ScamShield

🚀 Live Demo

Frontend (Live Website)

https://scam-shield-omega-six.vercel.app

Backend API

https://scamshield-eg3q.onrender.com

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ScamShield is an AI-powered full-stack web application that helps users detect potentially fraudulent messages and suspicious URLs, analyze risk levels, and maintain a history of security reports through an interactive dashboard.

The platform combines AI-assisted analysis, custom risk scoring logic, secure authentication, and URL security checks to identify scam patterns and provide meaningful risk explanations.

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Why I Built This Project

Online scams are becoming increasingly common through SMS, emails, calls, social media platforms, and phishing websites. I built ScamShield to gain hands-on experience with full-stack development while solving a real-world cybersecurity problem.

The project focuses on scam detection, authentication, REST API development, database integration, dashboard analytics, and secure report management.

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Features

🔐 Authentication

• User Registration
• User Login
• JWT Authentication
• Protected Routes
• Secure Password Hashing with bcrypt.js

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🤖 Scam Message Detection

• Analyze suspicious messages

• AI-assisted scam analysis

• Custom risk scoring logic

• Risk Classification:

  • HIGH Risk
  • MEDIUM Risk
  • LOW Risk

• Risk Score Generation

• Detection Reason Generation

• Intelligent scam pattern identification

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🌐 URL Risk Analyzer

• Analyze suspicious website URLs
• Detect potentially unsafe links
• HTTPS Security Check
• Suspicious Keyword Detection
• URL Risk Score Generation
• Risk Explanation

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📊 Dashboard

• Total Scam Checks
• High Risk Reports Count
• Medium Risk Reports Count
• Safe Reports Count
• Real-Time Statistics
• Recent Activity Tracking

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📜 History Tracking

• View Previous Scam Reports
• View URL Scan Reports
• Risk Level Tracking
• Message Analysis History
• Timestamped Records

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👤 User Profile

• Logged-in User Information
• Protected User Dashboard
• Secure Session Management

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🗄️ Database Integration

• MongoDB Atlas Cloud Database
• Persistent Report Storage
• User-Specific Data Management

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Tech Stack

Frontend

• HTML5
• CSS3
• JavaScript (Vanilla JS)
• Responsive UI Design
• Font Awesome Icons

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Backend

• Node.js
• Express.js

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Database

• MongoDB Atlas
• Mongoose

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Authentication & Security

• JWT (JSON Web Token)
• bcrypt.js

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AI Integration

• Groq API Integration
• Large Language Model (LLM) Based Scam Analysis
• AI Generated Risk Explanation

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API Endpoints

Authentication

Method	Endpoint	Description
POST	/api/auth/register	Register a new user
POST	/api/auth/login	Login and receive JWT token

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User

Method	Endpoint	Description
GET	/api/user/profile	Get logged-in user profile

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Scam Detection

Method	Endpoint	Description
POST	/api/scam/check	Analyze suspicious message
GET	/api/scam/history	Get scam report history
GET	/api/scam/stats	Get dashboard statistics

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URL Scanner

Method	Endpoint	Description
POST	/api/url/check	Analyze suspicious URL
GET	/api/url/history	Get URL scan history

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Project Structure

ScamShield
│
├── backend
│   ├── config
│   ├── controllers
│   ├── middleware
│   ├── models
│   ├── routes
│   ├── services
│   ├── utils
│   └── server.js
│
├── frontend
│   ├── css
│   ├── js
│   ├── index.html
│   ├── login.html
│   ├── register.html
│   ├── dashboard.html
│   └── history.html
│
└── README.md

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Implemented Features

✅ MongoDB Atlas Connection ✅ User Registration & Login ✅ JWT Authorization ✅ Protected APIs ✅ Scam Detection System ✅ AI-Assisted Risk Analysis ✅ Risk Classification System ✅ Custom Risk Scoring Logic ✅ URL Risk Analyzer ✅ HTTPS Security Checking ✅ Suspicious URL Pattern Detection ✅ Scam Report Storage ✅ URL Report Storage ✅ Dashboard Statistics ✅ Recent Activity Tracking ✅ History Management ✅ Responsive Frontend ✅ User Profile Section

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Screenshots

(Add screenshots of:)

• Login Page
• Registration Page
• Dashboard
• Scam Analysis Result
• URL Scanner Result
• History Page

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Future Improvements

• Machine Learning Based Scam Classification
• Real-Time Phishing Database Integration
• Email Scam Detection
• Admin Dashboard
• Advanced Risk Scoring Algorithm
• Data Visualization Charts
• Export Reports Feature
• Browser Extension Support
• Mobile Application

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Learning Outcomes

Through this project I learned:

• REST API Development
• Authentication & Authorization
• JWT Security
• MongoDB Atlas Integration
• AI API Integration
• LLM-Based Application Development
• Backend Architecture
• Frontend & Backend Communication
• API Testing
• Git & GitHub Workflow
• Full-Stack Project Development

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Author

Siddhi Dublish

AI-Powered Full-Stack Security Project built to strengthen backend development, AI integration, authentication, database management, and real-world cybersecurity problem-solving skills.

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⭐ If you like this project, consider giving it a star on GitHub.