# AI Red Team Methodology

> Master advanced AI red teaming methodologies, from scoping and reconnaissance to exploiting agentic systems and reporting findings securely.

Canonical: https://codelivly.com/learning-paths/ai-red-team-methodology
Last updated: 2026-10-14

| | |
|---|---|
| Level | Advanced |
| Category | Cybersecurity |
| Rooms | 4 |
| Lessons | 8 |
| Estimated time | 2 h |

This advanced learning path provides a comprehensive, end-to-end methodology for conducting professional AI red team engagements. You will learn how to properly scope AI systems, perform advanced reconnaissance on LLM architectures and agent frameworks, execute multi-stage agentic exploits, and document findings using industry-standard reporting frameworks tailored specifically for AI security risks.

## Rooms in this path

1. [AI Red Team vs Traditional Pentest](https://codelivly.com/rooms/ai-red-team-vs-traditional-pentest) - Understand the fundamental differences between traditional penetration testing and AI red teaming, including the unique…
2. [Threat Modeling an AI Application](https://codelivly.com/rooms/threat-modeling-an-ai-application) - Learn to systematically identify, quantify, and mitigate AI-specific risks using structured threat modeling frameworks…
3. [Scoping an AI Red Team Engagement](https://codelivly.com/rooms/scoping-an-ai-red-team-engagement) - Learn how to properly define the boundaries, objectives, rules of engagement, and success metrics for an AI-specific…
4. [Building a Structured Attack Scenario Library](https://codelivly.com/rooms/building-a-structured-attack-scenario-library) - Learn to develop, categorize, and maintain a comprehensive library of AI-specific attack scenarios, from prompt…

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- [Career path: AI Red Teaming and Adversarial ML](https://codelivly.com/career-paths/ai-red-teaming-and-adversarial-ml)
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