YOU DO NOT COPY PROFESSIONALISM. YOU ALIGN WITH IT.
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AGENTIC RED TEAM

Agentic red teaming is adversarial testing carried out by human operators against AI agents running in production. Not the model in isolation. The agent, with its tools, its permissions, its memory and its connections, in the environment where it actually runs. You do not receive a rating. You receive a working attack chain, reproduced step by step, and the control that closes it.

A POLICY SAYS WHAT YOUR AGENT SHOULD DO. WE ESTABLISH WHAT IT WILL DO.

DEFINITION

WHAT WE TEST

We test against the OWASP Top 10 for Agentic Applications, published 9 December 2025, and the OWASP Top 10 for LLM Applications. We did not write either list, which is exactly why we use them. A standard controlled by no vendor is a standard you can hold us to.

Agent Goal Hijack

The agent is redirected by content it reads, not by a message anyone sent it

Tool Misuse and Exploitation

Permissions are granted one tool at a time. Attacks arrive one chain at a time

Identity and Privilege Abuse

Shared keys, borrowed identities, actions nobody can attribute afterwards

Agentic Supply Chain

The integration, the token and the third party your agent trusts by default

Unexpected Code Execution

What the agent runs when the input was never meant to be code

Memory and Context Poisoning

A false memory planted once, acted on for weeks

Insecure Inter-Agent Communication

What one agent will believe because another agent said it

Cascading Failures

One wrong decision, propagated at machine speed through every agent downstream

Human-Agent Trust Exploitation

Your people trust the agent. That trust is an attack surface

Rogue Agents

The agents nobody registered, nobody owns, and nobody is watching

HOW THIS DIFFERS FROM AUTOMATION

Automated payload libraries give breadth. They fire a large number of known inputs at an interface and report which ones produced an unusual response. That is useful, and we use it for coverage.

What automation cannot do is decide what to try next based on how the agent responded. A real chain is multi-turn. The operator reads the refusal, infers the boundary, reframes the request, chains a permitted tool to a privileged one, and arrives somewhere nobody modelled. That decision, made repeatedly under judgement, is the product.

WHAT YOU RECEIVE

  • Proven exploitability. A working attack chain, reproduced step by step against your agents. Not a probability. Not a maturity rating.
  • A named operator. The person who ran the test sits in front of your audit committee and walks them through what happened, in language a director can follow.
  • A remediation path. The specific control that closes each chain, ordered by what it costs you to implement.
  • A retest. A finding you have not re-tested is a finding you have not closed.
  • Evidence you can use. Mapped to King V accountability and formatted for the testing calendar Joint Standard 2 expects.

WHAT THIS IS NOT

A SCAN. A QUESTIONNAIRE. A POLICY REVIEW. A MATURITY ASSESSMENT.

SCOPE AND AUTHORISATION

Nothing begins without a signed scope. We require written authorisation naming the systems in scope, an agreed testing window, and a named contact on your side with authority to stop the engagement.

We test what is in scope and nothing else. Where an agent connects to a third party, we do not touch that third party without their own written authorisation. Where a demonstration would create a live risk to customers or to production data, we build a mirror instead and say so in the report.

WHAT WE NEED BEFORE WE START

A named agent estate, or the AI Exposure Review that produces one. Access appropriate to the test type. A window. A contact.

Most clients start with the Exposure Review, because most organisations cannot yet list every agent running inside them.

FREQUENTLY ASKED QUESTIONS

FAQ

Adversarial testing carried out by human operators against AI agents running in production, rather than against the model in isolation. The objective is a working attack chain: a sequence an attacker could actually execute, demonstrated end to end, not a score or a list of theoretical risks.

A penetration test targets infrastructure and applications. An agentic red team targets the reasoning, the permissions and the tool access of an autonomous system. The agent is not exploited through a flaw in the code. It is persuaded through the content it reads.

No. A policy describes what the agent should do. A red team establishes what it will do when somebody tries. Both are needed. Only one of them produces evidence.

The scope decides. Destructive actions are excluded by default and only ever included by explicit written agreement, in an agreed window, with a named person able to stop us. Where a chain cannot be demonstrated safely in production, we demonstrate it in a mirror and document the difference.

Then this is the cheapest moment in the entire lifecycle to get the identity model, the tool permissions and the logging right. Testing a design costs less than testing an estate.

Read the OWASP mapping

TAKE ACTION

TEST IT BEFORE SOMEBODY ELSE DOES

Thirty minutes on your agent estate and what this risk looks like in your environment.