title: Crash in `max_pool3d` when size argument is 0 or negative
description: 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.
problem types: CWE-191: Integer Underflow (Wrap or Wraparound)
affected:
{
product: tensorflow
vendor: tensorflow
versions:
status: affected, version: >= 2.6.0, < 2.6.1
status: affected, version: >= 2.5.0, < 2.5.2
status: affected, version: < 2.4.4
}
metrics:
cvssV3_1: [
attackComplexity: LOW
attackVector: LOCAL
availabilityImpact: HIGH
baseScore: 5.5
baseSeverity: MEDIUM
confidentialityImpact: NONE
integrityImpact: NONE
privilegesRequired: LOW
scope: UNCHANGED
userInteraction: NONE
vectorString: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
version: 3.1
]