Headline
GHSA-qhw4-wwr7-gjc5: TensorFlow vulnerable to `CHECK` fail in `EmptyTensorList`
Impact
If EmptyTensorList receives an input element_shape with more than one dimension, it gives a CHECK fail that can be used to trigger a denial of service attack.
import tensorflow as tf
tf.raw_ops.EmptyTensorList(element_shape=tf.ones(dtype=tf.int32, shape=[1, 0]), max_num_elements=tf.constant(1),element_dtype=tf.int32)
Patches
We have patched the issue in GitHub commit c8ba76d48567aed347508e0552a257641931024d.
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 EmptyTensorList receives an input element_shape with more than one dimension, it gives a CHECK fail that can be used to trigger a denial of service attack.
import tensorflow as tf
tf.raw_ops.EmptyTensorList(element_shape=tf.ones(dtype=tf.int32, shape=[1, 0]), max_num_elements=tf.constant(1),element_dtype=tf.int32)
Patches
We have patched the issue in GitHub commit c8ba76d48567aed347508e0552a257641931024d.
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-qhw4-wwr7-gjc5
- tensorflow/tensorflow@c8ba76d
- https://github.com/tensorflow/tensorflow/releases/tag/v2.10.0
Related news
TensorFlow is an open source platform for machine learning. If `EmptyTensorList` receives an input `element_shape` with more than one dimension, it gives a `CHECK` fail that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit c8ba76d48567aed347508e0552a257641931024d. 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.