Headline
GHSA-37jf-mjv6-xfqw: TensorFlow vulnerable to `CHECK` fail in `Conv2DBackpropInput`
Impact
When Conv2DBackpropInput receives empty out_backprop inputs (e.g. [3, 1, 0, 1]), the current CPU/GPU kernels CHECK fail (one with dnnl, the other with cudnn). This can be used to trigger a denial of service attack.
import tensorflow as tf
import numpy as np
input_sizes = [3, 1, 1, 2]
filter = np.ones([1, 3, 2, 3])
out_backprop = np.ones([3, 1, 0, 3])
strides = [1, 1, 2, 1]
padding = 'VALID'
tf.raw_ops.Conv2DBackpropInput(
input_sizes = input_sizes,
filter = filter,
out_backprop = out_backprop,
strides = strides,
padding = padding
)
Patches
We have patched the issue in GitHub commit 27a65a43cf763897fecfa5cdb5cc653fc5dd0346.
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 Jingyi Shi.
Impact
When Conv2DBackpropInput receives empty out_backprop inputs (e.g. [3, 1, 0, 1]), the current CPU/GPU kernels CHECK fail (one with dnnl, the other with cudnn). This can be used to trigger a denial of service attack.
import tensorflow as tf import numpy as np input_sizes = [3, 1, 1, 2] filter = np.ones([1, 3, 2, 3]) out_backprop = np.ones([3, 1, 0, 3]) strides = [1, 1, 2, 1] padding = ‘VALID’
tf.raw_ops.Conv2DBackpropInput( input_sizes = input_sizes, filter = filter, out_backprop = out_backprop, strides = strides, padding = padding )
Patches
We have patched the issue in GitHub commit 27a65a43cf763897fecfa5cdb5cc653fc5dd0346.
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 Jingyi Shi.
References
- GHSA-37jf-mjv6-xfqw
- tensorflow/tensorflow@27a65a4
- https://github.com/tensorflow/tensorflow/releases/tag/v2.10.0
Related news
TensorFlow is an open source platform for machine learning. When `Conv2DBackpropInput` receives empty `out_backprop` inputs (e.g. `[3, 1, 0, 1]`), the current CPU/GPU kernels `CHECK` fail (one with dnnl, the other with cudnn). This can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 27a65a43cf763897fecfa5cdb5cc653fc5dd0346. 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.