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SEC-10 // Service brief

AI Security & LLM Red Teaming

Know what your AI can reveal, obey, or misuse.

Threat modelling and adversarial testing for LLM applications, RAG pipelines, agents, tools, models, and data flows.

Scope this engagement All services

When to engage

Signals this service is the right next step.

  • You are deploying an LLM application, RAG pipeline, copilot, or agent.
  • The system can access private data, tools, or consequential actions.
  • You need adversarial evidence before production or customer assurance.

Scope

What we examine

  • Prompt injection and jailbreaks
  • RAG data leakage
  • Agent permission abuse
  • Model and dependency supply chain

Deliverables

What your team receives

  • AI threat model
  • Reproducible attack cases
  • Guardrail recommendations
  • Verification testing

Methods and references

Standards-aligned, scope-specific delivery.

Frameworks guide coverage and consistency. Engagement scope, legal authorization, business context, and evidence determine how they are applied. Technology references describe assessment coverage and do not imply vendor partnership.

OWASP Top 10 for LLM ApplicationsMITRE ATLASNIST AI RMFSecure AI Framework principles
01

Authorize

Confirm scope, owners, constraints, evidence handling, and rules of engagement.

02

Examine

Collect evidence and test the paths relevant to your systems and risk.

03

Prioritize

Translate technical findings into business decisions and fix priorities.

04

Verify

Support remediation and confirm that material issues are resolved.

Start with a confidential scoping conversation

Tell us what decision, incident, or assurance requirement is driving the work.

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