THE QUESTION, ANSWERED

WHAT IS AGENTIC AI SECURITY?

Agentic AI security is protecting systems where an AI takes actions on its own rather than only producing text. The risk changes because the AI now has permissions, tools and reach into other systems. A chatbot that gets something wrong says something wrong. An agent that gets something wrong sends the payment, deletes the file or changes the record. So the control that matters is over the actions it takes, because the permission that makes an agent useful is the same permission that makes a compromised one dangerous.

How it differs from securing a chatbot

Securing a large language model was mostly about what goes in and what comes out: prompt injection, leaked data, harmful text. Those risks are still there. An agent adds three things on top of them. It holds credentials, it calls tools, and it takes many steps toward a goal without a person reading each one. A bad input no longer ends in a bad answer. It ends in an action, sometimes ten steps later, in a system nobody was watching.

The risks, by name

The OWASP GenAI Security Project published the first shared list in December 2025, the OWASP Top 10 for Agentic Applications for 2026:

Agent Goal Hijack (ASI01). Content the agent reads, an email or a document, steers it toward someone else’s goal.
Tool Misuse and Exploitation (ASI02). The agent misuses tools it is allowed to use.
Identity and Privilege Abuse (ASI03). An agent’s credentials, or the ones it was delegated, do something nobody authorized.
Agentic Supply Chain Vulnerabilities (ASI04). A tool, plugin, prompt or model it loads is compromised.
Unexpected Code Execution (ASI05). Code the agent writes or triggers runs without a check.
Memory and Context Poisoning (ASI06). Something planted in its memory keeps shaping what it does later.
Insecure Inter-Agent Communication (ASI07). Messages between agents are forged or altered.
Cascading Failures (ASI08). One bad step spreads through every connected system.
Human-Agent Trust Exploitation (ASI09). People approve what a confident agent tells them without checking.
Rogue Agents (ASI10). An agent works outside what it was meant to do.

Read down the list and most of the ten end the same way: an action runs that should not have. OWASP’s own advice starts with what it calls Least-Agency, giving an agent no more autonomy than the job needs.

What agentic AI security covers

Inventory. Know which agents exist, what models drive them and what each one can reach.
Identity and least agency. Each agent gets its own credentials and the smallest set of tools and permissions for its task. Identity vendors do this well.
Isolation. Code the agent runs stays in a sandbox with outbound access denied by default.
A check on every action before it runs. The agent decides; the action waits until it has been checked against the rules, then it is allowed, held for a person, or blocked. Every action, not only the first, because an agent that is blocked tries another route.
Rules the risk owners can write. In plain English, so changing one does not need an engineer.
A record. Who, what, when and why for every decision, kept for the auditor.

The first three decide what an agent can reach. Only the check decides whether a specific action, right now, runs. That is where several of the OWASP ten are stopped in practice: a hijacked goal, a misused tool and a rogue agent all have to act to do harm.

What it looks like when it works

Optimo AI runs a vendor-review agent that drafts, summarizes and recommends on its own and stops for a person only where the rules say: writing to a system of record, committing the business, reaching outside. When it was told to remove old evidence, the deletion did not run, the retry through a second tool did not run, and the reviewer saw both in the record. The Optimo AI proof of concept, signed off by its CEO. Every published run, misses included, is at the proof page.

Common questions

What is agentic AI security?

Agentic AI security is protecting systems where an AI takes actions on its own rather than only producing text. The risk changes because the AI now has permissions, tools and reach into other systems. The control that matters is over the actions it takes, since the same permission that makes an agent useful is what makes a compromised agent dangerous.

Is agentic AI security different from AI security?

It is the part of AI security that deals with AI that acts. AI security as a whole also covers models, training data and chat interfaces. Agentic AI security adds the questions that only matter once an AI holds credentials and calls tools: what it is allowed to do, what it actually does, and who finds out.

Does this require a human to approve every action?

No. It runs on its own, and a person steps in only where your rules say. HOLD is an option you switch on for the actions you choose, not a requirement. You decide where a person steps in, and everything else is checked and allowed to proceed without waiting on anyone.

Which AI models does this work with?

It works with any AI you already use. It sits at the execution layer, so it does not depend on which model produced the decision, or on that model's provider, version or hosting.

The product, if you want it

Mountain Theory is the check described above, shipped. It works with any AI you already use, in your environment or the cloud.

Book a demo and bring the agent you would least like to explain to your board.