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A collection of AI-powered tools for phishing detection, adversarial machine learning, and cybersecurity research. Includes Streamlit/Flask apps, attack simulations, LoRA fine-tuning, and secure model evaluation for red teaming and defense.

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WhiteHat

Welcome to the WhiteHat repository!

This project is a collection of resources, guides, and research in cybersecurity and artificial intelligence. The materials are organized into different sections to help students, professionals, and enthusiasts expand their knowledge and practical skills in various areas of cybersecurity.

Repository Structure

  • AI Projects
    Experiments and practical projects applying artificial intelligence and machine learning to cybersecurity problems, such as:
    • Adversarial machine learning (e.g., data poisoning, evasion attacks)
    • Automated malware detection
    • Security analytics using deep learning
  • Research
    Open source projects, articles, and presentations from my cybersecurity research.
  • Information Gathering
    • Fingerprinting techniques and tools
    • Automated tools for reconnaissance
  • My Courses
  • Networks and lab
  • Club Hack1ng
    • Workshops, tutorials, and learning experiences
    • Social engineering and web security
    • Programming with Python

Explore each folder for hands-on scripts, educational content, and research insights. All materials are intended for ethical and educational use.

Highlights

Information Gathering

Explore techniques for gathering information about a target, including manual and automated tools. Learn about documentation tools, network reconnaissance, and how to interpret data from HTTP requests and cookies. Example tools include:

  • Netcat
  • Telnet
  • Nmap
  • WhatWeb
  • Httpprint
  • BlindElephant

Club Hack1ng

A space for sharing educational activities and experiences from the Hack1ng Club at Universidad Icesi. Topics include:

  • Social Engineering tools and concepts
  • Web security practices
  • Python programming for cybersecurity
  • Workshop materials and practical exercises

Disclaimer

This repository is intended for educational purposes only. All information and tools provided here are intended for responsible and ethical use.

References

  • Seitz, Justin. Black Hat Python: Python Programming for Hackers and Pentesters. No Starch Press, 2014.
  • Ramos, Antonio., Barberto, C. Marugan, D., & Gonzáles I. hacking con ingeniería social técnicas para hackear humanos
  • Hadnagy, C. (2014). Unmasking the social engineer: The human element of security. John Wiley & Sons.
  • Ramos, Antonio., Barberto, M. Rubén., G. Ángel., & Gonzáles I. Hacking y seguridad de páginas web
  • Lutz, M. (2013). Learning Python: Powerful Object-Oriented Programming. " O'Reilly Media, Inc.".
  • O'Connor, T. J. (2012). Violent Python: a cookbook for hackers, forensic analysts, penetration testers and security engineers. Newnes.

Feel free to explore the subdirectories for more detailed guides and resources!

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A collection of AI-powered tools for phishing detection, adversarial machine learning, and cybersecurity research. Includes Streamlit/Flask apps, attack simulations, LoRA fine-tuning, and secure model evaluation for red teaming and defense.

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