GHSA-vjg4-v33c-ggc4 Out of bounds read 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 `FractionalAvgPoolGrad` does not consider cases where the input tensors are invalid allowing an attacker to read from outside of bounds of heap: ```python import tensorflow as tf @tf.function def test(): y = tf.raw_ops.FractionalAvgPoolGrad( orig_input_tensor_shape=[2,2,2,2], out_backprop=[[[[1,2], [3, 4], [5, 6]], [[7, 8], [9,10], [11,12]]]], row_pooling_sequence=[-10,1,2,3], col_pooling_sequence=[1,2,3,4], overlapping=True) return y test() ``` Patches We have patched the issue in GitHub commit 002408c3696b173863228223d535f9de72a101a9. 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 Yu Tian of Qihoo 360 AIVul Team.