Isn't that someone else's problem anyway? Someone else's model trained on your outputs is still someone else's model.

we cannot monitor how these distilled models are used or prevent misuse

which is fine since they are none of your (their) business..

I think the only possible concern is using their models name - making it clear it's a new model merely trained in another one should fix that.