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It uses Machine Learning and Natural Language Processing (NLP) techniques to flag phishing threats and offers a simple, secure interface with user login and history tracking.\n\n---\n\n## 🚀 Features\n\n- 🔗 **URL Phishing Detection** — Analyze and classify URLs as safe or phishing.\n- 📧 **Email Body Analysis** — Check raw email text to detect phishing patterns.\n- 👤 **User Authentication** — Register and log in to track your own detection history.\n- 🕓 **Scan History** — Review previous URL and email scans with results.\n\n---\n\n## 🧰 Tech Stack\n\n### 💻 Frontend\n- React.js\n- HTML5 / CSS3\n\n### 🖥 Backend\n- Node.js (Express)\n- Python (Flask)\n\n### 🤖 Machine Learning\n- XGBoost (URL Detection)\n- Multinomial Naive Bayes (Email Text Detection)\n- CountVectorizer for NLP processing\n\n### 🛢 Database\n- MongoDB (Mongoose)\n\n---\n\n## 📂 Project Structure\n\n```\n\nDeepPhish -- Phishing Detection Application/\n├── Backend/                     # Node.js API for user management and detection logic\n├── Backend/data                 # Pre-labeled phishing and safe URLs\n├── Python/DeepPhish--Python     # Flask server with ML models\n├── React/front-end/             # React app for UI\n\n\n````\n\n---\n\n### ⚙️ Setup Instructions\n### GO into directory DeepPhish -- Phishing Detection Application\n\n### 1. Start Backend (Node.js)\nMake sure your MongoDB is running locally.\n```bash\ncd Backend\nnpm install #for first time\nnode app.js\n```\n\nMake sure `.env` file is configured correctly:\n\n```env\nPORT=####\nMONGO_URI=mongodb+srv://\u003cusername\u003e:\u003cpassword\u003e@cluster.mongodb.net/DeepPhish\n```\nfor example i used it as\nPORT=5001\nMONGO_URI=mongodb://127.0.0.1:27017/phishingdb\n\n\n### 2. Start Python ML Server (Flask)\n\n```bash\ncd ../Python\ncd DeepPhish--Python\npip install -r requirements.txt \npython app.py\n```\n\n### 3. Start Frontend (React)\n\n```bash\ncd ../React/front-end\nnpm install         # only if node_modules was deleted\nnpm start\n```\n\n---\n\n## 🔒 Signup / Login Info\n\n### 🔐 Password Format\n\n* Minimum 8 characters \n* Must include one number and one special character\n* Example: `Secure@123`\n\n### ✅ Email Format\n\n* Must be in standard format (e.g., `user@example.com`)\n\n---\n\n## 🧪 How to Use\n\n1. **Signup/Login** to your account.\n2. Navigate to:\n\n   * **Check URL** — Enter a website link.\n   * **Check Email** — Paste the email content/body.\n3. The system will return:\n\n   * `Phishing` or `Safe`\n4. Go to **View History** to see all previously scanned results.\n\n---\n\n\n## 🧭 Future Scope\n\n* SMS Phishing Detection\n* Admin dashboard\n* Chrome extension\n* Real-time alert system\n\n---\n\n## 🧑‍💻 Author\n\n**Saad Asif**\nFinal Year CS Student | Cybersecurity, AL, ML \u0026 Full Stack Enthusiast\nLinkedIn: [https://www.linkedin.com/in/saadasif-nu/](https://www.linkedin.com/in/saadasif-nu/)\n\n**Muhammad Hammad**\nFinal Year CS Student | Cybersecurity, AL, ML \u0026 Full Stack Enthusiast\nLinkedIn: [https://www.linkedin.com/in/muhammad-hammad-69aa36248/](https://www.linkedin.com/in/muhammad-hammad-69aa36248/)","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsaadasif-nu%2Fdeepphish","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fsaadasif-nu%2Fdeepphish","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsaadasif-nu%2Fdeepphish/lists"}