Towards a Security Stress-Test for Cloud Configurations

TL;DR

This paper introduces a graph-based method to model and analyze cloud configurations, aiming to assist administrators in identifying safer setups and understanding security implications through scenario analysis.

Contribution

It proposes a novel knowledge graph approach to model cloud security objects and vulnerabilities, enabling safer configuration suggestions and scalable analysis.

Findings

Initial validation shows effectiveness in vulnerability analysis.

Supports scenario-based security assessments.

Scales to large cloud deployments.

Abstract

Securing cloud configurations is an elusive task, which is left up to system administrators who have to base their decisions on ``trial and error'' experimentations or by observing good practices (e.g., CIS Benchmarks). We propose a knowledge, AND/OR, graphs approach to model cloud deployment security objects and vulnerabilities. In this way, we can capture relationships between configurations, permissions (e.g., CAP\_SYS\_ADMIN), and security profiles (e.g., AppArmor and SecComp), as first-class citizens. Such an approach allows us to suggest alternative and safer configurations, support administrators in the study of what-if scenarios, and scale the analysis to large scale deployments. We present an initial validation and illustrate the approach with three real vulnerabilities from known sources.