TensorFlow vulnerable to Out-of-Bounds Read in GRUBlockCellGrad

Impact

Out of bounds read in GRUBlockCellGrad

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.

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 for more information regarding the security model and how to contact us with issues and questions.

Attribution

This vulnerability has been reported by r3pwnx.