StudentShield AI

AI-powered scam detection platform that protects students from fake internships, jobs, scholarships, courses, and phishing opportunities using multi-layer threat analysis.

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Inspiration

Students are frequently targeted by fake internships, job offers, scholarships, online courses, and study-abroad scams. Many of these scams appear legitimate and trick students into sharing personal information, paying registration fees, or exposing credentials.

We built StudentShield AI to act as a digital safety layer for students before they engage with suspicious opportunities.

What it does

StudentShield AI analyzes opportunities through multiple verification layers:

  • Opportunity Text Scanner
  • URL Reputation Scanner
  • Screenshot OCR Scanner
  • AI-Powered Threat Assessment
  • Risk Scoring Engine
  • Scam Classification System
  • Scan History Dashboard

The platform identifies suspicious indicators such as:

  • Upfront payment requests
  • Fake recruiter patterns
  • Generic email domains
  • Phishing URLs
  • Domain impersonation
  • Suspicious urgency tactics
  • Credential harvesting attempts

Users receive:

  • Risk Score (0-100)
  • Threat Classification
  • Confidence Rating
  • Scam Indicators
  • Safety Recommendations

How we built it

Frontend:

  • React
  • Vite
  • Tailwind CSS

Backend:

  • Node.js
  • Express.js

AI Layer:

  • Google Gemini API

Cloud Infrastructure:

  • AWS DynamoDB

Authentication:

  • JWT Authentication

Challenges we ran into

  • Designing accurate scam-detection heuristics
  • Reducing false positives on legitimate opportunities
  • Handling Gemini API failures and fallback logic
  • Building a scalable scan-history system with DynamoDB
  • Calibrating risk scores for real-world student scenarios

Accomplishments that we're proud of

  • Built a complete end-to-end cybersecurity platform
  • Implemented real AI-powered opportunity analysis
  • Added URL reputation and phishing detection
  • Created persistent scan history using AWS DynamoDB
  • Developed a professional cybersecurity dashboard experience

What we learned

  • Practical AI integration with cybersecurity workflows
  • Cloud-native database design using DynamoDB
  • Threat intelligence and phishing detection concepts
  • Risk scoring and trust indicator modeling

What's next for StudentShield AI

  • Multi-model AI consensus engine
  • Real-time domain reputation integrations
  • Browser extension support
  • University verification partnerships
  • Community scam intelligence network
  • Advanced threat intelligence feeds

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