Segfault in `QuantizedAvgPool` in TensorFlow
Vulnerability Description
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.
Impact Analysis
Refer to official advisory for detailed impact metrics.
Remediation
Ensure systems are updated to the latest vendor-supplied patch levels.
Am I Vulnerable?
Launch our assessment wizard to check if your infrastructure is exposed to • CVE-2022-35966
Credits & Attribution
No credits recorded in the NVD database.
References
More from tensorflow
View All →Affected Vendor
tensorflow
View all reports →