TensorFlow is an open source platform for machine learning. When TensorListScatter and TensorListScatterV2 receive an element_shape of a rank greater than one, they give a CHECK fail that can trigger a denial of service attack. We have patched the issue in GitHub commit bb03fdf4aae944ab2e4b35c7daa051068a8b7f61. 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.
The product contains an assert() or similar statement that can be triggered by an attacker, which leads to an application exit or other behavior that is more severe than necessary.
| Name | Vendor | Start Version | End Version |
|---|---|---|---|
| Tensorflow | * | 2.7.2 (excluding) | |
| Tensorflow | 2.8.0 (including) | 2.8.1 (excluding) | |
| Tensorflow | 2.9.0 (including) | 2.9.1 (excluding) | |
| Tensorflow | 2.10-rc0 (including) | 2.10-rc0 (including) | |
| Tensorflow | 2.10-rc1 (including) | 2.10-rc1 (including) | |
| Tensorflow | 2.10-rc2 (including) | 2.10-rc2 (including) | |
| Tensorflow | 2.10-rc3 (including) | 2.10-rc3 (including) |
While assertion is good for catching logic errors and reducing the chances of reaching more serious vulnerability conditions, it can still lead to a denial of service. For example, if a server handles multiple simultaneous connections, and an assert() occurs in one single connection that causes all other connections to be dropped, this is a reachable assertion that leads to a denial of service.