AI Security for Copilot and Agents

For security and IT teams responsible for Copilot, agents, and AI applications.

We model the threats AI opens up, set data boundaries in Microsoft Purview, limit what each agent can do, and turn on detection. Copilot, agents, and AI apps then run with the controls your other systems already have.

How we help

Threat modeling and risk discovery comes first, and what it finds decides the AI data protection, detection, and testing each workload gets.

Threat modeling and risk discovery

Estimated 2–4 weeks

Your existing threat model extended to AI, with the scenarios that matter and a schedule for revisiting them.

What you get

  • Your threat model extended with MITRE ATLAS, the catalog of attacks on AI, and the OWASP list of top AI risks
  • Scenarios for prompt injection, data leakage, cost, and an agent allowed to do more than its job needs
  • AI data risk assessed with Purview Insider Risk Management
  • A schedule for revisiting the threat model as models and threats change

Best for

Your threat model predates AI, and nobody has asked how an agent could be turned against you.

AI data protection

AI that reaches only the data that is right for its audience, with risky prompts and exposure visible.

What you get

  • Data classified with Purview sensitivity labels
  • Purview data loss prevention across AI workflows
  • Purview Data Security Posture Management to see risky AI prompts and exposure
  • Models and datasets behind private endpoints and encryption

Best for

An agent or custom AI app is about to read data its users shouldn’t see.

See Data Security and Compliance

Protection, detection, and testing

The AI you are running found and locked down, threats raised as alerts, a playbook for when one lands, and testing in proportion to the risk.

What you get

  • AI resources found with Azure Resource Graph and Defender
  • Agents’ tool access limited by managed identities, network isolation, and API Management
  • Generative AI risks across Azure tracked in Defender for Cloud
  • AI incident categories and a tested way to disable an agent
  • Adversarial testing in proportion to risk
  • Post-incident review and recertification

Best for

AI resources appearing across subscriptions with no list, and no plan for the night an incident lands.

Not sure which fits? Request a meeting

Questions we get

What is prompt injection, and should we worry about it?

Prompt injection is text, in a message, document, or web page, that tries to make an AI system ignore its instructions or leak data. It matters most for agents that read outside content or take actions, so we test for it and put approvals and limits on what agents can do.

Does Microsoft Defender cover AI workloads?

Yes, through Defender for Cloud. AI security posture management, part of the Defender CSPM plan, finds AI workloads and risky configurations across Azure, AWS, and Google Cloud. Threat protection for AI services raises alerts on attacks such as jailbreaks and data leakage as they happen. We turn both on, tune them, and connect them to your incident process.

How do we stop sensitive data from leaking through AI answers?

Set data boundaries before the AI goes live. That means Purview classification and sensitivity labels, data loss prevention in AI workflows and Copilot Studio agents, permission-aware retrieval, and Purview Data Security Posture Management to spot risky AI interactions. For Microsoft 365 Copilot alone, the tenant check before rollout is the Copilot Readiness Assessment.

See the Copilot Readiness Assessment

Do you penetration-test AI systems?

We run adversarial testing proportional to the risk tier: prompt injection, jailbreaks, data exfiltration, and tool misuse. Formal red-team exercises and independent audit opinions are scoped separately when you need them.

How long does AI security take?

Threat modeling and risk discovery comes first, with its estimated length listed above. Controls then roll out by risk tier, highest-risk workloads first.

What drives the effort in AI security work?

How many AI workloads and agents are in scope, how many of them take actions, and what they can reach count most. The security tools you already run, and how much adversarial testing the risk tiers call for, decide the rest.

Talk to us about AI Security for Copilot and Agents

It starts with a 60-minute call. If we need more to scope it, a short questionnaire follows. Then a written proposal and statement of work. Once you approve, we begin with the Assess phase.