Overflow/denial of service in `tf.raw_ops.ReverseSequence`
### Impact
The implementation of `tf.raw_ops.ReverseSequence` allows for stack overflow and/or `CHECK`-fail based denial of service.
```python
import tensorflow as tf
input = tf.zeros([1, 1, 1], dtype=tf.int32)
seq_lengths = tf.constant([0], shape=[1], dtype=tf.int32)
tf.raw_ops.ReverseSequence(
input=input, seq_lengths=seq_lengths, seq_dim=-2, batch_dim=0)
```
The implementation
https://github.com/tensorflow/tensorflow/blob/5b3b071975e01f0d250c928b2a8f901cd53b90a7/tensorflow/core/kernels/reverse_sequence_op.cc#L114-L118 fails to validate that `seq_dim` and `batch_dim` arguments are valid.
Negative values for `seq_dim` can result in stack overflow or `CHECK`-failure, depending on the version of Eigen code used to implement the operation. Similar behavior can be exhibited by invalid values of `batch_dim`.
### Patches
We have patched the issue in GitHub commit ecf768cbe50cedc0a45ce1ee223146a3d3d26d23
https://github.com/tensorflow/tensorflow/commit/ecf768cbe50cedc0a45ce1ee223146a3d3d26d23.
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.