Thesis Detección y mitigación de tecnologías en la sombra (Shadow IT) en infraestructuras de telecomunicaciones
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Date
2025
Authors
Journal Title
Journal ISSN
Volume Title
Program
Ingeniería Civil Telemática
Departament
Campus
Campus Santiago San Joaquín
Abstract
El avance de la digitalización y la conectividad ha traído consigo nuevos desafíos en el ámbito de la ciberseguridad, siendo uno de los más relevantes el fenómeno conocido como "Tecnologías en la Sombra"(Shadow IT). Este concepto se refiere al uso de dispositivos, software y servicios tecnológicos no autorizados o no registrados dentro de la infraestructura oficial de una organización, lo cual amplía considerablemente la superficie de ataque y dificulta la gestión de riesgos.
Este trabajo tiene como objetivo desarrollar una plataforma integral denominada Inventarium, diseñada para identificar, mapear y gestionar activos tecnológicos en un entorno de telecomunicaciones mediante técnicas avanzadas de reconocimiento, escaneo de vulnerabilidades y cálculo de riesgos basados en Inteligencia Artificial.
La metodología propuesta integra un conjunto de herramientas de búsqueda y exploración de servicios y protocolos de red que operan fuera del control oficial de la organización. Además, se implementa el algoritmo de aprendizaje no supervisado Isolation Forest para evaluar el riesgo de cada activo.
En la fase de evaluación, se revisaron 795 activos tecnológicos, con una duración total de 6 horas y 30 minutos (aproximadamente 2 activos por minuto). Como resultado, se descubrieron 171 activos no registrados en el inventario oficial, representando un 20 % del total analizado. De estos, se identificaron 10 activos operando en entornos no productivos, asociados a dominios de desarrollo y control de calidad. Asimismo, se detectaron 40 activos con malas configuraciones relacionadas con servicios inseguros de administración remota y bases de datos, entre otro. También se identificaron 9 activos desconocidos con vulnerabilidades críticas conocidas (CVE) con alto riesgo de explotación.
The advancement of digitalization and connectivity has brought new challenges in the field of cybersecurity, one of the most significant being the phenomenon known as Shadow IT. This concept refers to the use of unauthorized or unregistered devices, software, and technological services within an organization’s oficial infrastructure, which significantly expands the attack surface and complicates risk management. This work aims to develop a comprehensive platform called Inventarium, designed to identify, map, and manage technological assets in a telecommunications environment through advanced techniques of recognition, vulnerability scanning, and AI-based risk calculation. The proposed methodology integrates a set of tools for discovering and exploring network services and protocols operating outside the official control of the organization. In addition, the Isolation Forest unsupervised learning algorithm is implemented to assess the risk level of each asset. During the evaluation phase, 795 technological assets were reviewed over a period of 6 hours and 30 minutes (approximately 2 assets per minute). As a result, 171 previously unregistered assets were discovered, accounting for 20 % of the to tal analyzed. Among them, 10 assets were found operating in non-production environments, identified by domain indicators such as qa, test, dev, and -pp. Furthermore, 40 assets exhibited poor configurations related to insecure services such as FTP, SSH, Telnet, MySQL, PostgreSQL, and Oracle. In addition, 9 assets were found with critical known vulnerabilities (CVEs) with a high risk of exploitation.
The advancement of digitalization and connectivity has brought new challenges in the field of cybersecurity, one of the most significant being the phenomenon known as Shadow IT. This concept refers to the use of unauthorized or unregistered devices, software, and technological services within an organization’s oficial infrastructure, which significantly expands the attack surface and complicates risk management. This work aims to develop a comprehensive platform called Inventarium, designed to identify, map, and manage technological assets in a telecommunications environment through advanced techniques of recognition, vulnerability scanning, and AI-based risk calculation. The proposed methodology integrates a set of tools for discovering and exploring network services and protocols operating outside the official control of the organization. In addition, the Isolation Forest unsupervised learning algorithm is implemented to assess the risk level of each asset. During the evaluation phase, 795 technological assets were reviewed over a period of 6 hours and 30 minutes (approximately 2 assets per minute). As a result, 171 previously unregistered assets were discovered, accounting for 20 % of the to tal analyzed. Among them, 10 assets were found operating in non-production environments, identified by domain indicators such as qa, test, dev, and -pp. Furthermore, 40 assets exhibited poor configurations related to insecure services such as FTP, SSH, Telnet, MySQL, PostgreSQL, and Oracle. In addition, 9 assets were found with critical known vulnerabilities (CVEs) with a high risk of exploitation.
Description
Keywords
Ciberseguridad, Gestión de riesgos, Inventario
