CRIP — Cyber Risk Intelligence Platform

AI-powered SaaS platform that ingests asset and vulnerability data, builds a knowledge graph, and uses LLM-driven reasoning to surface attack paths, coverage gaps, and remediation priorities.

Architecture

Service	Port	Purpose
Ingestion	8000	Connector framework, asset/vuln ingestion into Neo4j
Reasoning	8001	RAG pipeline: intent classification, graph traversal, LLM generation
Persona	8002	APT persona management and kill-chain simulation
Dashboard	8003	Risk scoring, heatmaps, findings, report generation
Frontend	5173	React SPA

Prerequisites

• Python 3.12+
• Node.js 20+
• Docker & Docker Compose
• An Anthropic API key (for the reasoning service)

Quick Start

# 1. Copy environment config
cp .env.example .env
# Edit .env and set ANTHROPIC_API_KEY

# 2. Start infrastructure (Neo4j, DynamoDB Local, LocalStack)
make up

# 3. Install all dependencies
make install

# 4. Run services (each in its own terminal)
make dev-ingestion
make dev-reasoning
make dev-persona
make dev-dashboard

# 5. Start frontend
cd frontend && npm run dev

Local Infrastructure

Container	Ports	Notes
Neo4j	7474 (browser), 7687 (bolt)	Auth: neo4j / crip-local, APOC enabled
DynamoDB Local	8000	No auth required
LocalStack	4566	S3, SQS, EventBridge

Testing

make test    # Run all tests
make lint    # Ruff + ESLint
make typecheck  # mypy + tsc

Project Layout

shared/          Pydantic schemas and shared utilities (installed as crip-shared)
services/
  ingestion/     Connector framework and graph ingestion
  reasoning/     RAG pipeline with Claude
  persona/       APT persona CRUD and kill-chain simulation
  dashboard/     Metrics, findings, reports
frontend/        React 18 + Vite + TailwindCSS
infra/           AWS CDK v2 stacks