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hipaa
Run a HIPAA Security Rule gap analysis against your cloud environment.
Install with Codex or Claude Copy this prompt, paste it into Codex, Claude, or another assistant, and let it review the skill page and install it for you.
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Run a HIPAA Security Rule gap analysis against your cloud environment.
Install with Codex or Claude Copy this prompt, paste it into Codex, Claude, or another assistant, and let it review the skill page and install it for you.
Based on SOC occupation classification
Deep code scan for AI security issues — prompt injection, PII in prompts, hardcoded keys, unguarded agents.
Run AI governance checks across cloud accounts and code repos — ISO 42001, EU AI Act, NIST AI RMF compliance.
Scan cloud accounts and GitHub repos to discover AI/ML services and build an AI system inventory.
Walk staged changes against the engineering principles checklist and report pass/fail per principle. Run before any non-trivial commit. Catches doc drift, stub functions, single-region defaults, missing framework mappings, and other regressions before they ship.
Generate a public-facing security trust page from scan data. Produces a single deployable index.html that shows compliance framework scores, security policies, infrastructure overview, and data protection posture. Deployable to S3, Vercel, Netlify, or GitHub Pages.
Paste a vendor's domain. Get a security risk assessment in 60 seconds.
| name | hipaa |
| description | Run a HIPAA Security Rule gap analysis against your cloud environment. |
| user-invocable | true |
You are running a HIPAA Security Rule compliance assessment for a founder. Same cloud checks as SOC 2, but mapped to HIPAA Security Rule safeguards (Administrative, Physical, Technical).
Read shasta.config.json for python_cmd. Use that for all commands (shown as <PYTHON_CMD>).
<PYTHON_CMD> -c "
import json
from shasta.config import get_aws_client
from shasta.scanner import run_full_scan
from shasta.compliance.hipaa_mapper import get_hipaa_control_summary
from shasta.compliance.hipaa_scorer import calculate_hipaa_score
from shasta.reports.hipaa_report import save_hipaa_report
from shasta.db.schema import ShastaDB
client = get_aws_client()
client.validate_credentials()
print('Running HIPAA compliance scan...')
scan = run_full_scan(client, framework='hipaa')
db = ShastaDB(); db.initialize(); db.save_scan(scan)
report_path = save_hipaa_report(scan)
print(f'Report saved: {report_path}')
score = calculate_hipaa_score(scan.findings)
controls = get_hipaa_control_summary(scan.findings)
output = {
'report_path': str(report_path),
'score': {
'percentage': score.score_percentage,
'grade': score.grade,
'passing': score.passing,
'failing': score.failing,
'requires_policy': score.requires_policy,
},
'by_safeguard': {
'administrative': {'pass': score.administrative_pass, 'fail': score.administrative_fail},
'physical': {'pass': score.physical_pass, 'fail': score.physical_fail},
'technical': {'pass': score.technical_pass, 'fail': score.technical_fail},
},
'controls': {
k: {
'title': v['title'],
'safeguard': v['safeguard'],
'status': v['overall_status'],
'pass': v['pass_count'],
'fail': v['fail_count'],
'soc2_equiv': v['soc2_equivalent'],
'iso27001_equiv': v['iso27001_equivalent'],
}
for k, v in controls.items()
if v['has_automated_checks'] or v['overall_status'] != 'not_assessed'
}
}
print(json.dumps(output, indent=2))
"
/report for PDF generation, /remediate for fix guidance, /policy-gen for policy documents