An interactive demonstration of how an AI-assisted attacker could move from reconnaissance to data theft inside a business network, and where ordinary controls interrupt the path.
This is a depiction. It does not scan, test, access, or collect information from your device or network. All systems, addresses, commands, organizations, and events shown are fictional. Addresses use ranges reserved for documentation.
Scenario
Northstar Precision Components
A fictional 140-employee manufacturer with two facilities, a cloud email environment, an ERP platform, remote vendor support, engineering workstations, and several operational systems. Any resemblance to a real company is coincidental.
Defensive controls
Turn controls on, then run the attack again to see where it stalls.
Network map
Tool in useStandby
UnknownDiscoveredAccessedCompromised
Data exfiltration0.0 GB leaving the networkAttack stopped
The simulated activity feed will appear here once the simulation starts.
Stage 0 / 9
Projected detection point
Stage 9 · after the fact
Timeline
Simulated 08:00 to 10:30 window.
What management should see
After each stage, a plain-language explanation appears here.
At which stage would your organization have detected this activity?
AI does not remove the traditional attack path. It makes reconnaissance, social engineering, analysis, and adaptation faster. The management question is whether the organization has enough visibility, control, and evidence to recognize and interrupt an attack before material damage occurs.
01Understanding external exposure
02Reviewing network and operational boundaries
03Evaluating AI, cybersecurity, and incident-response governance