NetReconScanner is a full-stack cybersecurity web application designed for ethical network reconnaissance and educational security analysis. It combines a modern React + TypeScript dashboard with an Express/Nmap backend to perform automated scans, visualize open ports, and generate structured security reports.
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🌐 Modern cybersecurity-themed dashboard (Vite + Tailwind CSS)
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🔎 Automated network scanning using Nmap
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⚡ Scan Profiles:
- Quick Scan
- Service Detection
- Deep Scan
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🧠 Risk Level Indicators for open ports
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🖥️ Live terminal-style scan logs
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📊 Real-time results visualization
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🧾 JSON / PDF report export
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🔐 Authentication-ready architecture
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🗂️ Scan history tracking
NetReconScanner/
│
├── client/ → React + TypeScript frontend
├── server/ → Express API & scanning logic
├── shared/ → Common utilities & types
└── netlify/ → Deployment configuration
- React + TypeScript
- Vite
- Tailwind CSS
- Node.js + Express
- Nmap Integration
- REST API Architecture
This project simulates a Security Operations Center (SOC)-style interface, allowing users to:
- Enter IP address or subnet targets
- Launch automated scans
- View open ports with service details
- Monitor scan progress in real-time
This tool is built strictly for educational and authorized security testing. Only scan systems and networks that you own or have explicit permission to test.
Adhi Cybersecurity & Artificial Intelligence Student
Adhi focuses on building practical security tools and intelligent systems. Passionate about ethical hacking, network reconnaissance, and secure full-stack development, this project demonstrates hands-on experience creating real-world cybersecurity dashboards.
🔗 GitHub: https://github.com/Adhi-crypto
React TypeScript Express Nmap Python Cybersecurity Full-Stack Development
git clone https://github.com/Adhi-crypto/NetReconScanner.git
cd NetReconScanner
npm install
npm run dev
Frontend can be deployed via Netlify or Vercel. Backend API can be hosted using Render or similar Node.js hosting platforms.
To demonstrate real-world cybersecurity engineering skills by building a production-style reconnaissance dashboard that combines secure backend scanning with an interactive web interface.
This project is intended for educational and ethical cybersecurity research.