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πŸ” CyberLens

CyberLens is a modern desktop cybersecurity application designed to scan URLs and files for potential security threats. The project focuses on detecting malicious URLs (phishing, malware domains) and identifying suspicious files using hash-based analysis.

CyberLens is built primarily for educational and personal cybersecurity use and demonstrates practical implementation of secure coding, networking, and malware detection concepts.

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✨ Features

  • Intuitive graphical user interface built with Qt Widgets
  • URL analysis and threat detection
  • File scanning using cryptographic hash computation
  • Scan history tracking and management
  • Modular architecture for easy feature extension
  • Lightweight and fast desktop application

πŸ“Έ Screenshots

Main Application Window
Main Application Window

File Scanning Example
File Scanning Example

URL Scanning Example
URL Scanning Example

Scan History View
Scan History View

Report Generation / Results
Report Generation / Results

Network Checker Interface
Network Checker Interface

πŸ› οΈ Tech Stack

  • Programming Language: C++ (C++17 or later)
  • Framework: Qt 6 (Widgets & Network modules)
  • Build System: CMake
  • Platform: Cross-platform (Windows / Linux)

🎯 Learning Outcomes

Practical experience with cybersecurity concepts

Secure coding practices in C++

URL threat analysis techniques

File hashing and integrity checking

Desktop application development using Qt

πŸš€ Future Enhancements

Integration with online threat intelligence APIs

PDF/CSV report export

Real-time URL monitoring

Improved malware detection logic

🎯 Learning Outcomes

Practical experience with cybersecurity concepts

Secure coding practices in C++

URL threat analysis techniques

File hashing and integrity checking

Desktop application development using Qt

πŸš€ Future Enhancements

Integration with online threat intelligence APIs

PDF/CSV report export

Real-time URL monitoring

Improved malware detection logic

πŸ‘€ Author

Muhammad Jamshed

Cybersecurity Student

GitHub:https://github.com/JAMSHEDKHOSA57

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