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Services · AI RED TEAM EXERCISE

AI Incident Emulation

A targeted red team exercise against your live, customer-facing AI assistants and bots. We emulate the multi-turn manipulation a real attacker would use and measure what your production system actually does, only with written authorization and agreed safety limits.

USD 6,000 USD · per exercise

Technical scope

What we test.

For fintech, healthcare and e-commerce teams running AI assistants that talk to customers, access account data or trigger actions.

Attack scenarios

Multi-turn conversations designed to reach a defined harmful outcome:

  • Direct and indirect prompt injection
  • System prompt and policy extraction
  • Sensitive data disclosure across users
  • Unauthorized actions through connected tools
  • Guardrail and content-filter bypass

Safety limits

Agreed and signed before the exercise starts:

  • Written authorization from the system owner
  • Dedicated test accounts and data
  • Rate limits and testing windows
  • Stop conditions and a live escalation contact
  • No actions against real customer accounts

How it differs from Adversary

A focused exercise, not a full red team:

  • Scope limited to AI assistants and their tools
  • Fixed price per exercise
  • Adversary covers full attack chains across apps, identity and infrastructure

Methodology

Autonomous reconnaissance. Human exploitation. Human validation.

AI-assisted reconnaissance maps the attack surface. Security engineers build the attack paths, exploit them and validate every finding before it reaches your report.

See our methodology

Deliverables

  • Conversation transcripts as evidence
  • Success rate per attack scenario
  • Mapping to OWASP Top 10 for LLM Applications and MITRE ATLAS
  • Detection and response gaps
  • Prioritized guardrail and tool-permission fixes
  • Retest of fixed scenarios

No test starts without a contract, a defined scope and written authorization. Customer data, code, configurations and credentials are not submitted to public third-party commercial LLM services as part of the assessment workflow.

Scope your AI Incident Emulation engagement.

Tell us about the system, its architecture and your deadline. We reply with a proposed scope and a fixed price, usually within one business day.