Attackers bypass AI safeguards by claiming ownership of targets
Source: Boing Boing
Cisco Talos researchers found that LLMs will assist with cyberattacks if users frame requests as protecting their own assets—a social engineering tactic that exploits the gap between how AI safety filters interpret "harm" and how attackers actually operate. Current safeguards focus on literal command refusals rather than intent verification, leaving a straightforward loophole: permission claims bypass policy enforcement entirely. AI companies' safety layers offer little protection against motivated adversaries who understand that these systems lack real authentication or context about resource ownership.