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In the short history of AI security, rapid injection has become a major threat. Bigger languages naturally cannot distinguish between legitimate instructions given by users and malicious ones that enter emails, code, and other third-party content that the brands are processing. This makes it easier to inject bad rules that LLMs follow easily.
Without a way to manage this critical boundary between trusted and untrusted sources, AI engine developers are left to implement preventative measures to mitigate damage rather than eliminate the cause.
Until now, the most rapid injection has fallen into the group known as pushing, in which every injured person looks at him. For example, an adversary inserts malicious instructions into an email or ordering calendar. Because the injection has to be sent (or pushed) to each target, the size of the threat is limited, preventing a large-scale action that affects the Internet.
