Threat Intelligence Framework

What Is a Threat Intelligence Framework?

A threat intelligence framework is a structured system that gathers, analyzes, and applies threat data to improve organizational defenses. It helps teams make informed decisions based on real-time data, enabling better preparedness against cyber risks [link to TM glossary article].

Threat intelligence frameworks generally entail several discrete phases: setting objectives and priorities for data collection and analysis; collecting and processing data from various internal and external sources, such as system logs and threat feeds; analyzing data in real-time using AI techniques to detect patterns and threats; and disseminating findings for review and actioning, including feedback for future cycles.  

Threat intelligence frameworks are put into action through threat intelligence platforms, which, like threat libraries [link to TM glossary article], collect data from various sources. However, rather than serving only as a knowledge base, threat intelligence platforms use real-time analysis to provide actionable insights and enable proactive measures.

Why Are They Important?

Given the overwhelming amounts of threat data and the rapid evolution of cyber landscapes, threat intelligence frameworks are essential for security teams to structure their work and make sense of the latest cybersecurity risks [link to TM glossary page]. Most significantly, a threat intelligence framework distills raw data into actionable insights, which enables organizations to adopt a more proactive security posture. Security teams operating without a threat intelligence framework rely on less effective ad-hoc approaches, typically due to resource constraints, limited experience, or a reactive security culture.

What Are Some Key Considerations?

Beyond providing a structured approach to threat analysis for security operations, threat intelligence frameworks offer several important benefits, such as improved threat response and decision-making. Some threat intelligence frameworks, such as MITRE ATT&CK, outline specific tactics used by malicious actors, which enables security teams to recognize indicators of compromise (IoCs) and respond more quickly and effectively. Perhaps most importantly, the use of threat intelligence frameworks contributes to a security-first culture of cross-functional collaboration and continuous improvement. 

However, threat intelligence frameworks can have potential drawbacks, primarily with implementation—particularly with integrating various data sources—and contextualizing data effectively. Some frameworks offer only limited applicability to modern attack methods or may focus on IT environments at the expense of operational technology (OT) systems.

How Are They Related to Threat Modeling?

Threat intelligence frameworks assess the broader threat landscape, providing the foundational cybersecurity information to assess and respond to live threats. Whereas threat intelligence frameworks focus on real-time threat data collection and analysis, threat modeling strives to secure an organization’s applications, infrastructure, and code before incidents happen. This helps provide a holistic view of an organization’s security posture by assessing digital assets against known threats. 

Closing

Threat intelligence frameworks are an essential component of a robust cybersecurity strategy, providing the raw materials for risk assessments and threat models. Threat modeling uses the insights and best practices that threat intelligence frameworks provide to create effective and accurate models. Next-generation threat modeling frameworks and built-in compliance ensure the right threat intelligence is incorporated into threat models.