Agentic Security — when an AI system can act, a bad output becomes a real event.

An agent doesn't just answer — it acts

The failure mode of a manipulated chatbot is a bad sentence. The failure mode of a manipulated agent is a bad action.

Agentic AI systems are built to take initiative — querying data, calling APIs, sending communications, orchestrating other systems — with limited human review of each individual step. That's precisely what makes them useful, and precisely what makes a successful manipulation dangerous: the attacker doesn't need to extract information directly, they just need to convince the agent to act on their behalf.

Traditional application security assumes a human reviews consequential actions before they happen. Agentic systems are explicitly designed to reduce that review — that's the automation value. Testing an agent means testing whether it can be manipulated, through its inputs, its retrieved context, or the content it processes, into taking an action outside its intended scope: exfiltrating data through a tool call, escalating its own permissions, or chaining several small actions into a larger unintended outcome.

SIRI's agentic security testing maps every tool, plugin and action an agent can take, then tests whether it can be manipulated into using them outside intended scope — through direct instructions, indirect prompt injection via retrieved content, or multi-step chaining — and reports findings mapped to the OWASP LLM Top 10, alongside the same infrastructure testing SIRI Attack applies to everything else in your environment.