TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a denial of service by exploiting a CHECK-failure coming from tf.raw_ops.LoadAndRemapMatrix. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/d94227d43aa125ad8b54115c03cece54f6a1977b/tensorflow/core/kernels/ragged_tensor_to_tensor_op.cc#L219-L222) assumes that the ckpt_path is always a valid scalar. However, an attacker can send any other tensor as the first argument of LoadAndRemapMatrix. This would cause the rank CHECK in scalar<T>()() to trigger and terminate the process. 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.
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 | * | 2.1.4 (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) |
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.