Privilege escalation
Sudo abuse, setuid discovery and capability escalation inside the VM.
“Your AI agent is running. Do you know what it’s doing?”
Benchmarks tell you what a model knows. Behavior reports tell you what itdoes when it is pushed, probed and tempted to break the rules, scored across six dimensions and cryptographically signed so you can audit every claim.
Illustrative report. Real reports are generated from your own run evidence.
Every run exercises the attack classes that actually matter: inside isolated microVMs, cryptographically signed, in EU AI Act Annex IV format.
Sudo abuse, setuid discovery and capability escalation inside the VM.
Harvesting or exfiltrating secrets, tokens and keys reachable from the sandbox.
Agents coordinating over the message board to bypass individual constraints.
Direct, indirect and multi-turn attempts to break safety policy.
Acting outside the mandate, with unintended side effects.
Each report measures the same six concrete dimensions so results remain comparable across models, vendors and versions.
External evaluations run against recognized, comparable benchmarks alongside our own task packs.
A dynamic environment for evaluating tool-using agents against prompt-injection attacks in realistic task suites.
A standardized framework for measuring harmful capabilities and the robustness of refusals across attack methods.
A benchmark for indirect prompt injection against tool-integrated agents across common real-world scenarios.
Every report and its underlying run manifest is signed and hash-chained, so the evidence is tamper-evident and independently verifiable.
Technical documentation generated from real run evidence: architecture, risk management and testing records, structured for Annex IV review.
A signed risk verdict for jailbreak and misuse behavior, suitable for external companies, procurement and deployment sign-off.
A two-page verdict for decision makers: overall posture, top risks, and whether the model is ready to deploy.
Quantified scores with confidence intervals for each behavior dimension, compared against baselines.
Every weakness is backed by a specific, reproducible trajectory with a run ID you can replay.
Compare two model versions side by side to see what a change actually improved or regressed.
Task packs, seeds, reward functions and scoring definitions, fully transparent and auditable.
Machine-readable scores and the underlying trajectories, so your own team can verify the conclusions.
Pre-release safety evidence and training feedback.
Independent red-team evidence for internal agents.
Vendor due diligence before adopting a model.
Comparable metrics for risk and governance.
Connect an agent endpoint and the platform returns a scored, evidence-backed report through the standard pipeline.