README.md

---
license: mit
title: Scam Verifier
sdk: gradio
emoji: 💻
colorFrom: blue
colorTo: red
short_description: Verify wether the message is a scam or not
sdk_version: 5.42.0
---
# 🛡️ Scam-Signal Verifier

A comprehensive web application that helps users identify potentially fraudulent messages, emails, and advertisements. Perfect for protecting students, elderly individuals, and anyone who wants to stay safe from online scams.

## 🌟 Features

### Multi-Agent Analysis System
- **Claim Extractor**: Parses messages for URLs, phone numbers, emails, and financial amounts
- **Pattern Verifier**: Analyzes content against known scam patterns and suspicious keywords
- **Risk Calculator**: Provides a comprehensive risk score (0-100) with clear classification
- **Human-Friendly Explainer**: Generates actionable recommendations and reporting templates

### Detection Capabilities
- **Phishing Emails**: Bank, PayPal, Amazon verification scams
- **Job Offer Scams**: Work-from-home and "easy money" schemes  
- **Investment Fraud**: Cryptocurrency and get-rich-quick schemes
- **Lottery/Prize Scams**: Fake winnings and inheritance claims
- **Urgency Tactics**: High-pressure language and artificial deadlines
- **Suspicious Domains**: Known malicious and shortened URLs

### User Experience
- Clean, modern interface with gradient design
- Real-time risk assessment with color-coded results
- Pre-loaded example scams for testing
- One-click report template generation
- Mobile-responsive design

## 🚀 Quick Start

### Local Development
```bash
# Clone the repository
git clone <repository-url>
cd scam-signal-verifier

# Install dependencies
pip install -r requirements.txt

# Run the application
python app.py
```

### Docker Deployment
```bash
# Build the image
docker build -t scam-verifier .

# Run the container
docker run -p 7860:7860 scam-verifier
```

### Hugging Face Spaces
This app is optimized for Hugging Face Spaces deployment:
1. Upload all files to your Spaces repository
2. Set the Space to use Python/Gradio environment
3. The app will automatically start on port 7860

## 🎯 How It Works

### 1. Message Analysis
The system extracts key information from suspicious messages:
- URLs and domain reputation
- Contact information (phone, email)
- Financial references and amounts
- Suspicious keywords and phrases
- Urgency indicators and pressure tactics

### 2. Risk Assessment
Multi-factor scoring algorithm considers:
- **Keyword Score** (0-40 points): Suspicious language patterns
- **Urgency Score** (0-25 points): High-pressure tactics
- **Domain Risk** (0-20 points): Suspicious or shortened URLs
- **Contact Risk** (0-10 points): Multiple contact methods
- **Financial Risk** (0-15 points): Money-related content

### 3. Classification System
- **🔴 HIGH RISK (80-100)**: Obvious scam, avoid completely
- **🟡 MEDIUM RISK (50-79)**: Suspicious, verify independently  
- **🟢 LOW RISK (25-49)**: Minor concerns, stay cautious
- **✅ MINIMAL RISK (0-24)**: Appears legitimate

## 📊 Example Results

### High-Risk Phishing Email
```
Risk Score: 95/100 - HIGH RISK
Red Flags:
🚨 Contains 6 suspicious keywords/phrases
🚨 Uses high-pressure urgency tactics  
🚨 Uses suspicious domain: secure-bank-verify.net
🚨 Mentions money/financial transactions

Recommendations:
🚫 Do NOT click any links or provide personal information
📧 Report this message as spam/phishing
🛡️ Block the sender immediately
```

## 🛡️ Safety Features

- **No External API Calls**: All analysis happens locally for privacy
- **Educational Focus**: Teaches users to recognize scam patterns
- **Report Generation**: Creates templates for reporting to authorities
- **Multiple Examples**: Pre-loaded scenarios for learning

## 🔧 Technical Stack

- **Backend**: Python Flask with modular analysis engine
- **Frontend**: Responsive HTML/CSS/JavaScript
- **Deployment**: Docker + Gunicorn for production
- **Security**: No data persistence, privacy-focused design

## 📱 Mobile Support

The interface is fully responsive and works seamlessly on:
- Desktop browsers
- Mobile phones
- Tablets
- Touch devices

## 🤝 Contributing

This is an educational tool designed to help people stay safe online. Feel free to:
- Report bugs or issues
- Suggest new scam patterns to detect
- Improve the UI/UX design
- Add new analysis features

## 📄 License

Open source educational project. Use responsibly to help others stay safe from online scams.

## ⚠️ Disclaimer

This tool is for educational purposes and general guidance. It should not be the sole method for determining if something is a scam. Always use your best judgment and consult with relevant authorities when needed.

---

**Stay Safe Online! 🛡️**