FS-RE META-MODEL v2.0

The ARKONA Ecosystem

A 48-service, 19-agent platform for cyber-physical reverse engineering — built on 30+ industry frameworks, running on dual Tesla P40 GPUs.

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Lines of Code
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Services
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AI Agents
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Web Apps
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REST APIs
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MCP Servers
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LLM Models
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Source Files
Architecture

ARKONA is built on the FS-RE Meta-Model v2.0 — a full-stack reverse engineering framework with three axes: 8 vertical layers (L0-L7), 8 analytical viewpoints, and 6 process phases. Every tool maps to a specific layer in the stack.

L7 User Interface — COMET, FORGE, ARKONA HUD L6 Data — VAULT, Wiki.js, Evidence Chain L5 Enterprise — Boundary Mapper, API Analyzer L4 Supervision — Binary RE, Vuln Analyzer L3 Comms — Protocol RE, Network Mapper L2 Firmware — SEF Emulation Foundry L1 Hardware — KiCad Agent, Spec Sheets L0 Physical — Process Profiler INTELLIGENCE Strategic Operational Tactical Technical PLATFORM MuXD Router Ollama (5 models) Risk Engine Agent Comm Auth Service 2x Tesla P40 47GB VRAM 440GB RAM ARKONA FS-RE META-MODEL v2.0 — 8 LAYERS x 8 VIEWPOINTS x 6 PHASES
FS-RE Layers

Each layer in the stack maps to a specific domain of reverse engineering — from the physics of industrial processes up through firmware, protocols, and user interfaces. Analysis is bottom-up: every finding at a lower layer informs the layers above it.

L0Physical Process
The actual physics the OT system controls — process dynamics, SIL levels, P&ID elements, environmental conditions, and safety constraints. Where cyber meets physical.
Process ProfilerP&ID AnalysisIEC 61508
L1Sensing & Actuation
Hardware reverse engineering — PCB analysis, component identification, signal tracing, schematic extraction. AI vision identifies components from board photos and generates KiCad schematics.
KiCad AgentHardware RESpec Sheet Agent7 MCP Tools
L2Control Logic
Firmware extraction, emulation, and analysis. The System Emulation Foundry (SEF) supports three modes: Autopilot (AI-driven), Copilot (AI-assisted), and Manual. Ghidra headless bridge for binary analysis.
SEFGhidraQEMUbinwalk
L3Communication
Industrial protocol analysis — 8 ICS protocol signatures, Modbus deep inspection, PCAP topology discovery with Purdue model classification, OT asset inventory with Graphviz export.
Protocol RENetwork Mapper8 Protocols
L4Supervision & Operations
Application-level binary analysis — ELF/PE analysis, CWE vulnerability patterns, CVSS v4.0 scoring. 47 automated tests for vulnerability detection.
Binary RE47 TestsCVSS v4.0CWE
L5Enterprise
IT/OT boundary discovery, DMZ topology mapping, trust zone classification per IEC 62443, REST/ICS endpoint discovery, and attack surface enumeration.
Boundary MapperAPI Analyzer8 MCP ToolsIEC 62443
L6Data & Evidence
Digital evidence vault with chain of custody, SHA-256 hashing, AI summarization. Auto-generates Wiki.js articles from ingested artifacts. NIST SP 800-86 compliant.
VAULTWiki.jsEvidence ChainNIST 800-86
L7User Interface
The human-facing layer. COMET provides AI governance with 5-level delegation classification across 816+ task definitions. FORGE orchestrates 7 AI agents for autonomous software development.
COMETFORGEARKONA HUD5 Delegation Levels
Operational Domains

The ecosystem is organized into six operational domains, each with its own services, APIs, and web applications. CoreOps is the primary domain containing the full FS-RE reverse engineering stack.

30+ Source Frameworks

The meta-model synthesizes established frameworks from systems engineering, OT security, architecture, threat intelligence, risk quantification, and forensics into a unified ontology.

NIST SP 800-82
IEC 62443
MITRE ATT&CK ICS
ISO/IEC 15288
Purdue Model
FAIR v3.0
CVSS v4.0
Diamond Model
STIX 2.1 / TAXII
Kill Chain
IEC 61508
NIST SP 800-86
Zachman
TOGAF ADM
SABSA
DoDAF
INCOSE SE
NERC CIP
ISO 23247
UCO / CASE
Featured Articles
Article

Building ARKONA with Claude Code

How the entire ecosystem was built using AI-assisted development

Article

Building COMET: A 7-Step Framework for AI Delegation

The governance model behind every AI decision in the ecosystem

Article

From Governance to Inference: The COMET to Skill Builder Pipeline

How governance decisions become fine-tuned local models

Article

Why Agentic AI Needs Systems Engineering Discipline

Applying defense-grade SE principles to autonomous AI agents

Article

The Case for Local Inference: When Ollama on a Tesla P40 Beats the Cloud

Why on-premise models complement cloud AI for sensitive operations

Latest Podcast
Podcast

Arkona Intelligence — Daily Research Briefing

AI-generated daily intelligence briefing covering state-of-the-art across all FS-RE layers. 17 episodes and counting.

Live Command Center

Real-time telemetry from the running ecosystem. Service status, GPU temperatures, system metrics, and recent activity — updated every 60 seconds.