Personal Data Exposure Risk Score Calculator

ANA›Life Services Authority›National Calculator Authority›Personal Data Exposure Risk Score Calculator

.calc-container { max-width: 640px; margin: 2rem 0; padding: 1.5rem; background: #fff; border: 1px solid #ddd; border-radius: 8px; box-shadow: 0 1px 3px rgba(0,0,0,0.06); font-family: system-ui, -apple-system, sans-serif; } .calc-container h3 { font-family: Georgia, serif; font-size: 1.15rem; color: #1a1a1a; margin-bottom: 1rem; padding-bottom: 0.5rem; border-bottom: 2px solid var(--ac, #3d5a80); } .calc-row { display: flex; align-items: center; gap: 0.75rem; margin-bottom: 0.75rem; flex-wrap: wrap; } .calc-row label { min-width: 160px; font-size: 0.9rem; color: #333; font-weight: 500; } .calc-row input[type="number"], .calc-row select { flex: 1; min-width: 120px; max-width: 200px; padding: 0.5rem 0.6rem; border: 1px solid #ccc; border-radius: 4px; font-size: 0.9rem; font-family: system-ui, sans-serif; color: #1a1a1a; background: #fafaf8; } .calc-row input:focus, .calc-row select:focus { outline: none; border-color: var(--ac, #3d5a80); box-shadow: 0 0 0 2px rgba(26,74,138,0.12); } .calc-row .unit { font-size: 0.82rem; color: #888; min-width: 30px; } .calc-btn { display: inline-block; margin-top: 0.5rem; padding: 0.55rem 1.5rem; background: var(--ac, #3d5a80); color: #fff; border: none; border-radius: 4px; font-size: 0.9rem; font-weight: 600; cursor: pointer; font-family: system-ui, sans-serif; } .calc-btn:hover { opacity: 0.9; } .calc-result { margin-top: 1.25rem; padding: 1rem 1.25rem; background: #f0f6fc; border-left: 3px solid var(--ac, #3d5a80); border-radius: 0 6px 6px 0; display: none; } .calc-result.visible { display: block; } .calc-result-label { font-size: 0.78rem; text-transform: uppercase; letter-spacing: 0.06em; color: #666; margin-bottom: 0.25rem; } .calc-result-value { font-size: 1.6rem; font-weight: 700; color: var(--ac, #3d5a80); } .calc-result-detail { font-size: 0.85rem; color: #555; margin-top: 0.5rem; line-height: 1.5; } .calc-note { margin-top: 1rem; font-size: 0.8rem; color: #888; font-style: italic; } .calc-grid { display: grid; grid-template-columns: 1fr 1fr; gap: 0.75rem; margin-top: 0.75rem; } .calc-grid-item { padding: 0.6rem 0.8rem; background: #f8f9fa; border-radius: 4px; border: 1px solid #eee; } .calc-grid-item .label { font-size: 0.75rem; color: #888; text-transform: uppercase; letter-spacing: 0.04em; } .calc-grid-item .value { font-size: 1.1rem; font-weight: 600; color: #1a1a1a; } @media (max-width: 720px) { .calc-row { flex-direction: column; align-items: flex-start; gap: 0.3rem; } .calc-row label { min-width: auto; } .calc-row input[type="number"], .calc-row select { max-width: 100%; width: 100%; } .calc-grid { grid-template-columns: 1fr; } } .calc-chart { margin: 1rem 0; text-align: center; } .calc-chart svg { max-width: 100%; height: auto; } .calc-chart-legend { display: flex; flex-wrap: wrap; justify-content: center; gap: 0.6rem 1.2rem; margin-top: 0.6rem; font-size: 0.8rem; color: #555; } .calc-chart-legend span { display: inline-flex; align-items: center; gap: 0.3rem; } .calc-chart-legend i { display: inline-block; width: 10px; height: 10px; border-radius: 2px; font-style: normal; } .calc-related { max-width: 640px; margin: 2rem 0 1rem; padding: 1.25rem 1.5rem; background: #f8f9fa; border: 1px solid #e8e8e8; border-radius: 8px; } .calc-related h3 { font-family: Georgia, serif; font-size: 1rem; color: #1a1a1a; margin: 0 0 0.75rem; padding-bottom: 0.4rem; border-bottom: 2px solid var(--ac, #3d5a80); } .calc-related-list { list-style: none; padding: 0; margin: 0 0 0.75rem; display: grid; grid-template-columns: 1fr 1fr; gap: 0.4rem 1.5rem; } .calc-related-list li a { font-size: 0.88rem; color: var(--ac, #3d5a80); text-decoration: none; } .calc-related-list li a:hover { text-decoration: underline; } .calc-browse-all { margin: 0.5rem 0 0; font-size: 0.9rem; font-weight: 600; } .calc-browse-all a { color: var(--ac, #3d5a80); text-decoration: none; } .calc-browse-all a:hover { text-decoration: underline; } @media (max-width: 720px) { .calc-related-list { grid-template-columns: 1fr; } }

