ScamShield pro – AI Scam & Fake Link Detector

AI-powered tool that detects phishing messages and fake links in real time. It warns users before they click helping prevent scams, data theft and financial loss making the internet safer in our life

Comment

Inspiration

Online scams are growing faster than awareness. People lose money daily to fake job offers, phishing links, fake UPI payment messages, and fraudulent websites. Most victims are students, job seekers, and elderly users who cannot easily identify suspicious links. We realized that existing cybersecurity tools are too technical and not built for everyday users. There is no simple tool that instantly tells a person whether a link is safe before they click it.

What it does

ScamShield detects suspicious links and warns users before they open them. Users simply paste a URL and the AI instantly provides: Scam probability score (%) Red/Green safety indicator Reason for risk (phishing keywords, fake domain, suspicious patterns) Voice alert feature for elders and non-technical users Web app Browser extension (real-time link protection) Goal: Stop scams before they happen.

How we built it

We built ScamShield using a simple but powerful full-stack architecture: Frontend HTML, CSS, JavaScript Clean UI to paste links and display results Backend Python + Flask API Machine learning scam detection logic URL analysis using: Domain age check Suspicious keyword detection HTTPS & domain pattern analysis Extension Chrome Extension for real-time link checking The system sends a URL → backend AI → risk score → user warning.

Challenges we ran into

• Finding reliable scam detection datasets • Building a simple AI model within hackathon time • Making cybersecurity understandable for non-technical users • Connecting extension + backend in real time • Designing a UI simple enough for elderly users

Accomplishments that we're proud of

• Built a working AI scam detection prototype in limited time • Created a real-world solution with social impact • Made cybersecurity simple and accessible • Added voice alerts for inclusivity • Developed both web app and browser extension

What we learned

• Basics of phishing detection and cybersecurity • Building and deploying a full-stack AI project • Integrating machine learning into real-world apps • Importance of UX in security products • Team collaboration under hackathon pressure

What's next for ScamShield – AI Scam & Fake Link Detector

• Real-time WhatsApp & SMS scam detection • Multilingual voice alerts (Indian languages) • Mobile app version • Integration with banking & UPI apps • Community scam reporting system • Advanced AI model trained on real phishing datasets Our vision is to make ScamShield a daily digital safety tool for millions.

Built With

Share this project:

Updates