Headline
GHSA-p7hr-f446-x6qf: TensorFlow vulnerable to `CHECK` fail in `tf.sparse.cross`
Impact
If tf.sparse.cross receives an input separator that is not a scalar, it gives a CHECK fail that can be used to trigger a denial of service attack.
import tensorflow as tf
tf.sparse.cross(inputs=[],name='a',separator=tf.constant(['a', 'b'],dtype=tf.string))
Patches
We have patched the issue in GitHub commit 83dcb4dbfa094e33db084e97c4d0531a559e0ebf.
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
If tf.sparse.cross receives an input separator that is not a scalar, it gives a CHECK fail that can be used to trigger a denial of service attack.
import tensorflow as tf
tf.sparse.cross(inputs=[],name=’a’,separator=tf.constant(['a’, ‘b’],dtype=tf.string))
Patches
We have patched the issue in GitHub commit 83dcb4dbfa094e33db084e97c4d0531a559e0ebf.
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-p7hr-f446-x6qf
- tensorflow/tensorflow@83dcb4d
- https://github.com/tensorflow/tensorflow/releases/tag/v2.10.0
Related news
TensorFlow is an open source platform for machine learning. If `tf.sparse.cross` receives an input `separator` that is not a scalar, it gives a `CHECK` fail that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 83dcb4dbfa094e33db084e97c4d0531a559e0ebf. 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.