AI Cyber Defense / Threat modeling and exposure reduction
AI Cyber Defense: Protect business attack paths with dependency maps
Give every third-party path a destination boundary, expiration condition and business owner. Require separate authorization for supplier access to management systems.
Environment and inputs: Enterprise attack-surface management, asset inventory and trust-boundary analysis; vendor-neutral.
Scenario and goal
Automated targeting can exploit a low-profile supplier connection that indirectly controls an important service.
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
Map supplier identities, inbound tunnels, delegated permissions and the business processes that depend on them. Capture who can revoke each access path.
Validate with an authorized exercise
Disable a test supplier identity and confirm that its sessions lose access within the documented window while unrelated supplier workflows continue.
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.