TensorFlow has Segfault in Bincount with XLA

Impact

When running with XLA, tf.raw_ops.Bincount segfaults when given a parameter weights that is neither the same shape as parameter arr nor a length-0 tensor.

```python

import tensorflow as tf

func = tf.raw_ops.Bincount

para={'arr': 6, 'size': 804, 'weights': [52, 351]}

@tf.function(jit_compile=True)

def fuzz_jit():

y = func(**para)

return y

print(fuzz_jit())

`

Patches

We have patched the issue in GitHub commit [8ae76cf085f4be26295d2ecf2081e759e04b8acf](https://github.com/tensorflow/tensorflow/commit/8ae76cf085f4be26295d2ecf2081e759e04b8acf).

The fix will be included in TensorFlow 2.12. We will also cherrypick this commit on TensorFlow 2.11.1.

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 r3pwnx of 360 AIVul Team