VerifyX

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Inspiration

Every day students and job seekers face fake job posts, scam internships, and fraudulent HR messages demanding payments or collecting personal data. These scams waste time, steal money, and break trust. VerifyX was inspired by the need for a simple, fast, and accessible tool that instantly checks whether an opportunity is genuine or suspicious — especially for young applicants who are most targeted.

What it does

VerifyX analyzes any job post, internship listing, email, or URL for scam signals. Users paste text, and the system identifies warning patterns like payment requests, suspicious numbers, scam keywords, fake HR language, and fraud indicators. It then generates a clear Green / Yellow / Red risk score with human-readable reasons. Users can also report suspicious posts with one click.

How we built it

VerifyX has a React-based frontend deployed on Vercel and a Node.js + Express backend deployed on Render. We built a pattern-based detection system using:

Keyword scoring

Fraud-phrase identification

Contact extraction (email/phone)

Heuristic risk analysis

JSON-based structured responses

The entire system is lightweight, fast, and works without login or heavy AI models to keep it accessible.

Challenges we ran into

Ensuring accurate scam detection without false positives

Handling inconsistent job text formats

Deploying backend and frontend with correct environment variables

Syncing auto-deploy pipelines between GitHub → Render → Vercel

Avoiding caching issues that delayed frontend updates

Despite these, we built a stable and reliable version in limited time.

Accomplishments that we're proud of

A fully functional live tool that detects scams instantly

Clean and intuitive UI with real-time results

Reliable backend scoring logic

A solution that genuinely helps students stay safe

End-to-end deployment and CI/CD setup

Fast performance on both mobile and desktop

What we learned

How scam patterns differ across job niches

Efficient regex + heuristic design for fraud analysis

Structuring user-friendly explanations for trust decisions

Managing full-stack deployments with Vercel and Render

Importance of clear UX for trust-based tools

What's next for VerifyX

Adding AI-based analysis for deeper fraud detection

Browser extension to verify LinkedIn/Internshala posts directly

Database of reported fraud numbers/keywords

Multi-language support

Real-time alerts for trending scam patterns

Public API for other platforms to integrate VerifyX

A trust score for companies based on user reports

Built With

• express.js
• github
• node.js
• react
• regex
• render
• sqlite
• vercel