Organizations are increasingly using generative AI, machine learning, and autonomous AI agents. This leads to enormous innovation, but also to a rapidly growing attack surface that traditional security and pentesting methods are simply not designed for. The Advanced AI Red Teaming (AI-300) OSAI training is a unique, advanced AI cybersecurity training from OffSec (the organization behind, among others, OSCP) where you learn how to identify, investigate, and actively exploit vulnerabilities in these AI systems from an offensive perspective. 

With the rise of AI, not only technologies are changing, but also the risks. Models, data flows, vector databases, agents, and orchestration frameworks all bring their own vulnerabilities. And this is precisely where the focus of AI-300 lies: understanding how AI systems are truly attacked and how attackers think and act in such environments.

You will learn to adopt a true adversary mindset and combine it with proven offensive security techniques. You will specifically work with AI applications such as LLMs, deep learning models, and AI-driven infrastructures. How do you manipulate model behavior? How do you discover weaknesses in an AI pipeline? 

Advanced Red Teaming for AI Environments is a comprehensive, hands-on training where you learn how to actually attack modern AI systems. As organizations increasingly integrate LLMs, RAG pipelines, agents, and tool-calling frameworks into critical processes, it becomes essential to understand where these components fail and how they can be exploited. In this training, you will work with a structured and repeatable approach, based on frameworks such as MITRE ATLAS, the OWASP Top 10 for LLMs, and NVIDIA's AI Kill Chain. This way, you will learn step by step how to set up and execute complete AI attacks.

You will start by mapping the AI attack surface, analyzing model behavior, and conducting explorations on infrastructures where AI is integrated. Then you will get hands-on experience in practical labs. You will practice, among other things, prompt injection, manipulating RAG processes, data poisoning, influencing agents, abusing toolchains, and attacks on the supply chain. Attacks on protocols such as MCP and orchestration within multi-agent environments will also be covered. You will gradually develop the skills to identify vulnerabilities, simulate attacks, and analyze their impact within complete AI ecosystems. You will learn to approach AI systems as if you were an attacker, so you better understand where the real risks lie and how to help organizations defend against them.

Additionally, the emphasis is on stealth and OPSEC: how do you stay under the radar as an attacker? You will learn how to bypass AI-specific security measures and how attackers move from a compromised AI component towards broader enterprise environments. You will not only learn the theory but especially through practice. All topics are supported with realistic hands-on labs that simulate enterprise environments where AI systems are integrated with traditional IT and cloud infrastructures, allowing you to directly apply the techniques in professional red team scenarios. Think of scenarios with multi-agent systems, vector databases, and AI orchestration frameworks.

The training concludes with a capstone project, in which you perform a complete end-to-end AI attack on a realistic multi-agent enterprise environment. Here, you will bring together everything you have learned in one complete red team engagement.