An autonomous AI agent system is software that can break a goal into steps, choose tools, and execute actions with limited direct human input. Unlike a single chat prompt, an agent may inspect files, call APIs, query databases, schedule jobs, or trigger workflows while deciding what to do next based on prior results.
In cyber security, this matters because autonomy increases both capability and risk. A compromised agent can leak data, misuse service credentials, or perform unauthorized actions at machine speed. Attackers may also steer an agent through prompt injection, poisoned documents, or manipulated tool outputs so the system follows hostile instructions. Defenders reduce risk by scoping tool permissions, isolating agents from sensitive systems, logging every action, requiring human approval for high-impact steps, and using least-privilege credentials with short lifetimes. Security testing should treat the agent, its prompts, its tools, and its data sources as part of one attack surface.