PhishLens AI

Inspiration:

Phishing attacks are becoming increasingly sophisticated, using fake websites, emails, QR codes, and screenshots that look like legitimate content. We were inspired to create a solution that can detect these threats and explain them clearly to users.

What it does:

PhishLens AI is an AI-powered multimodal cybersecurity system that detects phishing across URLs, emails, QR codes, and screenshots. It analyzes suspicious content, generates a risk score, identifies potential threats, and explains the reason for the warning in simple language.

How we built it:

We combine machine learning, natural language processing, URL analysis, QR-code detection, and image analysis to identify phishing patterns. The system processes the submitted content through different detection modules and combines the results to generate a final security assessment.

Challenges we faced:

One of the main challenges was detecting different types of phishing attacks while minimizing false positives. Another challenge was making the system understandable to non-technical users by providing clear explanations instead of only showing a prediction.

What we learned:

Through this project, we learned how artificial intelligence can be applied to real-world cybersecurity problems. We also learned how multiple AI techniques can work together and how explainable AI can make security tools more useful and trustworthy.

Future scope:

In the future, PhishLens AI can be extended with browser integration, real-time phishing protection, multilingual threat explanations, continuous learning from new phishing patterns, and mobile support.