🔗 Live Demo
📁 GitHub Repository
PhishNet is an AI-powered web app that detects phishing URLs in real-time using a machine learning model trained on real-world phishing data. This project showcases how cybersecurity and AI can be combined to create smart threat prevention tools.
- 🚨 Real-time phishing detection
- 🧠 Trained on phishing + safe URL datasets using TF-IDF + Logistic Regression
- 🌐 Clean, dark-themed interface with Vite + React + Tailwind CSS
- ⚡ Backend API built with Flask
- 📦 Fully deployed frontend on Vercel
- User submits a URL on the frontend
- Frontend sends the URL to the Flask backend API
- ML model predicts if the URL is safe or phishing
- Result is displayed instantly
| Layer | Tools/Tech |
|---|---|
| Frontend | React, TypeScript, Vite, Tailwind CSS, shadcn/ui |
| Backend | Python, Flask |
| ML Model | TF-IDF Vectorizer + Logistic Regression |
| Deployment | Vercel (Frontend), Localhost or Render (Backend) |
git clone https://github.com/Adityarao19/phishnet.git cd frontend npm install npm run dev
cd backend python -m venv venv source venv/bin/activate # On Windows: venv\Scripts\activate pip install -r requirements.txt python app.py
🌍 Deployment Frontend: Vercel Deployment
Backend: Can be deployed to Render, Railway, or Replit