Platform

One platform for realistic attacker exposure

ThreatCanary unifies exposure intelligence, API behavioural intelligence, graph correlation and offensive validation so teams can understand how compromise could actually happen.

Evidence traceApproved scopeTarget-aware testing
What this covers

From discovery to evidence-backed attack-path validation.

The platform is built as one operating model: collect context, correlate relationships, reason over possible paths, then validate what is real.

01

Layer 1: Exposure Intelligence

  • Discovers domains, subdomains, services, cloud edges, certificates, technologies and externally visible APIs.
  • Monitors exposure drift so new assets, changed services and forgotten systems do not become silent risk.
  • Turns internet-facing data into offensive context rather than a static inventory.
02

Layer 2: API Behavioural Intelligence

  • Maps internal and external APIs, exposed documentation, shadow APIs, zombie endpoints and API ownership signals.
  • Analyses authentication, authorisation, sensitive data handling, business logic and runtime behaviour.
  • Treats APIs as trust boundaries and compromise pathways, not just endpoints.
03

Layer 3: Graph Intelligence

  • Connects assets, APIs, identities, services, vulnerabilities, data sensitivity, owners and trust boundaries.
  • Weights relationships so teams can see which combinations increase exploitability and business impact.
  • Gives AI agents grounded context instead of relying on prompt-only reasoning.
04

Layer 4: Offensive Validation

  • Generates attack hypotheses from exposure, API behaviour, vulnerability intelligence and graph relationships.
  • Runs controlled tests and deterministic validation before presenting risk as confirmed.
  • Continuously reassesses findings as the environment changes.
05

Operational principles

  • Every result is linked to observable evidence, not just model commentary.
  • AI can reason over context, but deterministic validation decides what becomes a finding.
  • Scope, safety controls and approval gates keep offensive workflows authorised and auditable.
Explore the platform

Move from platform architecture into the capability behind it.

Common questions

Questions teams ask before they commit.

Direct answers on scope, evidence, safety controls and how ThreatCanary differs from tools you already run.

01

What are the layers of the ThreatCanary platform?

The ThreatCanary platform has four layers working on shared context. Exposure Intelligence discovers what attackers can see from the outside. API Behavioural Intelligence models how APIs expose functionality, identity, data and trust. Graph Intelligence connects assets, APIs, identities, vulnerabilities, ownership and sensitive data into one model. Autonomous Offensive Operations generate hypotheses from that graph and validate exploitability under scope and safety controls.

02

Does ThreatCanary replace the security tools we already run?

ThreatCanary is designed to correlate rather than duplicate. It ingests context from cloud platforms, API gateways, repositories and SIEMs, and pushes validated findings back into issue tracking, chat, SIEM and webhook workflows. Teams typically keep existing vulnerability management for known-CVE hygiene and use ThreatCanary for the validation and attack-path layer those tools do not cover.

03

Why does attack-path context matter more than a findings list?

A weakness that looks minor in isolation can become critical when it connects to the right API, identity path or sensitive data flow. Attackers move through exposed services, APIs, identities, trust relationships, cloud edges and business logic — not through the categories security tools are organised into. Graph context is what lets ThreatCanary show which combinations of weaknesses form a realistic compromise path.

04

What evidence does a ThreatCanary finding include?

Each finding is designed to explain what was found, why it matters, how it was validated and who should act on it. Findings stay connected to the affected assets and APIs, identity context, data sensitivity, ownership and remediation workflow, so they can be reviewed, reproduced and routed to the responsible team without additional investigation.

See the operating model

Move from exposed assets to evidence-backed action.

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