AI Agents for Cybersecurity

This repository contains resources and materials for several courses by Omar Santos.

Repository Structure

The repository is structured with five comprehensive parts covering the spectrum from basic AI concepts to advanced agentic implementations:

• part1_basic_examples_no_rag/: Foundational examples covering chat models, embeddings, interactive chatbots, and integration with various model providers (OpenAI, Hugging Face, Ollama)
• part2_prompt_templates/: Advanced prompt engineering techniques, template systems, and structured prompting strategies for cybersecurity applications
• part3_prompt_chaining/: Sophisticated prompt chaining workflows using LangChain Expression Language (LCEL), including branching chains, parallel processing, and conditional logic
• part4_rag_examples/: Comprehensive Retrieval Augmented Generation implementations with vector databases, text splitting strategies, and metadata handling
• part5_agents_and_tools/: Advanced AI agents, tools integration, LangGraph workflows, agentic RAG, and Model Context Protocol (MCP) implementations

Comprehensive Learning Path

This repository provides a structured learning journey covering cutting-edge AI agent technologies and their applications in cybersecurity operations.

Part 1: Foundation - Basic AI Interactions

• Chat model fundamentals with OpenAI and alternative providers
• Embedding generation and vector operations
• Interactive chatbot development with Streamlit
• Ollama integration for local model deployment
• Multimodal document processing and image analysis
• Environment setup and API key management

Part 2: Prompt Engineering and Context Engineering Mastery

• Advanced prompt template design and optimization
• System message crafting for cybersecurity contexts
• Multi-variable prompt construction and placeholders
• Message history management and conversation flow
• Chain-of-Thought, Tree-of-Thought, and ReAct techniques
• Meta prompting and iterative refinement strategies

Part 3: Intelligent Prompt Chaining

• LangChain Expression Language (LCEL) fundamentals
• Sequential and parallel chain orchestration
• Conditional branching for dynamic decision-making
• Security incident analysis workflows
• Threat hunting automation with adaptive chains
• Multi-step reasoning for complex cybersecurity tasks

Part 4: Advanced RAG Implementations

• Vector database creation and management with Chroma
• Text splitting optimization for various document types
• Embedding model comparison (OpenAI vs. Hugging Face)
• Metadata integration and source tracking
• Web scraping and dynamic content ingestion
• Cost optimization strategies for embedding operations

Part 5: Next-Generation AI Agents & Tools

• Basic Agent Frameworks: ReAct agents with tool integration
• Advanced Agent Architectures: LangGraph-based workflows with state management
• Agentic RAG: Reasoning-based real-time data retrieval and generation
• Model Context Protocol (MCP): Standardized AI-to-system integration
• Multi-Agent Systems: Collaborative agent networks for complex tasks

Note: This will continue to be a living set of resources with updates and new content added regularly.

Contact Information

For any queries or further information, please contact:

Omar Santos

• X: @santosomar
• LinkedIn: /santosomar