As microservice-based architectures are increasingly adopted, microservices security has become a crucial aspect to consider for IT businesses. Starting from a set of “security smells” for microservice applications that were recently proposed in the literature, we enable the automatic detection of such smells in microservice applications deployed with Kubernetes. We first introduce possible analysis techniques to automatically detect security smells in Kubernetes-deployed microservices. We then demonstrate the practical applicability of the proposed techniques by introducing KubeHound, an extensible prototype tool for automatically detecting security smells in microservice applications, and which already features a selected subset of the discussed analyses. We finally show that KubeHound can effectively detect instances of security smells in microservice applications by means of controlled experiments and by applying it to existing, third-party applications.

KubeHound: Detecting Microservices’ Security Smells in Kubernetes Deployments

Dell’Immagine, Giorgio
Primo
;
Soldani, Jacopo
Secondo
;
Brogi, Antonio
Ultimo
2023-01-01

Abstract

As microservice-based architectures are increasingly adopted, microservices security has become a crucial aspect to consider for IT businesses. Starting from a set of “security smells” for microservice applications that were recently proposed in the literature, we enable the automatic detection of such smells in microservice applications deployed with Kubernetes. We first introduce possible analysis techniques to automatically detect security smells in Kubernetes-deployed microservices. We then demonstrate the practical applicability of the proposed techniques by introducing KubeHound, an extensible prototype tool for automatically detecting security smells in microservice applications, and which already features a selected subset of the discussed analyses. We finally show that KubeHound can effectively detect instances of security smells in microservice applications by means of controlled experiments and by applying it to existing, third-party applications.
2023
Dell’Immagine, Giorgio; Soldani, Jacopo; Brogi, Antonio
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11568/1188068
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