GHSA-87v6-crgm-2gfj Division by zero in Tensorflow

• PyPI tensorflow: < 2.5.3 → fixed in 2.5.3 • PyPI tensorflow: >= 2.6.0, < 2.6.3 → fixed in 2.6.3 • PyPI tensorflow: >= 2.7.0, < 2.7.1 → fixed in 2.7.1 • PyPI tensorflow-cpu: < 2.5.3 → fixed in 2.5.3 • PyPI tensorflow-cpu: >= 2.6.0, < 2.6.3 → fixed in 2.6.3 • PyPI tensorflow-cpu: >= 2.7.0, < 2.7.1 → fixed in 2.7.1 • PyPI tensorflow-gpu: < 2.5.3 → fixed in 2.5.3 • PyPI tensorflow-gpu: >= 2.6.0, < 2.6.3 → fixed in 2.6.3 • PyPI tensorflow-gpu: >= 2.7.0, < 2.7.1 → fixed in 2.7.1

Impact The implementation of `FractionalMaxPool` can be made to crash a TensorFlow process via a division by 0: ```python import tensorflow as tf import numpy as np tf.raw_ops.FractionalMaxPool( value=tf.constant(value=[[[[1, 4, 2, 3]]]], dtype=tf.int64), pooling_ratio=[1.0, 1.44, 1.73, 1.0], pseudo_random=False, overlapping=False, deterministic=False, seed=0, seed2=0, name=None) ``` Patches We have patched the issue in GitHub commit ba4e8ac4dc2991e350d5cc407f8598c8d4ee70fb. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range. For more information Please consult our security guide for more information regarding the security model and how to contact us with issues and questions. Attribution This vulnerability has been reported by Faysal Hossain Shezan from University of Virginia.