Wazuh + AWS Bedrock: RAG with Titan Embeddings (Part 3)

 Posted on September 5, 2026  (Last modified on September 6, 2026)  |  33 minutes  |  6924 words  |  pyToshka  • Other languages: Русский

Introduction

Ask the chat agent from Part 1 what the team runbook prescribes for an SSH brute force against web-server-01, or ask the MCP sidecar from Part 2 whether a file hash appeared in a threat intelligence feed last month, and the answer is whatever Claude remembers about the world in general. Both tools query alerts well. Neither of them can read a document, and the runbook, the manual and the feed never reach the model.

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devsecops  wazuh  security  aws  docker  llm  ai  machine learning  cybersecurity  automation  threat intelligence  security operations  cloud security  mcp  rag  embeddings  opensearch  mitre  misp 

RAG for Wazuh Documentation: Step-by-Step Guide, Part 2

 Posted on March 5, 2025  (Last modified on March 23, 2026)  |  5 minutes  |  1009 words  |  pyToshka  • Other languages: Русский

Related Reading:

Prerequisites and Environment Setup

For local RAG development, ensure you have the following requirements:

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devsecops  wazuh  security  devops  llm  LLMs for documentation  ollama  machine learning  cybersecurity  RAG  Retrieval-Augmented Generation  ai 

RAG for Wazuh Documentation: Step-by-Step Guide, Part 1

 Posted on March 2, 2025  (Last modified on February 2, 2026)  |  5 minutes  |  1053 words  |  pyToshka  • Other languages: Русский

Introduction to RAG

Retrieval-Augmented Generation (RAG) is a method that allows the use of information from various sources to generate more accurate and useful responses to questions.

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devsecops  wazuh  security  devops  llm  LLMs for documentation  ollama  machine learning  cybersecurity  RAG  Retrieval-Augmented Generation  NLP for documentation  RAG for Wazuh  ai