TensorFlow is an end-to-end open source platform for machine learning. In eager mode (default in TF 2.0 and later), session operations are invalid. However, users could still call the raw ops associated with them and trigger a null pointer dereference. The implementation(https://github.com/tensorflow/tensorflow/blob/eebb96c2830d48597d055d247c0e9aebaea94cd5/tensorflow/core/kernels/session_ops.cc#L104) dereferences the session state pointer without checking if it is valid. Thus, in eager mode, ctx->session_state() is nullptr and the call of the member function is undefined behavior. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.
A NULL pointer dereference occurs when the application dereferences a pointer that it expects to be valid, but is NULL, typically causing a crash or exit.
| Name | Vendor | Start Version | End Version |
|---|---|---|---|
| Tensorflow | * | 2.1.4 (excluding) | |
| Tensorflow | 2.2.0 (including) | 2.2.3 (excluding) | |
| Tensorflow | 2.3.0 (including) | 2.3.3 (excluding) | |
| Tensorflow | 2.4.0 (including) | 2.4.2 (excluding) |