A Behavioral Analysis of Ransomware in Active Directory: A Case Study of BlackMatter, Conti, LockBit, and Midnight

Ransomware continues to be a pervasive cyber-security threat, particularly in enterprise environments that leverage Active Directory (AD) for centralized management. This study focuses on analyzing ransomware behavior by ex-amining Windows Event Logs generated during attacks from four prominent ransomware families: “BlackMatter,” “Conti,” “LockBit,” and “Midnight”11The “Midnight” samples included in this study were labeled as such in the dataset [1]–[3]. Although not a commonly recognized ransomware family in public reports, they demonstrate typical ransomware behaviors, including encryption and system compromise.. We conducted experiments on 20 ransomware samples (5 per family) within a controlled Proxmox-based virtual AD environment to simulate realistic enterprise conditions. Our analysis applies n-gram sequence modeling and behavioral feature extraction to uncover distinctive event patterns and attack paths. The findings reveal consistent, family-specific behavioral sequences, such as repetitive service control and credential validation events, that are indicative of ransomware activity. In addition to offering insight into the operational methods of ransomware, we lay the groundwork for automated behavior-based detection mechanisms suited for enterprise AD environments.

Publication Details

Journal
Maryland Shared Open Access Repository (USMAI Consortium)
Published
2025-06-02
DOI
https://doi.org/10.13016/m2d6gm-vnkv
Primary Topic
Advanced Malware Detection Techniques
Type
article
Field-Weighted Citation Impact
0.00
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article

A Behavioral Analysis of Ransomware in Active Directory: A Case Study of BlackMatter, Conti, LockBit, and Midnight

Maryland Shared Open Access Repository (USMAI Consortium)
Advanced Malware Detection Techniques
article

A Behavioral Analysis of Ransomware in Active Directory: A Case Study of BlackMatter, Conti, LockBit, and Midnight

article en

Abstract

Ransomware continues to be a pervasive cyber-security threat, particularly in enterprise environments that leverage Active Directory (AD) for centralized management. This study focuses on analyzing ransomware behavior by ex-amining Windows Event Logs generated during attacks from four prominent ransomware families: “BlackMatter,” “Conti,” “LockBit,” and “Midnight”11The “Midnight” samples included in this study were labeled as such in the dataset [1]–[3]. Although not a commonly recognized ransomware family in public reports, they demonstrate typical ransomware behaviors, including encryption and system compromise.. We conducted experiments on 20 ransomware samples (5 per family) within a controlled Proxmox-based virtual AD environment to simulate realistic enterprise conditions. Our analysis applies n-gram sequence modeling and behavioral feature extraction to uncover distinctive event patterns and attack paths. The findings reveal consistent, family-specific behavioral sequences, such as repetitive service control and credential validation events, that are indicative of ransomware activity. In addition to offering insight into the operational methods of ransomware, we lay the groundwork for automated behavior-based detection mechanisms suited for enterprise AD environments.

Maryland Shared Open Access Repository (USMAI Consortium)
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Openalex Percentile: Top 50%
Advanced Malware Detection Techniques
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