Requirements

• Basic understanding of Large Language Models (LLMs): You should know what an LLM is and how basic prompting works. (No complex math
• data science
• or machine learning background is required!)
• Foundational Python skills: You should be comfortable reading and writing basic Python code to follow along with the custom defense scripts and API integrations
• Basic Command Line familiarity: We will be using the terminal to run simple cURL commands
• spin up Vector DBs using Docker
• and execute automated red teaming tools
• A computer with admin rights: You will need a Windows
• Mac
• or Linux machine with the ability to install standard free software (Python
• Docker
• and Node.js)
• No prior hacking experience needed: You do NOT need to be a penetration tester or cybersecurity expert. I will teach you the offensive AI mindset step-by-step from the ground up

Description

Who this course is for:

• AI & Machine Learning Engineers: You are actively building Large Language Model (LLM) applications
• Retrieval-Augmented Generation (RAG) pipelines
• or autonomous AI agents
• and you want to ensure your architectures are secure from data poisoning and prompt injection before shipping to production.
• Cybersecurity Professionals & Red Teamers: You are a penetration tester
• security analyst
• or ethical hacker looking to rapidly upskill into the high-demand field of Offensive AI Security. You want to learn how to actively exploit Vector Databases and bypass semantic LLM filters.
• AppSec Engineers & DevSecOps: You are responsible for securing corporate applications and need to understand how to align your AI features with the OWASP LLM Top 10
• as well as how to integrate automated AI vulnerability scanners (like Promptfoo) into your CI/CD pipelines
• Software Architects & Tech Leads: You are designing enterprise-grade systems and need to deeply understand the structural risks
• trust boundaries
• and liability issues associated with giving AI access to internal corporate data and APIs