Personal Data Exposure Risk Score Calculator

Estimate your personal data exposure risk score (0–100) based on your online presence, breach history, and privacy practices. A higher score indicates greater risk.

Number of known data breaches you've been part of

Number of active social media accounts

Password reuse level (1 = unique passwords, 5 = same password everywhere)

Multi-factor authentication usage (1 = never, 5 = always)

Amount of public personal info online (1 = minimal, 5 = extensive)

VPN / privacy tool usage (1 = always, 5 = never)

Susceptibility to phishing (1 = very cautious, 5 = often click links)

Number of internet-connected devices you own

Online shopping frequency (1 = rarely, 5 = daily)

Privacy settings review frequency (1 = regularly, 5 = never)

Calculate Risk Score Your risk score will appear here.

function perCalc() { // --- Gather inputs --- const breaches = parseFloat(document.getElementById('per-breaches').value); const social = parseFloat(document.getElementById('per-social').value); const reuse = parseFloat(document.getElementById('per-reuse').value); const mfa = parseFloat(document.getElementById('per-mfa').value); const publicInfo= parseFloat(document.getElementById('per-public').value); const vpn = parseFloat(document.getElementById('per-vpn').value); const phishing = parseFloat(document.getElementById('per-phishing').value); const devices = parseFloat(document.getElementById('per-devices').value); const shopping = parseFloat(document.getElementById('per-shopping').value); const privacy = parseFloat(document.getElementById('per-privacy').value);

// --- Input validation --- const fields = [ {val: breaches, min:0, max:50, name:"Data breaches"}, {val: social, min:0, max:20, name:"Social media accounts"}, {val: reuse, min:1, max:5, name:"Password reuse level"}, {val: mfa, min:1, max:5, name:"MFA usage"}, {val: publicInfo, min:1, max:5, name:"Public personal info"}, {val: vpn, min:1, max:5, name:"VPN usage"}, {val: phishing, min:1, max:5, name:"Phishing susceptibility"}, {val: devices, min:1, max:30, name:"Connected devices"}, {val: shopping, min:1, max:5, name:"Online shopping frequency"}, {val: privacy, min:1, max:5, name:"Privacy settings review"}, ];

for (const f of fields) { if (isNaN(f.val) || f.val f.max) { document.getElementById('per-result').innerHTML = ⚠ "${f.name}" must be between ${f.min} and ${f.max}.; return; } }

