TensorFlow vulnerable to Int overflow in `RaggedRangeOp`

Impact

The [RaggedRangOp](https://github.com/tensorflow/tensorflow/blob/0b6b491d21d6a4eb5fbab1cca565bc1e94ca9543/tensorflow/core/kernels/ragged_range_op.cc#L74-L88) function takes an argument limits that is eventually used to construct a TensorShape as an int64. If limits is a very large float, it can overflow when converted to an int64. This triggers an InvalidArgument but also throws an abort signal that crashes the program.

```python

import tensorflow as tf

tf.raw_ops.RaggedRange(starts=[1.1,0.1],limits=[10.0,1e20],deltas=[1,1])

`

Patches

We have patched the issue in GitHub commit [37cefa91bee4eace55715eeef43720b958a01192](https://github.com/tensorflow/tensorflow/commit/37cefa91bee4eace55715eeef43720b958a01192).

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 Jingyi Shi.