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| 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! 🛡️** |