A Practical Framework for Simulating and Investigating Multi-stage Cyber Intrusions through Log Correlation

Abstract

Defensive training techniques must advance in tandem with the growing complexity of cyberthreats. In order to give practical experience in investigating multi-stage network intrusions, this paper describes the setup and functioning of a simulated Security Operations Centre (SOC) environment. This project’s main component is a Python-built log correlation engine that handles and examines data gathered from several Linux servers. The system reconstructs the attacker’s actions by ingesting raw log files, normalising them into a structured format, and performing contextual and temporal analysis. A comprehensive attack timeline, a standardised set of indicators of compromise (IOCs), and visual dashboards that chart the progression of the security incident are some of the main outputs of the process. Students and aspiring SOC analysts can hone critical incident response skills in a controlled, realistic environment with this framework’s academically demanding, reasonably priced, and fully reproducible lab setup.