Researchers demonstrated a naming attack against AI assistants that can move from hallucinated lookups to remote code execution and, in some cases, malware delivery.
A newly named technique turns AI coding mistakes into a security boundary problem, showing how a hallucinated identifier can become a dangerous trust decision.
A reported technique called HalluSquatting shows how an LLM’s confidence can become an attacker’s entry point when agents are allowed to fetch or run what the model invents.