AI is not just a new technology —
it's a new attack surface.
As AI systems become decision-makers, security must evolve from data and systems to logic, learning, and behavior. We test the whole stack — foundation models, fine-tuned models, RAG pipelines, agentic systems, MLOps.
AI security is about three things.
Innovation
Enabling innovation without fear of exploitation.
Trust
Protecting trust between humans and machines.
Responsibility
Aligning security with compliance and accountability.
Four AI security packages. Scope the ones that match your stack.
Prompt · Jailbreak · Output
Prompt injection, jailbreaks, system-prompt leakage, sensitive-data disclosure, output-handling abuse.
Knowledge · Retrieval · Tenancy
Indirect injection, corpus traversal, vector-DB abuse, retrieval poisoning, cross-tenant leakage.
Tools · Autonomy · Workflows
Tool-invocation abuse, excessive agency, workflow manipulation, connector pivoting, approval bypass.
Training · Supply · Routing
Training-data poisoning, evaluation gaming, supply-chain review, model-routing manipulation, memorization probes.
7-phase AI red team lifecycle.
Adapted from classic kill-chain methodology, mapped to MITRE ATLAS TTPs and OWASP LLM Top 10 risks.
Four frameworks. Zero cherry-picking.
Our test coverage spans OWASP LLM Top 10, OWASP Agentic Top 10, MITRE ATLAS, and NIST AI RMF + Google SAIF — no gaps, no selective interpretation.
How we run an AI red team.
Foundation models, fine-tuned models, RAG pipelines, agentic systems, MLOps infrastructure.
MITRE ATLAS · OWASP LLM Top 10 · OWASP Agentic Top 10 · NIST AI RMF · Google SAIF.
Prod-safe and sandbox testing lanes. Data handling and model-state restoration protocols default-on.
Clear abort conditions, rollback protocols, evidence chain-of-custody.
What you walk away with.
Reproducible evidence
Every finding ships with PoC prompts, screenshots, and session logs your team can replay.
AI-adapted risk scoring
Data confidentiality, hallucination impact, tool-chain blast radius.
Executive heatmap
Prioritised remediation playbook, C-suite read in under 5 minutes.
60-day retest
Free retest on every remediated finding. No additional cost.
Every AI finding, reproducible.
AI findings need more than a screenshot of a chat. Ours include the full prompt chain, session log, and remediation at the platform layer — not just 'improve your system prompt'.
Indirect Prompt Injection → RAG Corpus Exfil → SSO Token Reuse
- Impact
- Attacker-controlled knowledge-base entry injects instructions that cause the assistant to leak cached SSO tokens from a previous user session.
- Evidence
- Reproducible prompt chain (7 turns), session log, screen recording showing token extraction and replay.
- Remediation
-
- Sanitize retrieved content before injection into the context window
- Scope per-user context isolation — no cross-session memory retention
- Rotate and invalidate session tokens on model context boundary
- Retest window
- 60 days, no additional cost.
Ship AI, confidently.
Tell us about your AI stack — foundation model, RAG pipeline, agentic system — and we'll propose a test plan within 2 business days.
Scope an AI red team