Lack of data validation In tensorflow-gpu
Description
TensorFlow vulnerable to CHECK fail in Conv2DBackpropInput
Impact
The implementation of Conv2DBackpropInput requires input_sizes to be 4-dimensional. Otherwise, it gives a CHECK failure which can be used to trigger a denial of service attack:
import tensorflow as tf strides = [1, 1, 1, 1] padding = "SAME" use_cudnn_on_gpu = True explicit_paddings = [] data_format = "NHWC" dilations = [1, 1, 1, 1]...
Patches
We have patched the issue in GitHub commit 50156d547b9a1da0144d7babe665cf690305b33c.
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
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Attribution
This vulnerability has been reported by Neophytos Christou, Secure Systems Labs, Brown University.
Mitigation
Update Impact
Minimal update. May introduce new vulnerabilities or breaking changes.
Ecosystem | Component | Affected version | Patched versions |
|---|---|---|---|
pypi | 2.7.2, 2.8.1, 2.9.1 | ||
pypi | 2.7.2, 2.8.1, 2.9.1 | ||
pypi | 2.7.2, 2.8.1, 2.9.1 |
Aliases
References