RAG for Cybersecurity: Use Cases and Implementation

Course details

This course provides an in-depth exploration of how retrieval-augmented generation (RAG) technology enhances cybersecurity. Gain a thorough understanding of RAG’s core components, including how it integrates with large language models to enhance data retrieval and analysis. The course focuses on practical use cases such as mapping cyber security logs and alerts to MITRE ATT&CK techniques, performing real-time gap analysis for governance, risk, and compliance (GRC) Join instructor Brennan Lodge to gain the knowledge and tools to implement RAG solutions, improving both proactive defense strategies and compliance processes in their organizations. This course is ideal for cybersecurity professionals, GRC experts, and data scientists seeking to leverage AI-driven solutions for enhanced security operations.

Learning objectives
Analyze the core components of retrieval-augmented generation (RAG) technology and evaluate its integration with large language models for enhancing cybersecurity analysis.
Design a RAG-based system to map threat intelligence data to specific MITRE ATT&CK technique while facilitating proactive defense strategies.
Implement a real-time gap analysis solution for governance, risk, and compliance (GRC) using RAG technology to compare internal policies with regulatory frameworks such as GDPR and NIST.

Concepts

Introduction

Welcome to RAG for Cyber Security
What to know before getting started

Understanding RAG

What is Retrieval-Augmented Generation
Core components of RAG systems

RAG in action

Introduce RAGs capabilities for risk and cyber security
Uploading MITRE ATT&CK techniques to a vector database
Adding the LLM
Case Study - MITRE ATT&CK and RAG in action

RAG for GRC

Using RAG for GRC automation
Enhancing regulatory compliance with RAG
Gap analysis using RAG - A deep dive

Advanced RAG Application

Maintaining and scaling RAG systems
Course summary

Conclusion

Course conclusion