🛡️ ShieldUp

Detect. Prevent. Educate.

An AI-powered scam detection and cybersecurity awareness platform designed to help users identify fraudulent messages, suspicious URLs, phishing screenshots, and social engineering attacks.

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📌 Overview

ShieldUp is a cybersecurity-focused web application that leverages Google's Gemini AI to analyze potentially fraudulent content and help users make safer decisions online.

The platform aims to combat common digital scams such as:

• Phishing attacks
• Fake job offers
• OTP and banking scams
• QR code scams
• Brand impersonation
• Social engineering attacks
• Malicious links and websites

Rather than only detecting scams, ShieldUp also focuses on user education through interactive scam simulations that teach users how scammers operate.

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🚀 Features

1. Scam Message Analyzer

Analyze suspicious messages using AI.

Users can paste messages received via:

• SMS
• WhatsApp
• Telegram
• Email
• Social Media

The AI evaluates the content and returns:

• Risk Level
• Scam Type
• Red Flags
• Safety Recommendations

Example

Input

Congratulations! You have been selected for an internship.
Pay ₹499 registration fee immediately to confirm your slot.

Output

Risk Level: High

Scam Type: Job Scam

Red Flags:
• Upfront payment request
• Artificial urgency
• Too-good-to-be-true offer

Recommendation:
Do not make any payment. Verify the opportunity through official channels.

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2. URL Scanner

Analyze suspicious links before opening them.

The scanner evaluates URLs and generates a risk assessment based on security indicators and AI analysis.

Example

Input:
https://suspicious-domain.xyz

Output:
Risk Score: 87/100
Status: Suspicious
Recommendation: Avoid visiting this website.

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3. Screenshot Detector

Upload screenshots of websites, emails, advertisements, or messages for AI-powered analysis.

The system can identify:

• Fake login pages
• Brand impersonation
• Suspicious payment requests
• Phishing attempts
• Social engineering tactics

Supported Examples

• Fake bank login pages
• Fake Amazon offers
• Fake internship forms
• Fraudulent payment screenshots

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4. QR Code Scanner

Upload a QR code image to inspect its contents safely.

The scanner:

• Decodes the QR code
• Extracts hidden URLs
• Evaluates potential threats
• Provides a risk assessment

This helps users avoid malicious QR-based phishing attacks.

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5. AI Scam Simulator ⭐

The Scam Simulator is the educational component of ShieldUp.

Users interact with simulated scammers in a safe environment and learn how to identify red flags.

Available Scenarios

• Fake Recruiter Scam
• Fake Bank Representative
• Refund Scam
• Prize Winner Scam

Learning Objectives

Users learn to:

• Identify manipulation tactics
• Avoid sharing personal information
• Recognize urgency-based scams
• Detect suspicious requests

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🏗️ Project Structure

ShieldUp/
│
├── backend/
│   ├── app/
│   │   ├── routes/
│   │   ├── services/
│   │   ├── models/
│   │   ├── database/
│   │   └── main.py
│   │
│   ├── uploads/
│   ├── .env
│   ├── requirements.txt
│   └── test.py
│
├── frontend_2.0/
│   ├── public/
│   ├── src/
│   │   ├── assets/
│   │   ├── utils/
│   │   ├── App.css
│   │   ├── App.jsx
│   │   ├── index.css
│   │   └── main.jsx
│   │
│   ├── index.html
│   ├── package.json
│   ├── tailwind.config.js
│   ├── vite.config.js
│   └── README.md
│
├── .gitignore
└── README.md

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🛠️ Tech Stack

Frontend

• React.js
• Vite
• Tailwind CSS
• Lucide React

Backend

• Python
• FastAPI
• Uvicorn
• Pydantic

AI & Machine Learning

• Google Gemini API

Utilities

• Python Dotenv
• Requests

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⚙️ Installation

Clone Repository

git clone https://github.com/your-username/shieldup.git

cd shieldup

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Frontend Setup

cd frontend

npm install

npm run dev

Frontend will run on:

http://localhost:5173

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Backend Setup

cd backend

pip install -r requirements.txt

uvicorn app.main:app --reload

Backend will run on:

http://localhost:8000

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Environment Variables

Create a .env file inside the backend directory.

GEMINI_API_KEY=your_api_key_here

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API Endpoints

Analyze Scam Message

POST /analyze-scam

Request

{
  "message": "Suspicious message content"
}

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Scan URL

POST /scan-url

Request

{
  "url": "https://example.com"
}

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Analyze Screenshot

POST /analyze-screenshot

Request

image file

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Scan QR Code

POST /scan-qr

Request

qr image file

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Scam Simulator

POST /simulate-scam

Request

{
  "scenario": "fake_recruiter"
}

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🎯 Hackathon Demo Flow

Step 1 - Scam Message Detection

Paste a suspicious message.

↓

AI analyzes the content.

↓

Risk level and scam indicators are displayed.

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Step 2 - Screenshot Analysis

Upload a suspicious screenshot.

↓

AI identifies phishing indicators.

↓

Threat assessment is generated.

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Step 3 - URL Scanning

Enter a suspicious link.

↓

The system evaluates risk.

↓

Safety recommendation is displayed.

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Step 4 - Scam Simulator

Choose a scam scenario.

↓

Interact with an AI scammer.

↓

Receive feedback and learning insights.

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🔒 Security Considerations

• API keys stored securely using environment variables
• Input validation using FastAPI and Pydantic
• Secure file upload handling
• Scalable backend architecture
• Modular AI service integration

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🔮 Future Enhancements

• Browser Extension
• Mobile Application
• Email Scam Detection
• Real-Time SMS Analysis
• Multi-Language Support
• Voice Scam Detection
• User Dashboard & Reports
• Threat Intelligence Integration
• Database Support for User History

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🌟 Vision

ShieldUp aims to make cybersecurity accessible to everyone by combining AI-powered scam detection with practical user education.

The goal is not only to identify threats but also to help users build the skills needed to stay safe online.

SAVDHAAN RAHE . SATARK RAHE . JAI HIND

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📄 License

This project is developed for educational, research, and hackathon purposes.