Safety vulnerability ID: 42443
The information on this page was manually curated by our Cybersecurity Intelligence Team.
Tensorflow versions 2.4.4, 2.5.2 and 2.6.1 include a fix for CVE-2021-41196: In affected versions, the Keras pooling layers can trigger a segfault if the size of the pool is 0 or if a dimension is negative. This is due to the TensorFlow's implementation of pooling operations where the values in the sliding window are not checked to be strictly positive. The fix is included in TensorFlow 2.7.0.
https://github.com/tensorflow/tensorflow/security/advisories/GHSA-m539-j985-hcr8
Latest version: 2.18.0
TensorFlow is an open source machine learning framework for everyone.
TensorFlow is an open source platform for machine learning. In affected versions the Keras pooling layers can trigger a segfault if the size of the pool is 0 or if a dimension is negative. This is due to the TensorFlow's implementation of pooling operations where the values in the sliding window are not checked to be strictly positive. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range. See CVE-2021-41196.
CONFIRM:https://github.com/tensorflow/tensorflow/security/advisories/GHSA-m539-j985-hcr8: https://github.com/tensorflow/tensorflow/security/advisories/GHSA-m539-j985-hcr8
MISC:https://github.com/tensorflow/tensorflow/commit/12b1ff82b3f26ff8de17e58703231d5a02ef1b8b: https://github.com/tensorflow/tensorflow/commit/12b1ff82b3f26ff8de17e58703231d5a02ef1b8b
MISC:https://github.com/tensorflow/tensorflow/issues/51936: https://github.com/tensorflow/tensorflow/issues/51936
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