SigmaShield is a mobile application that helps users detect and learn about online scams. Powered by AI and community insights, SigmaShield offers real-time URL analysis, educational modules, analytics dashboards, and a community forum.
- Scam Detection: Paste suspicious URLs to detect phishing or scam links with AI-powered confidence scores.
- Learn: Explore in-depth information about scams including definitions, common types, identification tips, and avoidance strategies.
- Analytics: Visualize total scam detections over time and get a breakdown of scam types.
- Forum: Join the community to discuss suspicious links, share experiences, and ask questions.
- Clone the repository:
git clone https://github.com/yourusername/SigmaShield.git cd SigmaShield - Install dependencies:
npm install
- Start the Expo development server:
npx expo start
- Launch the app on:
- Android emulator
- iOS simulator
- Expo Go (Android/iOS)
- Home: Login or continue as a guest to access the app.
- Scam Detection: Enter a URL and tap Detect. View results including phishing status, confidence, and keywords.
- Learn: Browse educational topics about scams. Tap a topic to read more.
- Analytics: View interactive charts of scam detection trends.
- Forum: Search, read, and create posts to discuss scam-related topics.
/app
/_layout.tsx # App-wide layout and routing
/(tabs)
index.tsx # Home (login) screen
scam-detection.tsx
learn.tsx
analytics.tsx
forum.tsx
report-scam.tsx
/components # Reusable UI components
/constants # App constants (colors, etc.)
/assets # Images and fonts
The app uses an external endpoint for scam detection:
POST https://dsta-code-exp-2025.onrender.com/predict
Body: { "url": "<URL_TO_ANALYZE>" }
Response: {
"is_phishing": boolean,
"confidence": number,
"keywords_found": string[],
"explanation": string
}
Contributions and feedback are welcome! Please open issues or submit pull requests on GitHub.
This project is licensed under the MIT License.