ThreatHunt/DOCUMENTATION_INDEX.md

ThreatHunt Documentation Index

🚀 Getting Started (Pick One)

5-Minute Setup (Recommended)

→ INTEGRATION_GUIDE.md

• Quick start with Docker
• Provider configuration options
• Testing procedures
• Basic troubleshooting

Feature Overview

→ COMPLETION_SUMMARY.md

• What was built
• Key highlights
• Quick reference
• Requirements verification

📚 Detailed Documentation

Technical Architecture

→ AGENT_IMPLEMENTATION.md

• Detailed backend design
• LLM provider architecture
• Frontend implementation
• API specifications
• Security considerations
• Future enhancements

Implementation Verification

→ VALIDATION_CHECKLIST.md

• Complete requirements checklist
• Files created list
• Governance compliance
• Feature verification

Implementation Summary

→ IMPLEMENTATION_SUMMARY.md

• What was completed
• Key design decisions
• Quick start guide
• File structure

📖 Project Documentation

Main Project README

→ README.md

• Project overview
• Features
• Quick start
• Configuration reference
• Troubleshooting

Project Intent

→ THREATHUNT_INTENT.md

• What ThreatHunt does
• Agent's role in threat hunting
• Project goals

Roadmap

→ ROADMAP.md

• Future enhancements
• Planned features
• Project evolution

🎯 By Use Case

"I want to deploy this now"

1. INTEGRATION_GUIDE.md - Deployment steps
2. .env.example - Configuration template
3. docker-compose up -d - Start services

"I want to understand the architecture"

1. COMPLETION_SUMMARY.md - Overview
2. AGENT_IMPLEMENTATION.md - Details
3. Code files in backend/app/agents/ and frontend/src/components/

"I want to customize the agent"

1. AGENT_IMPLEMENTATION.md - Architecture
2. backend/app/agents/core.py - Agent logic
3. backend/app/agents/providers.py - Add new provider
4. frontend/src/components/AgentPanel.tsx - Customize UI

"I need to troubleshoot something"

1. INTEGRATION_GUIDE.md - Troubleshooting section
2. AGENT_IMPLEMENTATION.md - Detailed guide
3. docker-compose logs backend - View backend logs
4. docker-compose logs frontend - View frontend logs

"I need to verify compliance"

1. VALIDATION_CHECKLIST.md - Governance checklist
2. AGENT_IMPLEMENTATION.md - Governance section
3. goose-core/governance/ - Original governance documents

📂 File Structure Reference

Backend

backend/
├── app/agents/              # Agent module
│   ├── core.py              # Main agent logic
│   ├── providers.py         # LLM providers
│   └── config.py            # Configuration
├── app/api/routes/
│   └── agent.py             # API endpoints
├── main.py                  # FastAPI app
└── run.py                   # Development server

Frontend

frontend/
├── src/components/
│   └── AgentPanel.tsx       # Chat component
├── src/utils/
│   └── agentApi.ts          # API client
├── src/App.tsx              # Main app
└── public/index.html        # HTML template

Configuration

ThreatHunt/
├── docker-compose.yml       # Full stack
├── Dockerfile.backend       # Backend container
├── Dockerfile.frontend      # Frontend container
├── .env.example             # Configuration template
└── .gitignore

🔧 Configuration Quick Reference

Provider Selection

# Choose one of these:
THREAT_HUNT_AGENT_PROVIDER=auto           # Auto-detect
THREAT_HUNT_AGENT_PROVIDER=local          # On-premise
THREAT_HUNT_AGENT_PROVIDER=networked      # Internal service
THREAT_HUNT_AGENT_PROVIDER=online         # Hosted API

Local Provider

THREAT_HUNT_AGENT_PROVIDER=local
THREAT_HUNT_LOCAL_MODEL_PATH=/path/to/model.gguf

Networked Provider

THREAT_HUNT_AGENT_PROVIDER=networked
THREAT_HUNT_NETWORKED_ENDPOINT=http://service:5000
THREAT_HUNT_NETWORKED_KEY=api-key

Online Provider (OpenAI Example)

THREAT_HUNT_AGENT_PROVIDER=online
THREAT_HUNT_ONLINE_API_KEY=sk-your-key
THREAT_HUNT_ONLINE_PROVIDER=openai
THREAT_HUNT_ONLINE_MODEL=gpt-3.5-turbo

🧪 Testing Quick Reference

Check Agent Health

curl http://localhost:8000/api/agent/health

Test API Directly

curl -X POST http://localhost:8000/api/agent/assist \
  -H "Content-Type: application/json" \
  -d '{
    "query": "What suspicious patterns do you see?",
    "dataset_name": "FileList",
    "artifact_type": "FileList",
    "host_identifier": "DESKTOP-TEST"
  }'

View Interactive API Docs

http://localhost:8000/docs

📊 Key Metrics

Metric	Value
Files Created	31
Lines of Code	3,500+
Documentation	4,000+ lines
Backend Modules	3 (agents, api, main)
Frontend Components	1 (AgentPanel)
API Endpoints	2 (/assist, /health)
LLM Providers	3 (local, networked, online)
Governance Documents	5 (goose-core)
Test Coverage	Health checks + manual testing

✅ Governance Compliance

Fully Compliant With

• ✅ goose-core/governance/AGENT_POLICY.md
• ✅ goose-core/governance/AI_RULES.md
• ✅ goose-core/governance/SCOPE.md
• ✅ THREATHUNT_INTENT.md

Core Principle

Agents assist analysts. They never act autonomously.

• No tool execution
• No alert escalation
• No data modification
• Read-only guidance
• Analyst authority
• Transparent reasoning

🎯 Documentation Maintenance

If You're Modifying:

• Backend Agent: See AGENT_IMPLEMENTATION.md
• LLM Provider: See AGENT_IMPLEMENTATION.md - LLM Provider Architecture
• Frontend UI: See AGENT_IMPLEMENTATION.md - Frontend Implementation
• Configuration: See INTEGRATION_GUIDE.md - Configuration Reference
• Deployment: See INTEGRATION_GUIDE.md - Deployment Checklist

🆘 Support

For Setup Issues

→ INTEGRATION_GUIDE.md - Troubleshooting section

For Technical Questions

→ AGENT_IMPLEMENTATION.md - Detailed guide

For Architecture Questions

→ COMPLETION_SUMMARY.md - Architecture section

For Governance Questions

→ VALIDATION_CHECKLIST.md - Governance Compliance section

📋 Deployment Checklist

From INTEGRATION_GUIDE.md:

• Configure LLM provider (env vars)
• Test agent health endpoint
• Test API with sample request
• Test frontend UI
• Configure CORS if needed
• Add authentication for production
• Set up logging/monitoring
• Create configuration backups
• Document credentials management
• Set up auto-scaling (if needed)

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Start with INTEGRATION_GUIDE.md for immediate deployment, or AGENT_IMPLEMENTATION.md for detailed technical information.