Scoring Azure permissions with metric spaces

Fuente: arXiv
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Auteur principal: Parisel, Christophe
Format: Preprint
Publié: 2025
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author Parisel, Christophe
author_facet Parisel, Christophe
contents In this work, we introduce two complementary metrics for quantifying and scoring privilege risk in Microsoft Azure. In the Control Plane, we define the WAR distance, a superincreasing distance over Write, Action, and Read control permissions, which yields a total ordering of principals by their configuration power. In the Data Plane, we present a blast radius distance for measuring the maximum breadth of data exfiltration and forgery, leveraging the natural ultrametry of Azure Tenants clustering hierarchy Together, these metrics offer a unified framework for proactive IAM analysis, ranking, lifecycle monitoring, and least privilege enforcement.
format Preprint
id arxiv_https___arxiv_org_abs_2504_13747
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Scoring Azure permissions with metric spaces
Parisel, Christophe
Cryptography and Security
In this work, we introduce two complementary metrics for quantifying and scoring privilege risk in Microsoft Azure. In the Control Plane, we define the WAR distance, a superincreasing distance over Write, Action, and Read control permissions, which yields a total ordering of principals by their configuration power. In the Data Plane, we present a blast radius distance for measuring the maximum breadth of data exfiltration and forgery, leveraging the natural ultrametry of Azure Tenants clustering hierarchy Together, these metrics offer a unified framework for proactive IAM analysis, ranking, lifecycle monitoring, and least privilege enforcement.
title Scoring Azure permissions with metric spaces
topic Cryptography and Security
url https://arxiv.org/abs/2504.13747