Kind of. You can’t do it 100% because in theory an attacker controlling input and seeing output could reflect though intermediate layers, but if you add more intermediate steps to processing a prompt you can significantly cut down on the injection potential.
For example, fine tuning a model to take unsanitized input and rewrite it into Esperanto without malicious instructions and then having another model translate back from Esperanto into English before feeding it into the actual model, and having a final pass that removes anything not appropriate.
Won’t this cause subtle but serious issue? Kinda like how pomegranate translates to “granada” in Spanish, but when you translate “granada” back to English it translates to grenade?
It will, but it will also cause less subtle issues to fragile prompt injection techniques.
(And one of the advantages of LLM translation is it’s more context aware so you aren’t necessarily going to end up with an Instacart order for a bunch of bananas and four grenades.)
Kind of. You can’t do it 100% because in theory an attacker controlling input and seeing output could reflect though intermediate layers, but if you add more intermediate steps to processing a prompt you can significantly cut down on the injection potential.
For example, fine tuning a model to take unsanitized input and rewrite it into Esperanto without malicious instructions and then having another model translate back from Esperanto into English before feeding it into the actual model, and having a final pass that removes anything not appropriate.
Won’t this cause subtle but serious issue? Kinda like how pomegranate translates to “granada” in Spanish, but when you translate “granada” back to English it translates to grenade?
It will, but it will also cause less subtle issues to fragile prompt injection techniques.
(And one of the advantages of LLM translation is it’s more context aware so you aren’t necessarily going to end up with an Instacart order for a bunch of bananas and four grenades.)