When Information Becomes the Attack Surface – Understanding AI Agent Traps

AI agents that can autonomously access websites, emails, and files are vulnerable to 'traps' - maliciously designed information that tricks them into wrong actions. These traps include content injection (hiding malicious instructions in webpage code or metadata), semantic manipulation (using repetition and emotional language to guide decisions), and cognitive state attacks (poisoning databases that agents rely on for memory), with research showing such attacks succeed 57-90% of the time depending on the type.