🛡️ Cloud Attack Path Visualiser
A Graph-Based Framework for Cloud Attack Path Discovery, Risk Assessment, and Visualization

⚠️ DEFENSIVE TOOL ONLY — This tool analyzes simulated AWS-style JSON configs. It never contacts real cloud accounts or performs any attacks.

Features
9 Deterministic Security Detectors — SSH exposure, public DB ports, public S3, unencrypted storage, public RDS, overly permissive IAM, hardcoded secrets, and more
Graph-Based Attack Path Discovery — Builds a networkx graph and finds multi-step attack paths from internet to high-value targets
Risk Scoring — 0–100 overall risk score with severity breakdown
Interactive Visualization — Pyvis-powered interactive network graph in the Streamlit dashboard
REST API — FastAPI endpoints for programmatic access
Optional AI Explanation — Uses OpenAI (if configured) to explain findings in plain English
Architecture
src/ ← Core engine (no Streamlit dependency)
models.py ← Pydantic data models
parser.py ← JSON config parser
detectors.py ← Security misconfiguration detectors
graph_builder.py ← Networkx graph construction
pathfinder.py ← Attack path discovery
risk_scorer.py ← Risk scoring
explainer.py ← AI explanation (optional)
engine.py ← Pipeline orchestrator

api/main.py ← FastAPI REST API
app/streamlit_app.py ← Streamlit dashboard
tests/ ← pytest test suite
data/ ← Sample simulated configs
Quick Start

Install dependencies

pip install -r requirements.txt

Run full test suite (73 tests)

pytest tests/ -v

Launch the interactive Streamlit dashboard

streamlit run app.py

Or start the FastAPI server

uvicorn api.main:app –reload
API Usage

Health check

curl http://localhost:8000/health

Full analysis

curl -X POST http://localhost:8000/analyze
-H “Content-Type: application/json”
-d @data/sample_config.json
–data-urlencode “config@data/sample_config.json”

Or with Python

import httpx, json
config = json.load(open(“data/sample_config.json”))
resp = httpx.post(“http://localhost:8000/analyze”, json={“config”: config})
print(resp.json())