Safety vulnerability ID: 51066
The information on this page was manually curated by our Cybersecurity Intelligence Team.
TensorFlow 2.7.4, 2.8.3 and 2.9.2 include a fix for CVE-2022-35972: Segfault in 'QuantizedBiasAdd'.
https://github.com/tensorflow/tensorflow/security/advisories/GHSA-4pc4-m9mj-v2r9
Latest version: 2.18.0
TensorFlow is an open source machine learning framework for everyone.
TensorFlow is an open source platform for machine learning. If `QuantizedBiasAdd` is given `min_input`, `max_input`, `min_bias`, `max_bias` 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. See CVE-2022-35972.
CONFIRM:https://github.com/tensorflow/tensorflow/security/advisories/GHSA-4pc4-m9mj-v2r9: https://github.com/tensorflow/tensorflow/security/advisories/GHSA-4pc4-m9mj-v2r9
MISC:https://github.com/tensorflow/tensorflow/commit/785d67a78a1d533759fcd2f5e8d6ef778de849e0: https://github.com/tensorflow/tensorflow/commit/785d67a78a1d533759fcd2f5e8d6ef778de849e0
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