SentinelScan

A full-stack secure code scanning platform that detects vulnerabilities in source code using AST parsing and pattern matching.

Features

• SQL Injection Detection — identifies string concatenation and interpolation in SQL queries using Python AST analysis and regex patterns
• Hardcoded Secrets — finds passwords, API keys, tokens, AWS credentials, and private keys embedded in source code
• Cross-Site Scripting (XSS) — detects innerHTML, document.write, dangerouslySetInnerHTML, template injection, and unsafe markup rendering
• Unsafe Functions — flags eval(), exec(), pickle.load(), os.system(), yaml.load(), and other dangerous calls
• AST-Based Analysis — uses Python's ast module for accurate detection beyond simple regex matching
• Multi-Language Regex — regex patterns extend detection to JavaScript, TypeScript, HTML, PHP, and more
• Severity Classification — every finding is rated High, Medium, or Low
• Structured Reports — JSON reports with file, line number, code snippet, description, and remediation guidance

Architecture

SentinelScan/
├── backend/                  # Python FastAPI backend
│   ├── app/
│   │   ├── api/routes.py     # REST API endpoints
│   │   ├── models/schemas.py # Pydantic data models
│   │   ├── scanners/         # Vulnerability scanners
│   │   │   ├── base.py       # Abstract scanner interface
│   │   │   ├── sql_injection.py
│   │   │   ├── secrets.py
│   │   │   ├── xss.py
│   │   │   └── unsafe_functions.py
│   │   ├── services/         # Scan orchestration
│   │   │   └── scanner_service.py
│   │   ├── utils/            # File handling utilities
│   │   │   └── file_utils.py
│   │   └── main.py           # FastAPI application entry point
│   ├── Dockerfile
│   └── requirements.txt
├── frontend/                 # React + Vite frontend
│   ├── src/
│   │   ├── components/       # UI components
│   │   ├── services/api.js   # API client
│   │   ├── styles/index.css  # Styles
│   │   ├── App.jsx           # Main application
│   │   └── main.jsx          # Entry point
│   ├── Dockerfile
│   └── nginx.conf
├── docker-compose.yml
└── README.md

API Endpoints

Method	Path	Description
POST	/api/scan/upload	Upload files for scanning (multipart form)
POST	/api/scan/repo	Scan a GitHub repo by URL
GET	/api/reports	List all scan reports
GET	/api/reports/{scan_id}	Get a specific report
GET	/api/health	Health check

Setup

Docker (recommended)

docker compose up --build

• Frontend: http://localhost:3000
• Backend API: http://localhost:8000
• API docs: http://localhost:8000/docs

Manual Setup

Backend:

cd backend
python -m venv venv
source venv/bin/activate
pip install -r requirements.txt
uvicorn app.main:app --reload

Frontend:

cd frontend
npm install
npm run dev

The frontend dev server proxies /api requests to the backend at port 8000.

Usage

Web Dashboard

1. Open http://localhost:3000
2. Upload source files using drag-and-drop or enter a public GitHub repository URL
3. View the scan report with severity breakdown and vulnerability details
4. Filter results by severity level

API

Scan uploaded files:

curl -X POST http://localhost:8000/api/scan/upload \
  -F "files=@vulnerable_app.py"

Scan a GitHub repository:

curl -X POST http://localhost:8000/api/scan/repo \
  -H "Content-Type: application/json" \
  -d '{"repo_url": "https://github.com/owner/repo"}'

Example Response

{
  "scan_id": "a1b2c3d4e5f6",
  "status": "completed",
  "files_scanned": 12,
  "summary": {
    "total": 5,
    "high": 2,
    "medium": 2,
    "low": 1
  },
  "vulnerabilities": [
    {
      "rule_id": "SQL_INJECTION",
      "title": "Potential SQL Injection",
      "severity": "High",
      "file": "app/db.py",
      "line": 42,
      "snippet": "cursor.execute(f\"SELECT * FROM users WHERE id = {user_id}\")",
      "description": "User-controlled data appears to be concatenated directly into a SQL query string.",
      "recommendation": "Use parameterized queries instead of string formatting."
    }
  ]
}

License

MIT