About This Project

Academic research project on phishing detection using rule-based analysis

Academic Project Notice

PhishGuard is a college cybersecurity project developed by Kuldeep Tiwari and Aman Tiwari as part of their academic curriculum. This platform demonstrates the practical application of heuristic detection algorithms and threat intelligence APIs for identifying phishing websites. It is intended for educational and research purposes only.

Project Team

Kuldeep Tiwari

Lead Developer

Lead developer responsible for system architecture, backend logic, API integration, and heuristic detection algorithms. Focused on creating a scalable and efficient phishing detection system using Flask and MongoDB.

Aman Tiwari

Project Partner

Project partner contributing to frontend development, user interface design, security awareness content, and testing. Collaborated on research and documentation for the detection methodology and best practices.

System Architecture

PhishGuard uses a rule-based detection system analyzing multiple threat indicators.

Frontend Interface

Built with HTML5, CSS3, and JavaScript, providing a responsive and intuitive user experience across mobile and desktop devices.

Backend Logic

Powered by Python (Flask), implementing 16+ heuristic detection rules including typosquatting detection, domain age verification, SSL certificate analysis, and behavioral pattern recognition.

Database Layer

MongoDB Atlas for persistent storage of scan history, domain reputation tracking, and community reports, ensuring data availability and security.

Detection Engine

Integrates Google Safe Browsing API, VirusTotal API, and WhoisXML API to fetch real-time threat intelligence on domains, SSL certificates, and security reputation.

Important Disclaimer

This is an Educational Project - Not a Commercial Security Product

  • Academic Purpose: PhishGuard was created as a college project to demonstrate cybersecurity concepts and is not intended for commercial use.
  • Rule-Based Detection: This system uses heuristic analysis and may produce false positives or miss sophisticated attacks.
  • No Liability: The developers assume no liability for any damages or security incidents. Always verify suspicious links independently.
  • Consult Professionals: For critical security decisions, always consult professional cybersecurity services and IT experts.
  • External APIs: This tool relies on third-party APIs which may have their own limitations and terms of service.

By using PhishGuard, you acknowledge that this is a learning project and agree to use it responsibly for educational purposes only. The creators are students and this project is part of their academic coursework.

Contact Information

Connect with the project team

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Acknowledgments

This project was made possible by the following tools and resources: