AI Cyber Defense / Threat modeling and exposure reduction
AI Cyber Defense: Use canary assets without exposing real secrets
Place a harmless decoy inside a controlled segment with no route to sensitive systems. Define who investigates contact and how ordinary inventory scans are excluded.
Environment and inputs: Enterprise attack-surface management, asset inventory and trust-boundary analysis; vendor-neutral.
Scenario and goal
A decoy can produce a useful signal when automated discovery touches a resource that normal work never needs.
Why it matters
For this scenario, plan for a shorter interval between an observable exposure and an attempt to use it. Improving the response queue is useful only if the team can also change the reachable access path. Work from the resource an adversary could reach and the authority that resource confers; a product label or vulnerability total does not describe that consequence.
Evidence to collect
Collect access to a dedicated synthetic share or service, source identity and the sensor health status. Avoid embedding production credentials in any lure.
Validate with an authorized exercise
Access the decoy with an approved test account; confirm a case appears with an asset owner, then repeat an approved inventory scan and verify its documented handling.
Rollout and checks
Review the asset owner, effective reachability and business dependency before changing exposure. Preserve a dated inventory snapshot and compare the effective state after the change. If a required dependency fails, use the approved rollback while keeping a narrower temporary boundary wherever feasible. An unverified asset or path remains an investigation item rather than evidence of safety.
Scope and limits
This guide proposes a defensive test; it is not a tested production design. Check platform support and local requirements. References explain the mechanisms but do not certify the design. Behavior alone does not prove AI involvement.