RAG and AI Applications for Cybersecurity and Networking Professionals
Published by Pearson
A hands-on approach to RAG, Langchain, LangGraph, and LlamaIndex and AI applications
- Explore cutting-edge topics focusing on combining RAG, Langchain, LangGraph, and LlamaIndex specifically for cybersecurity and networking operations
- Get a hands-on approach with practical demonstrations and code for real-world implementation
- Learn ethical hacking insights and techniques with exclusive exploration of uncensored AI models for developing advanced exploits and enhancing offensive security strategies.
Get the introduction to cutting-edge AI topics such as Retrieval Augmented Generation (RAG), Langchain, LangGraph, and LlamaIndex. This 4-hour course will show you how to harness the power of Large Language Models (LLMs) for both offensive and defensive cybersecurity operations, as well as networking implementations. From enhancing threat detection to automating complex ethical hacking tasks, this course provides practical skills that are reshaping today’s cybersecurity and networking landscape.
RAG and AI Applications for Cybersecurity and Networking Professionals goes beyond theoretical concepts, offering hands-on experience with real-world step-by-step AI coding examples. Whether you're a red team operator looking to develop more sophisticated attacks, a blue team analyst seeking to bolster defenses, a security researcher exploring the frontiers of AI in cybersecurity or a networking professional in need of AI knowledge, this course provides the core basics and skills needed to stay ahead in today’s environments. You will learn about traditional RAG, RAG Fusion, and implementations and how to use solutions like LangChain, LlamaIndex, and vector databases including Chroma DB, pgvector, Pinecone, FAISS, and MongoDB Atlas Vector Search. We will also introduce AI agents and agentic frameworks such as LangGraph and others.
What you’ll learn and how you can apply it
- Master the foundations and practical applications of RAG, Langchain, LangGraph, and LlamaIndex
- Compare and contrast traditional RAG, RAG Fusion, and RAPTOR implementations for optimal information retrieval and processing
- Explore real-world case studies and hands-on demonstrations of AI-enhanced security and networking operations
- Discover how to implement RAG for dynamic information retrieval, re-ranking, and advanced automation in cybersecurity and networking scenarios
This live event is for you because...
- You want to learn about RAG and AI systems.
- You are a developer, data scientist, or engineer looking to build secure AI applications while considering privacy aspects.
- You are a cybersecurity or networking professional looking to integrate AI into your toolkit.
- You are a product manager, team leader, or executive looking to integrate retrieval augmented generation (RAG), agents, and other AI implementations within your organization.
Prerequisites
- Basic awareness of ML and AI implementations such as ChatGPT, GitHub Copilot, Claude, Llama, Mistral, and others.
- Familiarity with computer science concepts: Basic knowledge of data structures, algorithms, and computer systems will be beneficial in understanding the underlying mechanisms of AI and ML algorithms and their security implications.
- Curiosity and willingness to learn: A strong desire to learn about AI, ML, security, ethics, and privacy, and the ability to think critically about the implications of AI and ML technologies on society is crucial for making the most of the training.
Course Set-up
- You can follow along during the presentation with any Linux system with Python 3.x installed.
Recommended Preparation
- Attend: AI-Enabled Programming, Networking, and Cybersecurity by Omar Santos
- Read: Deep Learning Illustrated: A Visual, Interactive Guide to Artificial Intelligence by Jon Krohn, Grant Beyleveld, Aglaé Bassens
- Watch: The Complete Cybersecurity Bootcamp, 2nd Edition, by Omar Santos
- Watch: Introduction to Transformer Models for NLP: Using BERT, GPT, and More to Solve Modern Natural Language Processing Tasks by Sinan Ozdemir
Recommended Follow-up
- Attend: Securing AI Implementations by Omar Santos
- Watch: Red Team and Bug Bounty Conference by Omar Santos
- Watch: Deep Learning for Natural Language Processing, 2nd Edition by John Krohn
- Watch: The Art of Hacking (Video Collection) by Omar Santos
- Explore: Ethical Hacking Labs by Omar and Derek Santos
Schedule
The time frames are only estimates and may vary according to how the class is progressing.
Segment 1: Introduction to RAG in Cybersecurity (45 minutes)
- Course overview and objectives
- Understanding the LLM stack and relevancy for cybersecurity operations
- Embeddings and Embedding Models
- Indexing Techniques
- Vector Databases
- Chunking strategies
- RAG vs. Fine-tuning
- RAG, RAG Fusion, and RAPTOR
- Hands-on labs: Embeddings and basic inference implementations with OpenAI API and Claude API using cybersecurity data.
Q&A and Discussion (5 minutes)
Break (10 minutes)
Segment 2: Introducing LangChain, LangGraph, and LLamaIndex (45 minutes)
- Introducing LangChain
- LangChain vs. LlamaIndex
- Prompt templates and system prompts
- LangServe and LangSmith
- AI agent frameworks and LangGraph
- Hands-on Lab: Using LangChain and Prompt Templates for cybersecurity and network operations
Q&A and Discussion (5 minutes)
Break (10 minutes)
Segment 3: Prompt Chaining and Retrieval Augmented Generation Labs for Cybersecurity and Networking Professionals (45 minutes)
- Basic Chain Examples
- Branching Chains
- Parallel Chains
- Hands-on labs: Basic, Branching, and Parallel Chains
- Hands-on labs: Basic RAG, one-off-questions, metadata, text splitting, and web scraping for passive reconnaissance and open-source intelligence (OSINT)
Q&A and Discussion (5 minutes)
Break (10 minutes)
Segment 4: AI Agents and Agentic Frameworks (45 minutes)
- Introduction to AI agents and related frameworks
- Introducing LangGraph
- Surveying LangGraph Cloud
- Function calling and tool calling
- Hands-on lab: A basic agent using function and tool calling for ethical hacking
Q&A, Course Conclusion and Wrap-up (15 minutes)
- Review of Key Takeaways for implementing RAG in cybersecurity
- Closing Remarks
Your Instructor
Omar Santos
Omar Santos is a Distinguished Engineer at Cisco focusing on artificial intelligence (AI) security, research, incident response, and vulnerability disclosure. He is a board member of the OASIS Open standards organization and the founder of OpenEoX. Omar's collaborative efforts extend to numerous organizations, including the Forum of Incident Response and Security Teams (FIRST) and the Industry Consortium for Advancement of Security on the Internet (ICASI). Omar is the co-chair of the FIRST PSIRT Special Interest Group (SIG). Omar is the lead of the DEF CON Red Team Village and the chair of the Common Security Advisory Framework (CSAF) technical committee. Omar is the author of over 20 books, numerous video courses, and over 50 academic research papers. Omar is a renowned expert in ethical hacking, vulnerability research, incident response, and AI security. His dedication to cybersecurity has made a significant impact on technology standards, businesses, academic institutions, government agencies, and other entities striving to improve their cybersecurity programs.