A data-driven approach to prioritize MITRE ATT&CK techniques for active directory adversary emulation

Abstract

Abstract Advanced Persistent Threats (APTs) continue to evolve, employing sophisticated and evasive techniques that pose significant challenges to modern defense mechanisms, particularly in Active Directory (AD) environments. Adversary emulation serves as a proactive security strategy, enabling organizations to replicate real-world adversary behaviors to assess and enhance detection, response, and mitigation capabilities. However, existing frameworks often lack a structured approach to prioritizing techniques based on impact, feasibility, and security control gaps, leading to suboptimal resource allocation. This study proposes a Multi-Criteria Decision-Making (MCDM) approach that integrates Operational Threat Intelligence (OTI) and structured datasets from MITRE ATT&CK to systematically prioritize adversary techniques. The methodology evaluates techniques across three key dimensions: Active Directory Impact, Threat Score, and Security Control Gap, employing entropy-based weighting to ensure an objective and data-driven prioritization process. To validate the proposed framework, a real-world case study based on the APT3 threat group is presented, demonstrating the applicability and effectiveness of the prioritization strategy in aligning adversary emulation with real-world attack scenarios. By focusing on high-impact and difficult-to-detect techniques, this framework enhances the effectiveness of adversary emulation and strengthens security postures in AD environments.