Forgotten staging host
Surfaced from a TLS certificate. Never present in inventory.
✓ evidence AI-NATIVE OFFENSIVE SECURITY
AI-Native Offensive
Security for the
Modern Attack Surface
ThreatCanary unifies EASM, API Security and AI Offensive Security to continuously discover, validate and prioritise exposures across your entire attack surface.
Deterministic evidenceScope-aware autonomyHuman approval controls
EXAMPLE OPERATIONILLUSTRATIVE · AUTHORISED SCOPE
SIMULATED OPERATIONExternal perimeter validation Example workflow
142example assets
27example hypotheses
EXAMPLE ATTACK PATH
ILLUSTRATIVE RESULTAuthentication boundary bypassExample deterministic replay · evidence capture
Attackers chain systems together.
Your tools don’t.
Your exposure, APIs, identities and cloud are connected. Attackers move across them fluidly; most security stacks see each in a silo and return findings without showing the path in.
One platform, one validation modelThree product pillars.
Three product pillars.
One attack-path validation platform.
Exposure intelligence, API behavioural intelligence and offensive validation share one graph, preserving context between systems and proving which paths are realistically exploitable.
01
AUTONOMOUS OFFENSIVE OPS
Explore ↗AI Offensive Security
Autonomous operations, adaptive testing, attack-path reasoning and evidence-backed exploitability.
02
EXPOSURE INTELLIGENCE
Explore ↗Exposure Intelligence
External attack-surface discovery, drift detection and exposure validation.
03
BEHAVIOURAL INTELLIGENCE
Explore ↗API Security
API discovery, behavioural intelligence, authorisation testing and sensitive-data exposure.
EASM finds the exposure. API security explains the behaviour. ThreatCanary proves the attack path — all of it correlated on ExposureGraph, one living model of your attack surface. Explore ExposureGraph.
Illustrative validation trace
See how ThreatCanary validates an attack chain.
This illustrative workflow shows how ThreatCanary moves from an exposed service to a scoped hypothesis, reproducible evidence and a validated path to impact.
Zombie API, no authentication
Deprecated two years ago. Still responding and still trusted internally.
✓ evidenceOver-scoped token
Reused across tenants and able to reach beyond its intended service.
✓ evidenceCustomer records
Read access safely proven with a reproducible capture.
✓ provenTrusted by
Customer and partner perspectives
Trusted by the teams who can't afford to guess
365mesh
Every scanner we'd run just handed us a longer backlog. ThreatCanary handed us a single proven path into the data that mattered — with the evidence to reproduce it. That's the first time security spend made sense to our board.
Farmdeck
We ship fast, and our APIs change every sprint. ThreatCanary keeps pace — it doesn't just point at an endpoint, it hands my developers the exact request that abuses it and the steps to fix it. It's the first security tool that fits the way we actually build.
Broadsecure
Most "AI security" is a language model making confident guesses. ThreatCanary is the opposite — the AI reasons like an attacker, but every finding is proven by deterministic testing we can reproduce. That separation is exactly why I trust it in production.
OutcomexPartner
Our clients don't need another scanner adding to the noise. We bring them ThreatCanary because it proves what's genuinely exploitable — the conversation moves from a list of maybes to an evidenced set of priorities. That's a value story we're glad to put our name to.
What the platform proves
Evidence-backed outcomes, not another finding list.
Examples of the outcomes ThreatCanary validates across exposure, APIs, identities and cloud. Explore the product map for the capabilities behind them.
Finds the API your team deprecated two years ago and proves whether it still provides an entry point.
Shadow & zombie API discoveryFinds the public bucket, the role that reaches it and proves the path between them.
Cloud exposure · attack-path reasoningTests whether one user can read another user’s data and captures the request that proves it.
BOLA / BFLA · business-logic abuseEvery validated finding comes with the evidence needed to reproduce and remediate it.
Deterministic validation · evidence pedigreeBuilds the exact test a target requires and validates it safely before controlled execution.
Controlled test generationA pentest is a snapshot. ThreatCanary keeps testing as the environment changes and proves when a path opens.
Continuous autonomous operationsCommon questions
Questions teams ask before they commit.
Direct answers on scope, evidence, safety controls and how ThreatCanary differs from tools you already run.
01What is ThreatCanary?
ThreatCanary is a continuous attack-path validation platform. It discovers exposed assets and APIs, connects them through graph intelligence, and validates which attack paths are realistically exploitable. It combines three layers — external attack surface management (EASM), API behavioural intelligence, and AI offensive security — so exposure is assessed the way an attacker would chain it rather than as isolated findings.
02How is ThreatCanary different from a vulnerability scanner?
A vulnerability scanner identifies known conditions, usually by matching a version, banner or signature against a predefined check. ThreatCanary goes a step further and validates whether the weakness is actually reachable and exploitable in your environment, and what it chains into. The output is evidence-backed findings with reproduction detail rather than a list of theoretical issues that still need triage.
03How is ThreatCanary different from EASM and API security tools?
Traditional EASM answers what exists on your perimeter, and API security tools answer what APIs exist and how they behave. ThreatCanary uses both as inputs and then asks the harder question: how those exposed systems and APIs can actually be used against you. Exposure, API behaviour, identity context and vulnerability data are correlated in one graph so findings carry attack-path context instead of sitting in separate tools.
04Is autonomous offensive testing safe to run against production?
ThreatCanary constrains autonomous testing with explicit scope definitions, approval gates, tool-trust settings and execution limits, so activity stays inside authorised boundaries. Scope management defines exactly what the platform is permitted to discover, test and validate. Deterministic systems produce the evidence and validation trail, which means results are auditable and reproducible rather than opaque model output.
05What does ThreatCanary actually deliver to a security team?
Customers get a living map of exposed assets, APIs and relationships as they change; validated findings backed by reproducible evidence rather than theoretical scanner output; attack-path context explaining what can be chained and why it matters; and role-specific outputs for CISOs, security teams, developers, GRC and platform owners.
06Where does AI fit in, and can the results be trusted?
ThreatCanary uses AI for reasoning, adaptation, hypothesis generation, reporting and advisory workflows — the parts that benefit from judgement. Deterministic systems handle discovery, validation, evidence capture and reproducibility. That split is deliberate: AI decides what is worth testing, while the evidence proving a finding is produced and reproducible by deterministic means.
See ThreatCanary in action
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