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Applying Neural Topic Modeling to Detect Anomalous Permission Requests in Microsoft 365 Applications.
Rel. Marco Mellia, Nikhil Jha, Alberto Verna. Politecnico di Torino, Corso di laurea magistrale in Cybersecurity, 2025
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Abstract
Microsoft 365 is a comprehensive suite of productivity tools that offers users a variety of services over the cloud. A significant advantage of Microsoft 365 is its ability to generate private cloud environments for organizations, called tenants or directories, where users have their own identities, can access their data, and collaborate with each other in a controlled environment. Applications are a key component for improving productivity and enhancing collaboration within tenants. They can request a set of permissions theoretically required to perform their intended functionalities. These permissions allow the applications to get read or write access to various tenant’s resources such as user information, calendars, files, mailbox, and more.
Consequently, the misuse of these permissions may represent a potential entry point for attackers who may compromise an existing application with excessive permissions or develop a malicious application to access sensitive data or perform unauthorized actions
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