THE PLATFORM
AI-driven, purpose-built cyber intelligence.
SIEGE is not another LLM wrapper. It is an adaptive platform developed over three years through DARPA CASTLE, with safe digital-twin validation before authorized execution.
- Customer-Governed Cyber Control Plane: Customer-defined approval points and a dated audit trail.
- Safe Digital-Twin Validation: Attack paths are proven in simulation before authorized emulation or live execution.
- Adaptive Adversary Behavior: Autonomous intelligence that adapts to your environment instead of replaying known scripts.
- Commodity CPU Economics: Purpose-built agents run on CPUs, not GPUs, with no continuous LLM inference cost.
01
HOW IT WORKS
Safe digital-twin validation.
Built on a modular, containerized architecture, SIEGE validates attack paths in a digital twin before interacting with live assets. Governed by your Cyber Control Plane, it can run continuously across scoped on-premises, cloud, or hybrid environments. Every action is mapped to MITRE ATT&CK and ranked by true exploitability.
FIG.01: ADVERSARY ATTACK PATH / SIMULATEDAGENT ACTIVE
You can't defend an attack path you've never seen. SIEGE finds it first.
agent-07▸enumerating external attack surface, 1,284 hosts mapped
agent-03▸valid credential reuse detected → foothold established
agent-07▸lateral path opened via remote services (T1021.002)
02
CAPABILITIES
What SIEGE does.
01
Adaptive Environment-Specific Adversary Behavior
SIEGE's reinforcement-learning agents do not replay static scripts. They analyze your specific topology, adapt to your defenses in real time, and dynamically chain offensive techniques to uncover novel attack paths unique to your environment.
02
Safe Digital-Twin Validation
SIEGE builds a lightweight digital twin and validates attack paths safely in simulation first. It pivots to emulation or live execution only when authorized.
03
Customer-Governed Cyber Control Plane
You define the scope, escalation thresholds, allowed toolsets, and human approval gates that govern agent activity. SIEGE records a dated audit trail for regulatory, board, and executive review.
04
Commodity CPU Economics
Because intelligence resides in specialized neural networks rather than general-purpose LLMs, SIEGE runs on commodity CPUs, not GPUs, with no continuous LLM inference cost.
