First published: Fri Sep 16 2022(Updated: )
TensorFlow is an open source platform for machine learning. If `QuantizedAvgPool` is given `min_input` or `max_input` tensors of a nonzero rank, it results in a segfault that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 7cdf9d4d2083b739ec81cfdace546b0c99f50622. 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 | >=2.7.0<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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CVE-2022-35966 is classified as a denial of service vulnerability due to the potential for a segfault.
To fix CVE-2022-35966, update TensorFlow to a patched version released after commit 7cdf9d4d2083b739ec81cfdace546b0c99f50622.
CVE-2022-35966 affects TensorFlow versions from 2.7.0 to 2.7.2, 2.8.0 to 2.8.1, 2.9.0 to 2.9.1, and certain release candidates of 2.10.
CVE-2022-35966 can be exploited to create a denial of service by causing a segfault in the application.
The vendor of the software affected by CVE-2022-35966 is Google, specifically their TensorFlow platform.