Why it matters
- Annual pentests cannot keep pace with continuous change.
- Autonomous execution without context produces noise.
- Continuous operations need governance, evidence and prioritisation.
Autonomous Offensive Operations
Run continuous offensive workflows that reassess exposure, generate hypotheses and validate realistic paths as environments change.
Deterministic evidenceScope-aware executionAdaptive capability
Capability architecture
Autonomous Offensive Operations: context, validation and evidence.
This capability contributes to the same platform outcome: understanding realistic attacker exposure and proving what matters.
ThreatCanary approach
- Operate over current graph context and approved scope.
- Trigger workflows from new exposure, API changes, vulnerability intelligence or analyst input.
- Record methodology, tests, decisions, evidence and outcomes for review.
What it validates or reveals
- Continuous validation coverage.
- Emerging attack paths.
- Findings that evolve as the environment changes.
Evidence and outputs
- A clear explanation of the exposure, affected assets and likely attack path.
- Reproducible evidence suitable for analysts, developers and risk owners.
- Prioritisation based on exploitability, business impact, sensitive data and chainability.
- Owner, remediation and workflow context that can move into Jira, Slack, SIEM or reporting.
See ThreatCanary in action
Book a technical demo