First published: Fri Sep 16 2022(Updated: )
TensorFlow is an open source platform for machine learning. The implementation of `FractionalAvgPoolGrad` does not fully validate the input `orig_input_tensor_shape`. This results in an overflow that results in a `CHECK` failure which can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 03a659d7be9a1154fdf5eeac221e5950fec07dad. 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 |
---|---|---|
Google TensorFlow | >=2.7.0<2.7.2 | |
Google TensorFlow | =2.8.0 | |
Google TensorFlow | =2.9.0 | |
Google TensorFlow | =2.10-rc0 | |
Google TensorFlow | =2.10-rc1 | |
Google TensorFlow | =2.10-rc2 | |
Google TensorFlow | =2.10-rc3 |
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CVE-2022-35963 is classified as a denial of service vulnerability due to an overflow in the `FractionalAvgPoolGrad` implementation.
To fix CVE-2022-35963, upgrade TensorFlow to a version that is not vulnerable, such as any version beyond the ones listed in the affected software section.
CVE-2022-35963 affects TensorFlow versions from 2.7.0 to 2.10-rc3.
CVE-2022-35963 can be exploited to trigger a denial of service attack.
Yes, CVE-2022-35963 is related to the lack of proper input validation for the `orig_input_tensor_shape`.