Eyal Lenga

The paper demonstrates that current defenses against malicious fine-tuning of foundation models are insufficient because they only address fixed attacks, and introduces a unified adaptive attack that breaks these defenses.

The paper addresses the 'agent attribution' problem—the inability to trace harmful or misbehaving AI agents back to their deploying account—by proposing a robust, canary-based protocol for vendors to identify the responsible user.