Data injection attacks enable unauthorized actions in autonomous AI agent workflows

Attackers can embed malicious data in sources that AI agents consume—such as product reviews or code comments—to manipulate agents into performing unintended actions while maintaining the illusion of legitimate task execution. These attacks corrupt the factual inputs agents rely on, allowing threat actors to achieve unauthorized clicks, unintended purchases, or arbitrary command execution without directly compromising the agent's control flow.