The OWASP Top 10 for LLM Applications maps what goes wrong with AI systems. Three of them are the ones we run into again and again on real AI agents. Here’s what each one causes, and the best way to shut it down.
LLM01 · Prompt Injection
The issue. An agent can’t tell an instruction from text it merely read, so a poisoned email, document or web page can quietly tell it what to do — and it complies. It’s the root of almost every agent hijack. How to solve it. You can’t stop an agent being convinced, so fence untrusted content away from instructions and shrink what a convinced agent can actually do on its own.
LLM02 · Sensitive Information Disclosure
The issue. Agents leak — secrets, personal data, internal files — through their answers or a connector that sends data outward. Once an agent can reach the open web or send mail, there’s a door for data to leave. How to solve it. Least access to data, and an allowlist for where data is permitted to go.
LLM06 · Excessive Agency
The issue. Give an agent too much autonomy and too many capabilities, and a single bad input becomes a real action — a forwarded file, a deleted record, a payment. It’s why excessive agency sits so high on the OWASP list, and why so many enterprises are running into it: they’re wiring agents into real systems faster than they scope what those agents are allowed to do. How to solve it. Least privilege, and a human in the loop for anything consequential. Reduce what the agent can do, not only what you ask it to do.
They’re one chain, not three problems
These three aren’t separate. An agent gets convinced (injection), it acts (agency), and data leaves (disclosure) — one chain, start to finish. Cut any single link and the whole attack fails.
What we’re building at Vantisec
That chain is exactly what we scan for. Vantisec reads your AI agents and grades the three things that decide the outcome — what can convince them, what they can actually do, and where data can leave — then shows you where the gaps are before anyone else finds them. Most organisations can’t answer those questions today, because no one has looked. That’s the gap we close.
See where your agents stand.
Get a clear read on injection exposure, agent reach and data egress across your AI agents — and where to close the gap.
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