/ * ── FORMULA ────────────────────────────────────────────────────────────── * * Each factor is normalised to a 0–1 scale, weighted, then summed to * produce a raw score that is mapped to 0–100. * * Weights (sum = 1.00): * W_breach = 0.20 (breaches are the strongest direct exposure signal) * W_reuse = 0.15 (password reuse amplifies breach impact) * W_mfa = 0.12 (MFA is the single best mitigation) * W_phishing = 0.12 (human factor) * W_public = 0.10 (publicly available PII) * W_vpn = 0.08 (network-level privacy) * W_social = 0.08 (attack surface via social platforms) * W_devices = 0.07 (IoT / endpoint attack surface) * W_shopping = 0.05 (payment & address data exposure) * W_privacy = 0.03 (proactive hygiene) * * Normalisation: * breach_norm = min(breaches / 10, 1) [0–10+ breaches → 0–1] * social_norm = min(social / 10, 1) [0–10+ accounts → 0–1] * reuse_norm = (reuse - 1) / 4 [scale 1–5 → 0–1] * mfa_norm = (mfa - 1) / 4 [higher MFA = lower risk → inverted] * public_norm = (publicInfo - 1) / 4 * vpn_norm = (vpn - 1) / 4 [higher vpn score = less usage = more risk] * phishing_norm = (phishing - 1) / 4 * devices_norm = min((devices - 1) / 14, 1) [1–15+ devices → 0–1] * shopping_norm = (shopping - 1) / 4 * privacy_norm = (privacy - 1) / 4 * * MFA is a protective factor, so its contribution is inverted: * mfa_contribution = W_mfa * (1 - mfa_norm) * (higher MFA usage → lower risk contribution) * * Raw score (0–1): * R = W_breach * breach_norm * + W_social * social_norm * + W_reuse * reuse_norm * + W_mfa * (1 - mfa_norm) ← protective inversion * + W_public * public_norm * + W_vpn * vpn_norm * + W_phishing * phishing_norm * + W_devices * devices_norm * + W_shopping * shopping_norm * + W_privacy * privacy_norm * * Final score (0–100): * Score = round(R * 100) * * ───────────────────────────────────────────────────────────────────────── /

// Weights const W_breach = 0.20; const W_reuse = 0.15; const W_mfa = 0.12; const W_phishing = 0.12; const W_public = 0.10; const W_vpn = 0.08; const W_social = 0.08; const W_devices = 0.07; const W_shopping = 0.05; const W_privacy = 0.03;

// Normalise const breach_norm = Math.min(breaches / 10, 1); const social_norm = Math.min(social / 10, 1); const reuse_norm = (reuse - 1) / 4; const mfa_norm = (mfa - 1) / 4; // high = protective const public_norm = (publicInfo - 1) / 4; const vpn_norm = (vpn - 1) / 4; const phishing_norm = (phishing - 1) / 4; const devices_norm = Math.min((devices - 1) / 14, 1); const shopping_norm = (shopping - 1) / 4; const privacy_norm = (privacy - 1) / 4;

// Weighted raw score const R = W_breach * breach_norm + W_social * social_norm + W_reuse * reuse_norm + W_mfa * (1 - mfa_norm) + W_public * public_norm + W_vpn * vpn_norm + W_phishing * phishing_norm + W_devices * devices_norm + W_shopping * shopping_norm + W_privacy * privacy_norm;

const score = Math.round(R * 100);

// Risk band let band, color, advice; if (score ${c.label}${c.pct} ).join('');

document.getElementById('per-result').innerHTML = ` ### Risk Score: ${score} / 100 — ${band} Risk

${advice}

Factor Score Points

${breakdown}

Total${score}

`; }

#### Formula

Each input is normalised to a 0–1 scale, multiplied by its weight, and summed to produce a raw score R (0–1). The final score is Score = round(R × 100).

R = 0.20 × breach_norm + 0.15 × reuse_norm + 0.12 × (1 − mfa_norm) + 0.12 × phishing_norm + 0.10 × public_norm + 0.08 × vpn_norm + 0.08 × social_norm + 0.07 × devices_norm + 0.05 × shopping_norm + 0.03 × privacy_norm

MFA is a protective factor and is therefore inverted: higher MFA usage reduces the score.

Normalisation: breach_norm = min(breaches/10, 1)  |  social_norm = min(social/10, 1)  |  devices_norm = min((devices−1)/14, 1)  |  all 1–5 scales → (value−1)/4

Risk Bands: 0–20 Low · 21–40 Moderate-Low · 41–60 Moderate · 61–80 High · 81–100 Critical

#### Assumptions & References

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References

• ANA
• Life Services Authority