TensorFlow is an open source platform for machine learning. In affected versions several TensorFlow operations are missing validation for the shapes of the tensor arguments involved in the call. Depending on the API, this can result in undefined behavior and segfault or CHECK-fail related crashes but in some scenarios writes and reads from heap populated arrays are also possible. We have discovered these issues internally via tooling while working on improving/testing GPU op determinism. As such, we dont have reproducers and there will be multiple fixes for these issues. These fixes will be included in TensorFlow 2.7.0. We will also cherrypick these commits on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range.
The product does not validate or incorrectly validates the integrity check values or “checksums” of a message. This may prevent it from detecting if the data has been modified or corrupted in transmission.
| Name | Vendor | Start Version | End Version |
|---|---|---|---|
| Tensorflow | 2.4.0 (including) | 2.4.4 (excluding) | |
| Tensorflow | 2.5.0 (including) | 2.5.2 (excluding) | |
| Tensorflow | 2.6.0 (including) | 2.6.1 (excluding) | |
| Tensorflow | 2.7.0-rc0 (including) | 2.7.0-rc0 (including) | |
| Tensorflow | 2.7.0-rc1 (including) | 2.7.0-rc1 (including) |