVE-2022-41900 is a security vulnerability in TensorFlow, an open source platform for machine learning.
What is the severity of CVE-2022-41900?
The severity of CVE-2022-41900 is critical with a CVSS score of 9.8.
How does CVE-2022-41900 affect TensorFlow?
CVE-2022-41900 affects TensorFlow 2.8.4, 2.9.0 to 2.9.3, and 2.10.0.
How can attackers exploit CVE-2022-41900?
Attackers can exploit CVE-2022-41900 by using TensorFlow's FractionalMax(AVG)Pool with an illegal pooling_ratio, allowing them to access heap memory not under user control, leading to a crash or remote code execution.
Is there a fix available for CVE-2022-41900?
Yes, a fix is available. Users should update to a patched version of TensorFlow.
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