Knowledge
Base

Where AI is applied across triage, remediation guidance, reporting and researcher support — and where human judgement is required.

How the AXUMIS AI pentesting engine and its AXGNT orchestration layer work, and what changes when it runs inside your own perimeter.

Policy templates, disclosure timelines, CVE handling, advisory publishing and researcher recognition.

How uploaded evidence is stored, encrypted, scanned and quarantined — and how access to it is controlled.

Wallets, budget allocation, metering, overage handling, invoicing and the incentive engine that keeps security spend predictable.

How participants authenticate, how expert access is gated, how permissions are scoped, and what is audited.

Researcher onboarding tiers, payout channels, thresholds, cycles, currency conversion and what the researcher sees before being paid.

How the AXUM SEC platform is put together — two testing engines, one control plane, and where each capability lives.

How an expert-led engagement runs end to end — scope, staffing, testing, retest, certification and billing.

How a validated finding is tracked to a verified fix, including retest loops, ticket sync and delta reporting.

Collecting tax forms, applying treaty benefits, calculating withholding and meeting annual reporting obligations.

The states a submission moves through, how overlap is resolved, and how the SLA policy engine keeps response commitments visible.

How semantic duplicate detection works, what it compares, and how it changes reward economics.

The nine program models available on AXUM SEC, what each one is for, and how to choose between them.

How targets, severity tiers and testing boundaries are modelled and enforced on AXUM SEC.

How findings reach Jira, GitHub, GitLab, Azure DevOps, Slack and Microsoft Teams, what syncs, and what stays in the platform.