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

Vasilios Koutsokostas, Nikolaos Lykousas, Theodoros Apostolopoulos, Gabriele Orazi, Amrita Ghosal, Fran Casino, Mauro Conti, Constantinos Patsakis*

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

7 Citations (Scopus)

Abstract

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.

Original languageEnglish
Article number102582
JournalComputers and Security
Volume114
DOIs
Publication statusPublished - 2022
Externally publishedYes

Keywords

  • LOLBAS
  • Macro malware
  • Malware
  • Office documents
  • Powershell

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