The Scam Message Checker is a web-based tool designed to help users identify potentially dangerous scam messages. Users can paste any message they receive—via WhatsApp, SMS, email, or social media—and the tool analyzes it for common scam patterns such as:
- Urgency words (e.g., "urgent", "now", "immediately")
- Prize or lottery claims
- Requests for money or transfers
- Requests for passwords, OTPs, or bank information
The tool classifies messages into three risk levels:
- 🟢 SAFE
- 🟡 RISKY
- 🔴 DANGEROUS
Clear advice is provided based on the risk level to guide users in taking the next steps safely.
This project was built to promote digital safety awareness, especially for:
- Beginners on the internet
- Elderly users
- Individuals unfamiliar with online scam tactics
The goal is to make internet safety simple, visual, and actionable, without requiring technical knowledge.
The project is hosted live and accessible via any modern web browser:
View Live Project
- Languages: HTML, CSS, JavaScript
- Data Storage:
LocalStorage(for passing messages between pages) - UI: Responsive and beginner-friendly interface optimized for mobile and desktop
- User pastes a suspicious message into the input box.
- Click "Check Message" → message stored in LocalStorage.
- User is redirected to the results page.
- JavaScript analyzes the message using keyword pattern matching.
- Result page displays:
- Risk level
- Color-coded indicator
- Safety advice
- Fully responsive on desktop and mobile devices
- Large, clear text and buttons for easier readability
- Simplified interface for first-time users and elderly individuals
- Front-end development with HTML, CSS, and JavaScript
- Logical pattern recognition implementation
- User-focused and accessibility-first UI design
- Data persistence using LocalStorage
- Deployment and hosting on GitHub Pages
- Tested with 10 users, including elderly and beginners
- 7/10 users found it intuitive and easy to use
- 3/10 users needed additional guidance → led to UI improvements
User testing shows that iterative feedback is key to building usable digital safety tools.
- Detect suspicious links (URLs) automatically
- Expand the keyword database for more comprehensive scam detection
- Add multilingual support
- Improve UI/UX for better accessibility and visual clarity
- Optionally, integrate AI-driven risk scoring in future versions
Developed as part of a digital literacy initiative to empower non-technical users to recognize online scams and protect themselves from potential fraud.