Diseño de una herramienta inteligente para el análisis forense de configuraciones en redes de telecomunicaciones

Abstract

In the operation of modern telecommunications networks, equipment configuration management is a critical process. Various studies indicate that a high percentage of service interruptions and network failures originate from human errors during the modification of these configurations. These errors, commonly referred to as “misconfigurations,” not only affect service availability but can also introduce security vulnerabilities.

This industrial challenge becomes particularly critical in the context of the communications company, which operates the most extensive fiber optic network in the country. Given the scale of this infrastructure, efficient configuration management is vital. However, the company had not implemented an automated system to facilitate forensic analysis tasks on network configurations, creating a bottleneck for critical areas such as the Network Operations Center (NOC) and the technical audit team.

In both scenarios, the process depended on the manual review of text files in a Git repository, which resulted in an increase in the Mean Time to Repair (MTTR), impacting Service Level Agreements (SLAs) and making audit activities more difficult. This project addresses this technological gap through the design and implementation of a functional prototype that, using Python and regular expressions, automates the extraction and comparison of network configurations from a GitLab repository to streamline forensic analysis.