AI Red Teaming
Deeper, adversarial campaigns for your highest-risk AI systems — the same judge-scored methodology behind AI Security Testing, run with more time and attack depth per target.
Security leaders, red teams, and product-security teams responsible for high-impact agents, tools, and workflows.
Scoped engagements for major releases, high-risk systems, material architecture changes, or targeted assurance needs.
A defined target, supported interface, authorized actions, meaningful success conditions, and explicit safety constraints.
Reviewed findings, full transcripts, judge reasoning, impact context, attack-path hypotheses, and remediation retest evidence.
What's included
Multi-turn adversarial sessions
Chains of prompts designed to compound smaller weaknesses into a real compromise, not single-shot attempts.
Separate judge scoring
Every transcript is scored against an explicit success condition by a model that isn't the one being tested — see our research on the methodology.
Cross-surface attack-path correlation
Relate relevant agent and web/API findings conservatively, labeling inferred relationships separately from end-to-end verified chains.
Admin-gated, fully audited
Opt-in for authorized live targets, with bounded execution, full event logging, and human review of deeper campaign results.
How it works
Scope the target
We agree on the specific high-value system and the actions that would constitute a real compromise.
Run under the Intensive profile
Deeper multi-turn campaigns execute against the live target with full logging.
Human review before ship
Our team reviews judge verdicts before anything is marked confirmed in your dashboard.
Correlate and report
Reviewed findings are delivered with transcript evidence and clearly labeled related web/AI context.
See Oxyne on your own systems.
Book a 30-minute walkthrough — we'll scope a real assessment for your AI and web surfaces.