First published: Fri Sep 16 2022(Updated: )
TensorFlow is an open source platform for machine learning. If `QuantizeDownAndShrinkRange` is given nonscalar inputs for `input_min` or `input_max`, it results in a segfault that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 73ad1815ebcfeb7c051f9c2f7ab5024380ca8613. 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<2.8.1 | |
Google TensorFlow | >=2.9.0<2.9.1 | |
Google TensorFlow | =2.10-rc0 | |
Google TensorFlow | =2.10-rc1 | |
Google TensorFlow | =2.10-rc2 | |
Google TensorFlow | =2.10-rc3 |
Sign up to SecAlerts for real-time vulnerability data matched to your software, aggregated from hundreds of sources.