CVE-2022-35972: Segfault in `QuantizedBiasAdd` in TensorFlow
TensorFlow is an open source platform for machine learning. If QuantizedBiasAdd is given mininput, maxinput, minbias, maxbias 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 785d67a78a1d533759fcd2f5e8d6ef778de849e0. 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.
Affected Software
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Event History
Frequently Asked Questions
What is the severity of CVE-2022-35972?
CVE-2022-35972 has been identified as a vulnerability that can lead to a denial of service due to a segmentation fault.
How do I fix CVE-2022-35972?
To fix CVE-2022-35972, you should update to a patched version of TensorFlow that addresses this issue.
Which versions of TensorFlow are affected by CVE-2022-35972?
CVE-2022-35972 affects TensorFlow versions from 2.7.0 up to, but not including, 2.7.2 and further includes similar ranges up to 2.10-rc3.
What types of attacks can CVE-2022-35972 facilitate?
CVE-2022-35972 can be exploited to trigger a denial of service attack.
Is there an official patch for CVE-2022-35972?
Yes, TensorFlow has released a patch for CVE-2022-35972 on GitHub.