QRGuard

QRGuard is your secure QR scanner that protects you from malicious links, phishing, and threats—scan with confidence and keep your device safe, always.

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QRGuard – Project Story

Inspiration

The idea for QRGuard came from a growing concern over malicious QR codes being circulated in public places—be it phishing scams on posters, payment frauds via fake UPI codes, or even malicious URLs shared offline. I realized there was no easy-to-use tool that could proactively check the safety of a QR code before a user clicks. With rising digital threats, I wanted to build a simple mobile-first scanner that empowers everyday users to protect themselves.

What it does

QRGuard is a smart QR code scanner that instantly checks the safety of any scanned URL using trusted sources like Google Safe Browsing, PhishTank, and other daily-updated threat databases. It leverages AI models such as ChatGPT, Gemini, and Claude.ai to provide real-time analysis, flag suspicious links, and suggest safe alternatives. Users can log in via magic link authentication or continue as guests, with the app maintaining a history of scanned links.

How we built it

I developed the app using TypeScript with React Native and Expo for the mobile frontend. For authentication, database storage, and edge functions, I integrated Supabase. The backend API was built using NestJS, which handles threat-checking by interfacing with Google Safe Browsing, PhishTank, and internal ML logic powered by AI models like ChatGPT.

The app supports:

  • Magic link login (via Supabase)
  • Guest access with limited features
  • History of scanned links
  • AI-based threat summaries
  • Clean UI built with dark mode support

Challenges we ran into

  • Integrating real-time URL scanning APIs and handling rate limits from services like Google Safe Browsing.
  • Creating a seamless magic link login flow across platforms.
  • Combining multiple AI outputs (ChatGPT, Claude, Gemini) into one meaningful summary for the user.
  • Ensuring the app remains lightweight while still being powerful in its detection capabilities.

Accomplishments that we're proud of

  • Built and shipped a full-stack mobile app as a solo developer.
  • Integrated multi-AI models into a single pipeline to analyze malicious content in scanned QR links.
  • Designed a user-friendly interface with both guest and authenticated modes.
  • Enabled real-time protection using only open-source and developer-first tools.

What we learned

  • Efficiently combining AI models like ChatGPT, Claude, and Gemini for a single task.
  • The power of Supabase for quickly adding secure, scalable backend features.
  • The importance of UI/UX when building cybersecurity tools for non-technical users.
  • How essential URL safety is in the modern digital landscape—and how underprotected users are.

What's next for QRGuard

The roadmap for QRGuard includes:

  • SMS Scan: Detecting suspicious links in SMS content automatically.
  • Payment Scan: Validating UPI/payment QR codes to protect against financial fraud.
  • Push notifications for newly discovered threats in previously scanned links.
  • Browser extension to scan QR codes and links directly on the web.
  • Local ML models for faster and offline-first threat detection.

QRGuard is powered by open-source technologies and AI—designed to make digital safety simple and accessible to all.

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