Calculator
Enter your current posture and recent signals. Submit to see the score above this form.
Example Data Table
| Scenario | MFA / Privileged Users | Alerts & Anomalies | Result |
|---|---|---|---|
| Strong posture, low noise | 98% MFA, 3% privileged | 2 activity alerts, 0 key exposures | Low to Medium risk |
| Weak controls, moderate signals | 70% MFA, 9% privileged | 12 alerts, 4 external shares, 2 geo anomalies | High risk |
| Offboarding delay, unusual downloads | 90% MFA, 6% privileged | 6 large downloads, 3 DLP alerts, SLA 96h | High to Critical risk |
Formula Used
The calculator converts each input into a normalized risk component (0–100), then combines them with weights:
+ 0.18·Controls + 0.10·Telemetry + 0.04·Departing
+ MaturityModifier + 0.02·BreakGlassRisk
- Access increases when MFA is low and privileged/risky roles are high.
- Signals increases with alerts, large downloads, external sharing, and geo anomalies.
- Identity increases with orphan/shared accounts and new admin grants.
- Controls increases with weak endpoint health and key exposures.
- Telemetry increases with poor log coverage or short retention.
How to Use
- Gather recent 30-day cloud activity, DLP, and behavior alerts.
- Enter your identity posture, device health, and key hygiene.
- Confirm logging coverage and how long logs are retained.
- Select your privilege practices and offboarding response time.
- Press Submit to view the score above the form.
- Download CSV or PDF for reporting and tracking.
Risk scoring turns scattered signals into priorities
Insider risk in cloud environments blends access, activity, and data movement across many services. A structured score helps security teams compare teams, accounts, and time windows without relying on anecdotes. Weighted components highlight where small fixes reduce large exposure, especially when privileges and sensitive datasets overlap during peak project cycles. It also supports consistent reporting to leadership and creates a common language between security, IT, and compliance teams.
Identity hygiene drives most preventable insider exposure
Orphaned and shared accounts weaken accountability and complicate incident response. Reducing these identities lowers lateral movement opportunities and improves audit clarity, because every action maps to a real owner. Pair identity cleanup with strong multifactor coverage, role separation, and periodic entitlement reviews to keep privileged pathways narrow, time bound, and well approved. Automate deprovisioning and enforce unique credentials for all service users.
Behavior analytics works best with context and baselines
Alert volumes matter less than change over time. Track large downloads, unusual sharing, and location anomalies against historical averages per role, application, and contractor cohort. When a spike appears, validate with ticketing and manager approvals, then correlate with recent privilege grants. Tune detections and suppression rules so analysts focus on high fidelity events instead of constant noise. Segment baselines by geography and time of day to reduce false positives.
Telemetry quality determines investigation speed and certainty
Logging coverage and retention shape both confidence and outcomes. Centralized control plane logs, storage access logs, and identity events enable reconstruction of intent and impact across tenants. Longer retention supports slower investigations, legal holds, and recurring trend analysis across projects and vendors. Well structured fields also speed enrichment, case management, and automated response playbooks. Retain high value logs in immutable storage and regularly test retrieval workflows.
Use the score to plan controls, not to label people
Treat the result as a governance metric. Use it to justify least privilege work, just in time elevation, and faster offboarding for departing staff. Review the score monthly, document exceptions, and communicate improvements as operational risk reduction rather than surveillance. Combine the score with training, clear policies, and respectful HR processes to reduce harmful insider behavior.
FAQs
1) What does the risk score represent?
The score summarizes your current exposure based on inputs you provide, combining access posture, event signals, identity hygiene, endpoint controls, and telemetry maturity into a single 0–100 indicator.
2) Can a high score prove malicious intent?
No. A high score indicates elevated conditions and abnormal signals. It should trigger validation steps, access reviews, and evidence gathering, not assumptions about individuals.
3) Which inputs typically move the score fastest?
MFA coverage, shared accounts, orphan accounts, key exposure findings, and short log retention commonly create the biggest swings because they amplify both opportunity and investigation difficulty.
4) How should we choose alert numbers?
Use a consistent 30‑day window and count confirmed alerts or high confidence detections. If you only have raw alerts, start with a conservative estimate and refine monthly as tuning improves.
5) How often should we reassess?
Monthly is a practical cadence for governance. Recalculate after major events like reorganizations, new cloud projects, tool migrations, or large onboarding and offboarding waves.
6) How do CSV and PDF exports help?
Exports capture inputs, results, and timestamps for reporting, audits, and trend tracking. Keep historical exports to show risk reduction progress alongside control rollouts and policy changes.