Headline
GHSA-9vqj-64pv-w55c: TensorFlow vulnerable to `CHECK` fail in `tf.linalg.matrix_rank`
Impact
When tf.linalg.matrix_rank receives an empty input a, the GPU kernel gives a CHECK fail that can be used to trigger a denial of service attack.
import tensorflow as tf
a = tf.constant([], shape=[0, 1, 1], dtype=tf.float32)
tf.linalg.matrix_rank(a=a)
Patches
We have patched the issue in GitHub commit c55b476aa0e0bd4ee99d0f3ad18d9d706cd1260a.
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 Kang Hong Jin.
Impact
When tf.linalg.matrix_rank receives an empty input a, the GPU kernel gives a CHECK fail that can be used to trigger a denial of service attack.
import tensorflow as tf
a = tf.constant([], shape=[0, 1, 1], dtype=tf.float32) tf.linalg.matrix_rank(a=a)
Patches
We have patched the issue in GitHub commit c55b476aa0e0bd4ee99d0f3ad18d9d706cd1260a.
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 Kang Hong Jin.
References
- GHSA-9vqj-64pv-w55c
- tensorflow/tensorflow@c55b476
- https://github.com/tensorflow/tensorflow/releases/tag/v2.10.0
Related news
TensorFlow is an open source platform for machine learning. When `tf.linalg.matrix_rank` receives an empty input `a`, the GPU kernel gives a `CHECK` fail that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit c55b476aa0e0bd4ee99d0f3ad18d9d706cd1260a. 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. There are no known workarounds for this issue.