arXiv Computation and Language By Mostafa Anouar Ghorab, Mohamed Aymen Saied

Towards Secure Cloud-Native Computing: Unveiling Kubernetes Misconfigurations with Large Language Models

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The paper investigates how Large Language Models can help detect misconfigurations in Kubernetes, the dominant platform for orchestrating containerized applications in cloud‑native environments. It presents a taxonomy of common misconfiguration types, evaluates existing detection tools, and analyzes which Kubernetes objects are most vulnerable and how severe the issues can be. The study demonstrates that advanced machine learning, particularly LLMs, can offer new insights and improve the effectiveness of misconfiguration detection methods.

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