FAIR, an acronym for Factor Analysis of Information Risk, is a foundational open-source methodology within cybersecurity that enables organizations to understand, analyze, and quantify information risk in financial terms. Unlike traditional qualitative approaches that rely on subjective heat maps or high-medium-low scales, FAIR provides a rigorous, quantitative framework for measuring the probable frequency and magnitude of future loss events.

Core Components

The FAIR framework dissects risk into two fundamental components:

• Threat Event Frequency: How often a threat event is likely to occur
• Probable Loss Magnitude: The financial impact when a threat materializes

These elements are further broken down into granular factors including threat capability, control strength, vulnerability, asset value, and various forms of primary and secondary losses.

Key Benefits

FAIR empowers security and business leaders to:

• Make data-driven decisions regarding security investments
• Prioritize mitigation strategies based on genuine return on investment
• Communicate complex risk scenarios with clarity to stakeholders
• Transform abstract threat concepts into actionable intelligence

Strategic Value

By providing measurable outcomes rather than subjective assessments, FAIR enhances organizational resilience against evolving cyber threats. The framework supports effective governance and strategic planning by enabling precise financial quantification of cyber risk exposure, making it invaluable for sophisticated risk management and threat intelligence initiatives.