Measure exposure from habits, controls, and response speed. Pinpoint training gaps and prioritize remediation. Turn awareness data into safer actions for everyone.
| Team | Click rate | Training | MFA | Reporting (hrs) | Estimated score | Priority note |
|---|---|---|---|---|---|---|
| Finance | 12% | 88% | 82% | 16 | 62.4 | Targeted spear-phish drills and invoice controls. |
| Engineering | 6% | 84% | 90% | 10 | 41.8 | Improve completion and secure dev tooling access. |
| Sales | 15% | 78% | 70% | 22 | 76.1 | High urgency; refresh training and enforce MFA. |
| Operations | 8% | 92% | 88% | 12 | 33.5 | Maintain cadence; monitor reporting speed. |
The calculator converts each metric into a 0–100 risk component, then applies a weight. Higher values mean higher risk. The weighted components are summed and adjusted slightly for organization size.
| Metric | Weight | How risk is derived |
|---|---|---|
| Phishing click rate | 0.18 | Scaled so 25% click ≈ 100 risk. |
| Training completion | 0.10 | Risk = 100 − completion. |
| Policy acknowledgement | 0.07 | Risk = 100 − acknowledgement. |
| MFA coverage | 0.10 | Risk = 100 − coverage. |
| Privileged MFA | 0.06 | Risk = 100 − privileged coverage. |
| Patch compliance | 0.10 | Risk = 100 − compliance. |
| Password hygiene | 0.06 | Risk = 100 − hygiene score. |
| Reporting time | 0.08 | 0h→0 risk; 48h→70; 120h+→100. |
| Incident rate | 0.12 | 0→0 risk; 5→70; 12+→100. |
| Simulations frequency | 0.05 | Too rare increases risk; 12+/year floors at 20. |
| Role-based coverage | 0.05 | Risk = 100 − coverage. |
| Third-party reviews | 0.03 | Risk = 100 − review coverage. |
Overall score = Σ(component_risk × weight) + size_adjustment, clamped to 0–100.
Security awareness is measurable when human behavior is translated into comparable signals. This calculator converts operational metrics into a 0–100 risk score so teams can track improvement over time. For example, moving from a 12% phishing click rate to 6% halves the click contribution, while faster reporting reduces lateral movement opportunities. Include vendors and contractors to avoid blind spots in access hygiene metrics. Using a consistent 90‑day window keeps comparisons fair across quarters and business units.
Inputs reflect both habits and controls: completion, policy acknowledgement, MFA coverage, patch compliance, and response speed. Common benchmark goals include training completion above 90%, MFA above 85%, and privileged MFA above 95%. Reporting time below 12 hours typically indicates clear escalation paths. Incident rate is normalized per 100 users per quarter, allowing small and large groups to be evaluated using the same scale.
Each metric becomes a component risk value. Protective metrics are inverted using 100 minus the percentage, while adverse metrics are scaled to known upper bounds, such as 25% clicks mapping near 100 risk. Reporting time rises to 70 risk by 48 hours and reaches 100 after about 120 hours. Components are weighted, with phishing clicks and incident rate carrying the largest influence, then summed and lightly adjusted for exposure by organization size.
Use the component signals to target the biggest drivers first. If MFA risk is high, prioritize email, VPN, and admin consoles before lower‑impact apps. If patch risk dominates, tighten critical update SLAs and document exceptions. High click risk is best addressed with more frequent simulations, just‑in‑time training, and scenario drills for finance and executive assistants. Recalculate monthly to validate the effect of each change.
The export options support governance. CSV history can feed dashboards and show trend lines by department, while the PDF report provides a concise snapshot for quarterly reviews. Pair scores with narrative context: what changed, what actions were taken, and which targets are next. Over time, aim for a sustained score under 50, declining incident rate, and improved reporting speed, demonstrating reduced exposure and stronger security culture.
Use a consistent 60–90 day window so trends are comparable. If you run quarterly reporting, align inputs to the same quarter and avoid mixing annual training data with weekly phishing metrics.
The score is directional and blends behavior and control signals. It helps prioritize awareness work, but it cannot prove control effectiveness or regulatory compliance without audits and evidence.
Increase simulation cadence, add short follow‑up coaching for clickers, and run targeted scenarios for finance and executives. Combine this with stricter email protections and MFA enforcement for high‑risk apps.
Start with a best estimate from ticketing or SOC logs and keep the method consistent. You can also track near‑miss reports until your incident taxonomy and tagging mature.
Yes. Edit the weights array and scaling rules in the file to match your threat model. Keep changes documented, and avoid frequent adjustments so historical comparisons remain meaningful.
Report the overall score, top two drivers, and the next actions with owners and dates. Include trend charts from CSV history and highlight improvements in MFA, patch compliance, and reporting speed.
Important Note: All the Calculators listed in this site are for educational purpose only and we do not guarentee the accuracy of results. Please do consult with other sources as well.