Division by 0 in `Conv2D`
### Impact
An attacker can trigger a division by 0 in `tf.raw_ops.Conv2D`:
```python
import tensorflow as tf
input = tf.constant([], shape=[0, 0, 0, 0], dtype=tf.float32)
filter = tf.constant([], shape=[0, 0, 0, 0], dtype=tf.float32)
strides = [1, 1, 1, 1]
padding = "SAME"
tf.raw_ops.Conv2D(input=input, filter=filter, strides=strides, padding=padding)
```
This is because the implementation
https://github.com/tensorflow/tensorflow/blob/988087bd83f144af14087fe4fecee2d250d93737/tensorflow/core/kernels/conv_ops.cc#L261-L263 does a division by a quantity that is controlled by the caller:
```cc
const int64 patch_depth = filter.dim_size(2);
if (in_depth % patch_depth != 0) { ... }
```
### Patches
We have patched the issue in GitHub commit b12aa1d44352de21d1a6faaf04172d8c2508b42b
https://github.com/tensorflow/tensorflow/commit/b12aa1d44352de21d1a6faaf04172d8c2508b42b.
The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, 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 Ying Wang and Yakun Zhang of Baidu X-Team.