Calculator Inputs
Use this form to estimate coverage across AI APIs, model endpoints, prompt channels, vector stores, agent tools, training workflows, and data interfaces.
Example Data Table
This sample table shows how different AI security zones can be tracked in a practical coverage program.
| Zone | Identified | Assessed | Protected | Critical | Critical Covered | Open Findings | Weighted Score |
|---|---|---|---|---|---|---|---|
| Model API Gateway | 24 | 22 | 19 | 6 | 5 | 2 | 82.4% |
| Prompt Injection Layer | 18 | 14 | 10 | 5 | 3 | 4 | 58.7% |
| Vector Store Connector | 20 | 17 | 13 | 4 | 4 | 1 | 76.9% |
| Training Pipeline | 28 | 21 | 16 | 8 | 6 | 3 | 67.5% |
| Agent Toolchain | 30 | 18 | 12 | 5 | 3 | 5 | 49.8% |
Formula Used
The calculator combines coverage breadth, critical path protection, testing effort, and unresolved findings into one practical score.
(Assessed Surfaces ÷ Total Identified Surfaces) × 100
(Protected Surfaces ÷ Total Identified Surfaces) × 100
(Covered Critical Surfaces ÷ Critical Surfaces) × 100
min((((0.70 × Automated Checks) + (1.30 × Manual Reviews)) ÷ Assessed Surfaces) × 40, 100)
(0.30 × Assessment Coverage) + (0.30 × Protection Coverage) + (0.25 × Critical Coverage) + (0.15 × Validation Score)
min((Open Findings ÷ Assessed Surfaces) × 35, 25)
min(((100 − Base Coverage Score) × Exposure Weight) + Finding Penalty, 100)
100 − Risk-Adjusted Gap
max(Target Coverage − Weighted Coverage Score, 0)
How to Use This Calculator
- Count all known AI-facing attack surfaces first.
- Enter how many were actually assessed by testing.
- Enter how many currently have active controls.
- Mark the number of high-impact critical surfaces.
- Enter how many critical surfaces are already covered.
- Add automated checks and manual review totals.
- Record unresolved findings still affecting assurance.
- Adjust exposure weight to reflect environment sensitivity.
- Set your target coverage and calculate the result.
- Review the chart, export files, and plan remediation.
Frequently Asked Questions
1. What is attack surface coverage for AI systems?
It estimates how much of your AI exposure is known, assessed, and protected. It covers APIs, model endpoints, prompts, data flows, agent tools, training paths, and supporting integrations.
2. Why separate assessed and protected surfaces?
Assessment shows what you reviewed. Protection shows where controls already exist. A system may be tested but still lack strong preventive or detective safeguards.
3. Why does critical coverage matter more?
Critical surfaces can cause greater harm when exposed. Prioritizing them helps teams reduce severe failure paths before trying to perfect low-impact areas.
4. What does exposure weight change?
Exposure weight increases or reduces the penalty on remaining gaps. Higher values fit sensitive environments, regulated systems, or deployments with privileged automation.
5. Why include open findings in the score?
Open findings show known weaknesses are still unresolved. They reduce practical coverage because documented issues can still be exploited until remediation is complete.
6. Does a high validation score guarantee security?
No. It only reflects testing depth per assessed surface. Real security still depends on control quality, threat relevance, and how quickly findings are resolved.
7. Can this calculator support ongoing reporting?
Yes. Teams can run it weekly or monthly, compare trend values, and track whether coverage grows faster than new AI exposure.
8. Should this replace full threat modeling?
No. It is a tracking and planning tool. Detailed threat models, architecture reviews, and control testing are still needed for strong AI security governance.