Tensorflow is an Open Source Machine Learning Framework. The GraphDef
format in TensorFlow does not allow self recursive functions. The runtime assumes that this invariant is satisfied. However, a GraphDef
containing a fragment such as the following can be consumed when loading a SavedModel
. This would result in a stack overflow during execution as resolving each NodeDef
means resolving the function itself and its nodes. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
The product does not properly control the allocation and maintenance of a limited resource.
Name | Vendor | Start Version | End Version |
---|---|---|---|
Tensorflow | * | 2.5.2 (including) | |
Tensorflow | 2.6.0 (including) | 2.6.2 (including) | |
Tensorflow | 2.7.0 (including) | 2.7.0 (including) |
Mitigation of resource exhaustion attacks requires that the target system either:
The first of these solutions is an issue in itself though, since it may allow attackers to prevent the use of the system by a particular valid user. If the attacker impersonates the valid user, they may be able to prevent the user from accessing the server in question.
The second solution is simply difficult to effectively institute – and even when properly done, it does not provide a full solution. It simply makes the attack require more resources on the part of the attacker.