LLM Pentesting: Mastering Security Testing for AI Models

Complete Guide to LLM Security Testing

What You Will Learn:

Definition and significance of LLMs in modern AI

Overview of LLM architecture and components

Identifying security risks associated with LLMs

Importance of data security, model security, and infrastructure security

Comprehensive analysis of the OWASP Top 10 vulnerabilities for LLMs

Techniques for prompt injection attacks and their implications

Identifying and exploiting API vulnerabilities in LLMs

Understanding excessive agency exploitation in LLM systems

Recognizing and addressing insecure output handling in AI models

Practical demonstrations of LLM hacking methods

Interactive exercises including a Random LLM Hacking Game for applied learning

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Generative AI for Cybersecurity

Generative AI’s growing impact makes mastering its architecture and tech stacks essential. This course offers hands-on cybersecurity applications, covering Python, Google Colab, PyTorch, and advanced LLM fine-tuning  to build practical, high-level Generative AI expertise. 
[[2999 | currency]] [[9999 | currency]]

Hands-on Zero Day Exploit

This course tackles zero-day attacks by teaching vulnerability research, exploitation, fuzzing, buffer overflows, stealth reconnaissance, and Tor-over-VPN scanning. Gain hands-on skills to effectively detect, prevent, and protect software from malicious hackers. 
[[2999 | currency]] [[5999 | currency]]

Practical Bug Bounty Hunting for Hackers and Pentesters

To counter growing cyber threats, companies use Bug Bounty programs for crowdsourced vulnerability discovery. This course covers target  identification, exploit development, reporting, and the essential skills needed to succeed in the Bug Bounty industry. 
[[2999 | currency]] [[5999 | currency]]

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