Independent research desk / Authorized assessment
A research desk for AI-enabled offensive security and the adversarial testing of AI systems.
Use an agent’s task tree to organize an authorized assessment—not to certify its conclusions. What must survive the handoff to a human reviewer?
Use AI to draft coverage across endpoints, identities, and object ownership—then check the gaps in an isolated staging API.
Use AI to connect changed routes, identity checks, and data access—then turn the supported leads into tests a human can verify.
Let AI connect your approved inventories and observations into testable leads—not invent new assets or expand scope.
Separate harness quality, reachable coverage, reproducible crashes, and confirmed security impact before judging AI-assisted vulnerability discovery.
Evaluate legitimate completion, policy violations, and scorer disagreement separately when testing an AI application.
AI-assisted assessment should not ask the same model to propose an action and decide whether it is authorized.
A review assistant can help triage changed code. That does not make the pull request a safe source of instructions.
Task splits, guidance, budgets, and graders determine what an agent’s score actually means. Compare like with like before selecting a workflow.
Test authorization at the tool boundary using synthetic users and a mock downstream service.
Keep harness validity and reproducibility in the denominator of AI-assisted fuzzing.
Separate workflow development from evaluation when comparing offensive-security assistants.
Compare reviewer effort and unsupported findings, not the fluency of the final report.