International Journal of Computer Science and Technology

International Journal of Computer Science and Technology | Vol. 3, No. 12, December 2022 | pp. 1–8

DOI: 10.46882/2022/IJCST/000215

Article Type: Original Research Paper

Title: Automated Microservice Vulnerability Assessments via Contextual Resource Consumption Profiling

Names of Authors: Klaus Meyer¹, Rachel Green²

Authors’ Affiliations: ¹Institute for Software Systems Security, Munich Technical University, Munich, Germany; ²DevSecOps Research Center, CloudScale Innovations, Austin, USA

Abstract: Monolithic software applications are rapidly transitioning toward cloud-native microservice architectures to achieve higher scalability and deployment flexibility. However, tracking anomalies across hundreds of independent containers introduces significant security and operational complexity. This paper presents an automated security validation framework designed to identify microservice vulnerabilities through non-intrusive container profiling. The system tracks low-level kernel activities, specifically counting system calls alongside memory allocations and CPU usage patterns. It creates a dynamic behavior baseline using an isolation forest algorithm to identify anomalous infrastructure patterns. We tested the tracking mechanism across a continuous integration environment running 80 distinct service modules. The profiling framework successfully identified container escape activities and resource-exhaustion exploits with a 95.4% success rate. The tracking agent operates outside the main application container, maintaining a low resource footprint under 1.8% CPU overhead. This setup ensures continuous software vulnerability assessments without degrading application performance.

Keywords: Microservices, Cloud-Native Security, Container Profiling, System Call Analysis, Automated Detection, DevOps

Manuscript Timeline: Received: May 29, 2022; Revised: July 05, 2022; Accepted: July 29, 2022; Published: December 14, 2022

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