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Add folder anatomy (scripts/agent.py + references/api-reference.md) for 648 cybersecurity skills
Complete skill folder anatomy across all cybersecurity skills: - scripts/agent.py: 80-150 line Python agents using real libraries (impacket, boto3, azure-mgmt-*, kubernetes, pefile, yara, scapy, shodan, stix2, etc.) - references/api-reference.md: real API documentation with method signatures - LICENSE: MIT license for all skill folders
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# API Reference: CISA Zero Trust Maturity Model Assessment Agent
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## Dependencies
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| Library | Version | Purpose |
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|---------|---------|---------|
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| (stdlib only) | Python 3.8+ | JSON processing, assessment logic |
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## CLI Usage
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```bash
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python scripts/agent.py \
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--data /assessments/zt_responses.json \
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--output-dir /reports/ \
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--output ztmm_report.json
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```
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## Functions
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### `assess_control(control, implemented, maturity) -> dict`
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Scores a single control: 0 (Traditional) to 3 (Optimal).
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### `assess_pillar(pillar, responses) -> dict`
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Evaluates all controls within a CISA ZT pillar. Returns score, percentage, and maturity level.
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### `compute_overall_maturity(pillar_results) -> dict`
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Aggregates pillar scores into overall maturity: Traditional/Initial/Advanced/Optimal.
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### `generate_recommendations(pillar_results) -> list`
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Identifies unimplemented controls, prioritizes by pillar weakness.
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### `generate_report(data_path) -> dict`
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Full assessment pipeline: load data, assess 5 pillars, compute maturity, generate recommendations.
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## CISA ZT Pillars
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| Pillar | Controls Assessed |
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|--------|-------------------|
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| Identity | MFA, phishing-resistant MFA, JIT access, PAM |
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| Devices | Inventory, EDR, health attestation, posture |
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| Networks | Microsegmentation, encrypted DNS, SDP |
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| Applications | Inventory, access controls, API security |
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| Data | Classification, DLP, encryption at rest |
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## Input Data Format
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```json
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{
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"Identity": {
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"MFA enforced for all users": {"implemented": true, "maturity": "Advanced"},
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"Phishing-resistant MFA (FIDO2/PIV)": {"implemented": false, "maturity": "Traditional"}
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}
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}
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```
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## Output Schema
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```json
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{
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"overall_maturity": {"percentage": 52.3, "maturity_level": "Advanced"},
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"pillars": [{"pillar": "Identity", "percentage": 66.7, "maturity_level": "Advanced"}],
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"recommendations": [{"pillar": "Devices", "control": "EDR deployed", "priority": "HIGH"}]
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}
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```
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