Inspiration:Scamsafe-app was inspired by the daily flood of scam and phishing messages targeting people of all ages and backgrounds. We wanted to make digital safety accessible to everyone—not just cybersecurity experts—by providing an easy way to check suspicious messages and learn how to stay safe online.
What it does
The app highlights scam red flags—such as urgent language, strange links, and threats—while explaining its reasoning so users learn how to spot scams themselves.
How we built it
AI/ML: Integrated Groq AI for advanced scam classification and scoring. Collaboration: Built remotely using VS Code Live Share and version control. APIs: Leveraged ngrok for secure public testing and (optionally) Google Speech-to-Text for voice analysis.
Challenges we ran into
Detecting new and evolving scam tactics beyond simple keyword checks. Integrating and managing several APIs with different rate limits and authentication. Balancing thorough scam detection with fast, user-friendly responses. Ensuring user data privacy and keeping API keys and sensitive info secure. Keeping remote collaboration smooth and efficient across team members and time zones.
Accomplishments that we're proud of
Built an interface that’s both educational and protective, not just a black box. Successfully integrated advanced AI for richer, more accurate scam analysis. Maintained strong teamwork and learned new tech together.
What we learned
Real-world experience with SMS APIs, and integrating external AI.
What's next for Scamsafe-app
Expanding to check fraudulent images and checks using computer vision. Adding real-time threat updates so detection improves as scams evolve.
Built With
- bash
- groqai
- html/css
- python
- visual-studio
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