AI Red Team
Adversarial Testing for LLMs and AI Agents.
Prompt injection, jailbreaks, multi-turn attack simulation, tool-chaining abuse, PII exfiltration, and business logic exploitation.
Attack simulation
Multi-turn adversarial testing tailored to the agent’s actual capabilities, tool access, and business context.
Prompt and guardrail testing
Jailbreaks, system prompt extraction, context poisoning, output validation bypass, and policy evasion.
Evidence-led reporting
Each finding includes the path, impact, reproducibility, and practical remediation guidance.
AI security is different
This Is Not a Standard Penetration Test.
| Traditional Assessment | AI Security Assessment |
|---|---|
| Tests known vulnerability classes (CVEs, misconfigs) | Tests AI-specific attack surfaces (prompt injection, jailbreaks, context poisoning) |
| Static – tests a point in time | Dynamic – AI agent behaviour changes with context and model updates |
| Tool-driven scanning | Requires human adversarial reasoning plus AI-assisted tooling |
| Scope: infrastructure, applications, APIs | Scope: models, prompts, agent logic, tool access, output validation |
| Pass/fail against known signatures | Nuanced risk – same prompt can succeed or fail depending on framing |
| Covered by most pentest firms | Genuinely specialist – most firms have never tested an AI agent |