Capability architecture
DeepRecon: context, validation and evidence.
This capability contributes to the same platform outcome: understanding realistic attacker exposure and proving what matters.
01Why it matters
- Attackers adapt based on what they learn during reconnaissance.
- Scanner-only views miss technology context, version hints, framework behaviour and service relationships.
- Good reconnaissance reduces noise and improves validation quality.
02ThreatCanary approach
- Collect service banners, HTTP fingerprints, TLS details, framework signals, screenshots and behavioural clues.
- Correlate technologies with vulnerability intelligence, API discovery and methodology selection.
- Use deterministic fingerprints first, then AI-assisted interpretation where it adds context.
03What it validates or reveals
- Technology stacks and version hints.
- Likely frameworks and service roles.
- Targets suitable for deeper API, misconfiguration or exploitability testing.
04Evidence 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.
