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A single email can stealthily poison the memory of personal agents, leading to long-term manipulation of their behavior without detection.
Self-evolving LLMs can amplify adversarial threats, making every known attack lineage-persistent and exposing critical vulnerabilities that static defenses can't address.
Trustworthy memory search can significantly reduce vulnerabilities in personal AI agents without compromising their long-term memory utility.
MCP-based AI systems are alarmingly vulnerable to caller identity confusion, allowing unauthorized access to sensitive tools and operations after just one initial authorization.
Embodied AI's failures aren't just LLM or CPS problems; they arise from embodiment itself, where safe-seeming decisions cascade into real-world chaos.
