01.4
Adversary Emulation for AI
AI Red Team & Readiness
Test your AI against a real adversary, and your team’s response
We emulate a determined attacker across your AI pipeline, from people and cloud to models and agents, then test how your team detects and responds.
The Problem
Name the Worst Case. Test It.
Every exercise begins with objectives your executives care about. Here’s one: could someone outside your company steer an agent into fetching a protected record and pushing it out through an approved tool used the wrong way?
We then pursue those objectives like a determined adversary, from public recon and phishing the people who run your AI to moving through your cloud toward model files and data, stringing small weaknesses into a real attack path. Then we test how your team detects and responds.
Where a path can run:
- People who build and run your AI
- Identities and the access they carry
- Cloud accounts, CI/CD pipelines, and model files
- Sensitive data, including training and fine-tuning sets
- Retrieval sources that feed the model
- Models and their guardrails
- Agent tools and the actions they take
- Business processes that trust AI output
Readiness
Earn the Red Team First
A red team pays off only on solid fundamentals. We’ll recommend one only when your program meets all four of these conditions.
Mature System Ownership
Named owners for each AI system, data source, and integration involved.
Logging
Telemetry good enough to rebuild what the AI did, including its inputs, tools, and permissions.
Response Procedures
A defined way to detect, escalate, and contain an AI-related event.
Defined Objectives
Specific adversarial outcomes the exercise is built to test.
Not ready yet?
Start with the AI Threat & Exposure Assessment or AI Penetration Testing. Either one exposes the gaps in ownership, logging, and response worth closing before a red team.
How We Test
Realism With Guardrails
The exercise is built to expose risk, not cause it. Each one runs under documented controls built for that exercise alone, with a named contact on both sides and an activity log kept throughout.
Plan and Set Objectives
Set the goals, what success looks like, the threat to emulate, and which modules to run.
Rules of Engagement and Safety
Document entry points, targets and off-limits systems, the people and methods in scope for social engineering, prohibited actions, and stop conditions. Every production system gets rate, cost, data, and recovery safeguards.
Emulate the Attack
Move from recon and initial access toward each objective as a determined attacker would, across people, cloud, pipelines, models, and agents. In purple-team sessions, we work alongside your defenders to see what they catch.
Report and Debrief
Reproduce each path and map it as an attack graph, replay it step by step with your defenders, run the tabletop with your response team, and brief executives on what landed and what to fix first.
Mapped To
- MITRE ATT&CK
- MITRE ATLAS
- OWASP Top 10 for Agentic Applications
- OWASP Top 10 for LLM Applications
Every step of every path is tagged to the techniques it used, so your defenders can find it in their own tools.
Key Outcomes
See the Path. Break the Chain.
See Your AI as an Attacker Does
Learn how an adversary could string small gaps together to reach the assets and goals you care about most.
Validate Your Defenses
Find out what your team and tools would have spotted, and how fast they could have responded.
Sharpen Detection and Response
Tune what was missed during purple-team sessions, and rehearse the response in a tabletop before a real incident.
Prioritize the Chain-Breakers
Put remediation where it breaks the chain soonest, on the controls that would have halted the path in its first steps.
Deliverables
The Full Story, Documented
Attack Graphs and Narratives
Every path attempted and achieved, mapped step by step and tagged to MITRE ATT&CK and ATLAS, because you need the whole story of what was tried.
Technical Findings and Execution Logs
Screenshots, execution logs, and a record of every change we made to your systems, so your defenders can replay each path and confirm everything was cleaned up.
Detection and Response Findings
What your team saw, how it responded, and what the purple-team sessions and tabletop changed, because prevention is only half of defense.
Findings Walkthrough and Debrief
A walkthrough of which attempts succeeded and which fixes come first, plus a debrief that replays each path step by step with your defenders, because decision-makers need a decision and engineers need the detail.
Common Questions
AI Red Teaming Explained
What is AI red teaming?
An exercise where we act as a determined adversary pursuing goals you define, such as pulling a protected record out through an agent’s tool, along realistic paths through people, identity, cloud, data, models, tools, and business processes. It also tests how your team detects and responds.
How is AI red teaming different from a traditional red team?
The attack still runs through people, identities, and cloud, but the objectives and paths go through your AI: its models, training data, retrieval sources, agents, and the business processes that trust its output.
Should I choose a red team or an AI penetration test?
A pentest covers one defined system systematically and confirms what’s exploitable. A red team goes after specific objectives, chaining techniques as an adversary would, and checks whether your defenses notice and respond. We don’t label every AI test a red team.
What is purple teaming?
Our testers and your defenders work together during the exercise. We run an attack, your team checks what its tools saw, we tune detection together, and then we retest to confirm it works.
Do you include social engineering?
Only the people and methods named in the rules of engagement, such as a phishing test against the team that runs your AI pipeline. Nothing outside that list is touched, and physical intrusion isn’t part of the engagement.
How long does an engagement take?
Usually several weeks of active testing, plus planning beforehand and reporting after. The modules you choose and the number of objectives set the length, and your statement of work confirms it.
How often should we run one?
Many programs run one a year, and again after a major change such as a new agent platform or model provider. Between exercises, Continuous AI Penetration Testing retests the systems that change most.
Who is a red team right for?
Programs with mature system ownership, working logs, response procedures, and clear adversarial objectives. It’s never the default first engagement. Missing those basics? Start with the AI Threat & Exposure Assessment or AI Penetration Testing instead. And no red team can guarantee that an adversary would never reach your objective; it shows how one could, and what stops them.
How do you keep a red team from harming production?
Every exercise gets its own rules of engagement and an operational safety review, plus production safeguards for rate, cost, data, and stop conditions. We leave out any scenario that could cause avoidable operational harm.
Your Move
Test the Outcome You Fear Most
Name the scenario your executives worry about. We’ll check that you’re ready, then scope an exercise around it.