TensorFlow vulnerable to `CHECK` failures in `UnbatchGradOp`
### Impact
The `UnbatchGradOp`
https://github.com/tensorflow/tensorflow/blob/769eddaf479c8debead9a59a72617d6ed6f0fe10/tensorflow/core/kernels/batch_kernels.cc#L891 function takes an argument `id` that is assumed to be a scalar. A nonscalar `id` can trigger a `CHECK` failure and crash the program.
```python
import numpy as np
import tensorflow as tf
# `id` is not scalar
tf.raw_ops.UnbatchGrad(original_input= tf.constant([1]),batch_index=tf.constant([[0,0,0 ], ], dtype=tf.int64),grad=tf.constant([1,]),id=tf.constant([1,1,], dtype=tf.int64))
```
It also requires its argument `batch_index` to contain three times the number of elements as indicated in its `batch_index.dim_size(0)`. An incorrect `batch_index` can trigger a `CHECK` failure and crash the program.
```python
import numpy as np
import tensorflow as tf
# batch_index's size is not 3
tf.raw_ops.UnbatchGrad(original_input= tf.constant([1]),batch_index=tf.constant([[0,0], ], dtype=tf.int64),grad=tf.constant([1,]),id=tf.constant([1,], dtype=tf.int64))
```
### Patches
We have patched the issue in GitHub commit 5f945fc6409a3c1e90d6970c9292f805f6e6ddf2
https://github.com/tensorflow/tensorflow/commit/5f945fc6409a3c1e90d6970c9292f805f6e6ddf2.
The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, 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 Kang Hong Jin from Singapore Management University and 刘力源 from the Information System & Security and Countermeasures Experiments Center, Beijing Institute of Technology