AI agents pose unique security risks; three real-world breaches show what can go wrong

AI agents differ fundamentally from traditional software because they operate autonomously—once given a goal, they assemble and execute their own steps without waiting for human approval, and they adjust their behavior based on past interactions and external data. This autonomy introduces three categories of risk. First, their outputs are non-deterministic: the same instruction produces different actions each time, so testing cannot guarantee safe production behavior. Second, errors cascade: a single wrong decision propagates through subsequent autonomous actions before anyone can intervene. Third, their adaptability can be weaponized: attackers can gradually adjust inputs to steer the agent toward harmful outputs.

The three concrete incidents—EchoLeak, Instagram account takeover, and Supabase token leakage—all exploit the gap between what developers intended and what an autonomous system does when given ambiguous or malicious input. In each case, traditional security controls (firewall rules, authentication checks) failed because the agent held legitimate permissions and the harmful action looked like a valid task from the agent's perspective. This is why the article emphasizes that agency itself is the vulnerability: power concentrated in an autonomous system magnifies the impact of any mistake or exploit.