AI Agent Security Assessment

It evaluates an autonomous AI agent — one that calls tools and takes actions toward a goal — for security weaknesses: excessive agency, insecure tool calling, indirect prompt injection through what it reads, workflow hijacking, and missing human gates on high-impact actions. It follows the OWASP Top 10 for LLM Applications and the OWASP AI Testing Guide, with each finding proven and rated.

A chatbot answers; an agent acts. The extra risk in an agent is agency — it can call tools, run multi-step workflows, and take real actions, so the impact of steering it is far higher. An agent assessment focuses on that: the tools, their permissions, the human gates, and how far a compromised step reaches.

It is when an agent can do more than its task requires — call tools it does not need, reach systems outside its job, or take irreversible actions without a check. It is the headline risk for agents in the OWASP Top 10 for LLM Applications, because it sets the size of the damage when an agent is steered off-task.

Usually through what it reads. An agent acts on observations — a tool's output, a fetched web page, a retrieved document — and an injected instruction hidden in that content can redirect its plan. Because the agent trusts its own data path, a poisoned observation can turn its reasoning against you without any direct message from the attacker.

We test each tool from the agent's side: whether it validates parameters, checks authorization independently, and is scoped to least privilege. A deep assessment of the backend systems behind those tools is a separate scope we can add; the agent-to-tool boundary is part of this service.

This is exactly why scoping matters. We prefer a staging environment where the agent's tools point at test systems, so an action taken during a test is harmless. When we must test against production we agree the limits in advance, avoid irreversible actions, and keep a contact on your side to pause at once.

Each finding gets a CVSS score for a common baseline, adjusted by the real blast radius — what a steered agent can read, change, or trigger, and whether a high-impact action lacks a human gate — and is mapped to the OWASP Top 10 for LLM Applications. An agent that can only draft text is a different risk from one that can move money.

Duration depends on the agent's complexity — the number of tools, the depth of its workflows, and whether multiple agents interact. A typical assessment runs about two to four weeks, and we give a firm estimate after scoping. Re-testing after you remediate is included.