Malware remains a critical challenge in the broader context of Cyber Threat Intelligence (CTI), and an adversary-based approach to threat modeling offers a valuable framework for understanding and responding to these threats. Julian Cohen’s framework, which maps adversary playbooks to defense strategies, provides a structured way to align defensive tactics with different phases of an attack. The table below outlines various defense strategies across phases like detect, deny, disrupt, degrade, deceive, and destroy.

While many defenses, such as dark web scans, mail gateways, and EDRs, are considered low-cost for defenders, the most impactful strategies are those that impose high costs on attackers. For example, advanced threat analysis techniques like sandboxing force adversaries to innovate. Sandboxing detects malicious behavior by analyzing malware in a controlled environment, prompting attackers to redesign their malware or burn valuable resources—a significant win for defenders.

This underscores the dual advantage of efficient defenses for organizations and resource-draining tactics for attackers. Sandboxing is particularly effective in the “degrade” and “deceive” phases according to Cohen’S table, where its ability to increase the complexity of adversarial operations makes it an essential tool in CTI. By focusing on defenses that increase attacker costs while leveraging accessible tools like EDRs, organizations can build a resilient security posture tailored to counter evolving threats.

Government agencies, the defense industry, and financial institutions are prime targets for nation-state and advanced threat actors, which means they must contend with sophisticated adversary playbooks. Yet, the challenge remains: how can these entities maintain efficiency amidst limited resources and operational demands?

The key lies in adopting strategies that prioritize automation, collaboration, and proactive threat mitigation.