Cybersecurity Risk Assessment Calculator

Vulnerability represents how likely a threat would succeed if it hit your systems with no defenses at all — an inherent weakness in the asset or process itself. Control effectiveness then represents how much your actual security measures reduce that raw likelihood, so the two combine to give effective vulnerability: the real-world chance a threat event turns into an actual loss after your existing defenses are accounted for.

A single incident's cost tells you what one bad event would hurt, but it says nothing about how often that event is likely to happen — a rare but catastrophic risk and a frequent but minor one can have wildly different single-incident costs while representing similar overall exposure. Annualizing the loss by multiplying by expected frequency puts every risk in the same per-year dollar terms, which is what actually needs comparing when allocating a limited security budget.

No — it's a commonly cited industry rule of thumb (often stated as a 5-15% range) meant as a starting reference point, not a precise optimal figure for every situation. The right investment level also depends on factors this simplified model doesn't capture, like whether a control also mitigates other risks simultaneously, and the point of diminishing returns as spending increases.

FAIR is a real, published standard: The Open Group maintains it as the Risk Analysis (O-RA) Standard, the risk-quantification half of the Open FAIR body of knowledge (paired with the Risk Taxonomy, O-RT, Standard that defines FAIR's risk factors). This calculator implements FAIR's core mechanic — Loss Event Frequency multiplied by Loss Magnitude (here, Single Loss Expectancy) to produce an Annualized Loss Expectancy — in simplified form, without the full taxonomy's more granular threat-capability and control-strength breakdowns.

The math itself is exact, but its output quality depends entirely on the accuracy of the inputs you supply, and threat frequency and vulnerability in particular are often genuinely difficult to estimate precisely in the real world. Treat the annualized loss figure as a structured, defensible estimate for comparing and prioritizing risks relative to each other, rather than a guaranteed prediction of actual future losses.