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Invoice #31415 attached: Automated analysis of malicious Microsoft Office documents

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journal contribution
posted on 2022-02-23, 14:27 authored by Vasilios Koutsokostas, Nikolaos Lykousas, Theodoros Apostolopoulos, Gabriele Orazi, Amrita GhosalAmrita Ghosal, Fran Casino, Mauro Conti, Constantinos Patsakis
Microsoft Office may be by far the most widely used suite for processing documents, spreadsheets, and presentations. Due to its popularity, it is continuously utilised to carry out malicious campaigns. Threat actors, exploiting the platform’s dynamic features, use it to launch their attacks and penetrate millions of hosts in their campaigns. This work explores the modern landscape of malicious Microsoft Office documents, exposing the means that malware authors use. We leverage a taxonomy of the tools used to weaponise Microsoft Office documents and explore the modus operandi of malicious actors. Moreover, we generated and publicly shared a specially crafted dataset, which relies on incorporating benign and malicious documents containing many dynamic features such as VBA macros and DDE. The latter is crucial for a fair and realistic analysis, an open issue in the current state of the art. This allows us to draw safe conclusions on the malicious features and behaviour. More precisely, we extract the necessary features with an automated analysis pipeline to efficiently and accurately classify a document as benign or malicious using machine learning with an F1 score above 0.98, outperforming the current state of the art detection algorithms.

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ASW SEARCH PLANNING

United States Department of the Navy

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History

Publication

Computers and Security;114, 102582

Publisher

Elsevier

Note

peer-reviewed

Other Funding information

European Union (EU), Horizon 2020, Government of Catalonia

Language

English

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