AWS IR
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Python command line utility for incident response in AWS
A compilation of suggested tools for each component in a detection and response pipeline, along with real-world examples. The purpose is to create a reference hub for designing effective threat detection and response pipelines. Join us, explore the curated content, and contribute to this collaborative effort. Main Components of a Detection & Response Pipeline: - Detection-as-Code Pipeline - Data Pipeline - Detection and Correlation Engine - Response Orchestration and Automation - Investigation and Case Management - Real-world Examples - Additional Resources Detection-as-Code Pipeline Tool / Service Purpose: - GitHub: Detection content development - GitLab: Detection content development - Gitea: Detection content development - AWS CodeCommit: Detection content development - GitHub Actions: CI/CD pipeline - GitLab Runner: CI/CD pipeline - Drone: CI/CD pipeline - AWS CodePipeline: CI/CD pipeline Resources: Automating Detection-as-Code: An example reference that uses GitHub for detection content development, GitHub Actions for CI/CD, Elastic as SIEM, GitHub Issues for alert management, and Tines for alert and response handling. Practical Detection-as-Code: An exa
Python command line utility for incident response in AWS
Incident response platform for automating alert handling and incident response procedures.
Repository of templates for Ayehu's workflows with the ability to design, execute, and automate IT and business processes.
AWS Community repository of custom Config rules with instructions for leveraging and developing AWS Config Rules.
Open-source security automation platform for automating security alerts and building AI-assisted workflows.
A multi-platform open source tool for triaging suspect systems and hunting for Indicators of Compromise (IOCs) across thousands of endpoints.