Multi-Factor Authentication Risk Reduction Calculator
ANA›Life Services Authority›National Calculator Authority›Multi-Factor Authentication Risk Reduction Calculator
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Multi-Factor Authentication Risk Reduction Calculator
Estimates the reduction in account compromise risk when implementing Multi-Factor Authentication (MFA), based on baseline breach probability, MFA effectiveness, and user adoption rate.
Baseline Annual Account Compromise Probability (%) Likelihood an account is compromised per year without MFA (e.g., 1–20%)
MFA Effectiveness (%) Percentage of attacks blocked by MFA. Microsoft/Google research: SMS ≈ 96%, Authenticator App ≈ 99.9%
MFA Adoption / Enforcement Rate (%) Percentage of users/accounts that actually use MFA
Total Number of Accounts Total user accounts in scope
Estimated Cost per Compromised Account ($) Average cost of remediating one compromised account (incident response, downtime, etc.)
Calculate
function mulCalc() { // --- Grab inputs --- const baselineRiskPct = parseFloat(document.getElementById('mul-baseline-risk').value); const mfaEffPct = parseFloat(document.getElementById('mul-mfa-effectiveness').value); const adoptionPct = parseFloat(document.getElementById('mul-adoption-rate').value); const numAccounts = parseFloat(document.getElementById('mul-num-accounts').value); const costPerBreach = parseFloat(document.getElementById('mul-cost-per-breach').value); const resultDiv = document.getElementById('mul-result');
// --- Validation --- const errors = []; if (isNaN(baselineRiskPct) || baselineRiskPct 100) errors.push("Baseline risk must be between 0.01% and 100%."); if (isNaN(mfaEffPct) || mfaEffPct = 100) errors.push("MFA effectiveness must be between 1% and 99.9%."); if (isNaN(adoptionPct) || adoptionPct 100) errors.push("Adoption rate must be between 1% and 100%."); if (isNaN(numAccounts) || numAccounts 0) { resultDiv.style.display = 'block'; resultDiv.innerHTML = 'Input Error:' + errors.map(e => '').join('') + ''; return; }
// --- Convert to decimals --- const P_base = baselineRiskPct / 100; // baseline compromise probability per account const E_mfa = mfaEffPct / 100; // MFA effectiveness const A = adoptionPct / 100; // adoption rate
// --- Core Formulas --- // Residual risk for MFA-protected accounts: // P_protected = P_base * (1 - E_mfa) const P_protected = P_base * (1 - E_mfa);
// Blended (portfolio) residual risk across all accounts: // P_residual = A * P_protected + (1 - A) * P_base // = P_base * [A*(1 - E_mfa) + (1 - A)] // = P_base * [1 - A * E_mfa] const P_residual = P_base * (1 - A * E_mfa);
// Absolute risk reduction (percentage points): // ARR = P_base - P_residual = P_base * A * E_mfa const ARR = P_base - P_residual;
// Relative risk reduction: // RRR = ARR / P_base = A * E_mfa const RRR = ARR / P_base;
// Expected compromised accounts (before MFA): const expectedBreachesBefore = P_base * numAccounts; // Expected compromised accounts (after MFA): const expectedBreachesAfter = P_residual * numAccounts; // Accounts saved per year: const accountsSaved = expectedBreachesBefore - expectedBreachesAfter;
// Annual cost exposure before and after: const costBefore = expectedBreachesBefore * costPerBreach; const costAfter = expectedBreachesAfter * costPerBreach; const costSaved = accountsSaved * costPerBreach;
// --- Format helpers --- const fmt2 = v => v.toFixed(2); const fmtPct = v => (v * 100).toFixed(4); const fmtDollar = v => '$' + v.toLocaleString('en-US', {minimumFractionDigits:2, maximumFractionDigits:2});
// --- Render --- resultDiv.style.display = 'block'; resultDiv.innerHTML = ` ### Results
Baseline Compromise Probability (per account/year) ${fmtPct(P_base)}%
Residual Risk — MFA-Protected Accounts ${fmtPct(P_protected)}%
Blended Residual Risk (all accounts) ${fmtPct(P_residual)}%
Absolute Risk Reduction (ARR) ${fmtPct(ARR)} percentage points
Relative Risk Reduction (RRR) ${fmt2(RRR * 100)}%
Expected Compromised Accounts / Year (Before MFA) ${fmt2(expectedBreachesBefore)}
Expected Compromised Accounts / Year (After MFA) ${fmt2(expectedBreachesAfter)}
Accounts Protected / Year ${fmt2(accountsSaved)}
Annual Cost Exposure (Before MFA) ${fmtDollar(costBefore)}
Annual Cost Exposure (After MFA) ${fmtDollar(costAfter)}
Estimated Annual Cost Savings ${fmtDollar(costSaved)}
`; }
#### Formulas Used
1. Residual risk for MFA-protected accounts:
P_protected = P_base × (1 − E_mfa) Where P_base = baseline annual compromise probability, E_mfa = MFA effectiveness (fraction).
2. Blended residual risk across all accounts:
P_residual = A × P_protected + (1 − A) × P_base = P_base × (1 − A × E_mfa) Where A = MFA adoption rate (fraction). Accounts without MFA retain the full baseline risk.
3. Absolute Risk Reduction (ARR):
ARR = P_base − P_residual = P_base × A × E_mfa
4. Relative Risk Reduction (RRR):
RRR = ARR / P_base = A × E_mfa
5. Expected compromised accounts:
Breaches_before = P_base × N Breaches_after = P_residual × N Accounts_saved = Breaches_before − Breaches_after
6. Annual cost savings:
Cost_saved = Accounts_saved × Cost_per_breach
#### Assumptions & References
- MFA effectiveness values are drawn from Microsoft Security research (2019): SMS-based MFA blocks ~96% of automated attacks; authenticator-app / hardware-key MFA blocks ~99.9% of attacks. (Alex Weinert, Microsoft, 2019)
- This calculator models annual risk and does not account for multi-year compounding or attacker adaptation over time.
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