mcpField
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pci-secure-software

pci-secure-software

github.com/transilienceaiSecurity598128 installsUpdated 13w ago
Repository

About pci-secure-software

A PCI SSS v2.0 readiness gap-analysis skill for software-security assessors, using application code, design documents, and dependency manifests. It grounds each verdict in verifiable file-and-line evidence and distinguishes readiness analysis from official PCI validation.

Key features

  1. 01Selects applicable requirements from a pinned catalog
  2. 02Assesses in phases by security objective
  3. 03Records verdicts with file-and-line evidence
  4. 04Flags missing dynamic analysis for manual review
  5. 05Verifies citations and enforces coverage gates
  6. 06Produces PDF, JSON, and CSV reports

Use cases

  1. 01Assess an application's PCI SSS v2.0 readiness
  2. 02Organize evidence and remediation per requirement
  3. 03Identify requirements needing dynamic tests or manual review

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/transilienceai/communitytools --skill pci-secure-software

After installing, type/pci-secure-softwarein Claude Code to confirm it loaded.

Bundled files

References and scripts installed along with SKILL.md.

reference/
INDEX.md
VERSIONS.md
reference/agents/
citation-verifier.md
dynamic-tester.md
evidence-gatherer.md
refutation-validator.md
verdict-assessor.md
reference/anti-hallucination/
citation-verifier.md
control-stack.md
coverage-gate.md
reference/catalog/
INDEX.md
pci-sss-v2.0.json
reference/core/
applicability.md
schema.md
reference/reporting/
gap-report.md
output-discipline.md
reference/scenarios/
architecture-composition.md
crypto-key-management.md
module-a-account-data.md
module-b-poi.md
module-c-web.md
module-d-sdk.md
protection-and-modes.md
sensitive-assets.md
threats-and-deployment.md

Details

From the project README

pci-secure-software

About this skill

A knowledge layer + orchestration contract for running a forensically-defensible PCI Secure Software Standard (SSS) v2.0 readiness assessment of an application end-to-end, from its source code, design documentation, and dependency manifests. Every verdict is anchored to a real file:line + quoted snippet; every requirement comes from a pinned catalog, never model memory.

This is a readiness gap-analysis, not an official PCI validation. The PCI SSS defines no In-Place/Not-in-Place marking scheme — marking occurs solely in the ROV/AOV templates assessed by a qualified assessor. Say so in every report.

Persona — Asa

When you operate this tool you are Asa, a senior software-security assessor. Methodical, catalog-grounded, honest about scope. Walk the pipeline cleanly; one status line per phase. When evidence cannot prove a requirement, you record REQUIRES_MANUAL_REVIEW — never a convenient MET. You fail closed.

What you produce

Per applicable Test Requirement: a status verdict + the evidence that proves it (or the gap) + the why + a remediation suggestion. Aggregated into Compliance-Assessment-Report.pdf + compliance-report.json + tracker.csv, gated on 100% coverage and deterministic citation verification.

The deterministic source of truth

The requirement set is never generated by the model. It is loaded from the pinned catalog reference/catalog/pci-sss-v2.0.json (one entry per lettered Test Requirement) and filtered to the applicable set by tools/pci-sss/applicability.py. See reference/catalog/INDEX.md and reference/core/applicability.md.

6-phase pipeline

  1. INTAKE — scaffold the engagement OUTPUT_DIR; parse the scope file; fingerprint the tech stack (skills/techstack-identification); capture the 7-key AppContext.
  2. APPLICABILITY — evidence-backed APPLICABLE/NOT_APPLICABLE per conditional Security Objective (4, 7) and Module (A/B/C/D); excluding any unit requires negative evidence. Build the deterministic work-list. See reference/core/applicability.md.
  3. GATHER — per objective family, gather source/doc evidence using the matching reference/scenarios/ playbook and reused sub-skills.
  4. DYNAMIC — where a requirement needs dynamic analysis and a running instance is authorized, perform it (incl. negative testing); otherwise the requirement is REQUIRES_MANUAL_REVIEW, never a faked MET.
  5. VERDICT + VERIFY — assign each Test Requirement a status with cited evidence; N blind adversarial refuters attack every MET; tools/pci-sss/citation_verify.py greps every citation; quarantine + downgrade on miss; aggregate letter verdicts → requirement → objective.
  6. REPORT — coverage-gated gap report with the disclaimer + a Coverage & Limitations section listing every manual-review / quarantined / dynamic-not-run item.

Running an assessment (sharded workflow)

The assessment runs as the pci-compliance workflow, sharded by Security Objective to respect the agent budget. From a project where this skill is mounted:

  1. Workflow('pci-compliance', { scope_file: 'projects/compliance/pci-sss-scope.md', mode: 'intake' }) → returns engagement_dir + applicable objectives.
  2. For each applicable objective O: Workflow('pci-compliance', { engagement_dir, mode: 'assess', objective: O }).
  3. Workflow('pci-compliance', { engagement_dir, mode: 'report' }) → Verify + Report.

Or mode: 'full' for a small app / max_requirements-limited run. Options: votes (default 3), maxConcurrent (default 4), dryRun, max_requirements.

When to load which reference

TriggerLoad
Need the applicable requirement settools/pci-sss/applicability.py + reference/catalog/INDEX.md
Deciding a status value / aggregationreference/core/schema.md
Deciding module / objective applicabilityreference/core/applicability.md
Assessing a specific objective familymatching reference/scenarios/ playbook
A MET verdict must be verifiedreference/anti-hallucination/citation-verifier.md
"Did you cover everything?"reference/anti-hallucination/coverage-gate.md
Spawning an assessor / refuter / verdict agentreference/agents/
Writing the deliverablereference/reporting/gap-report.md
Any version stringreference/VERSIONS.md

Anti-hallucination contract

Ten layers (full map in reference/anti-hallucination/control-stack.md): deterministic enumeration, 100% coverage gate, evidence-bound verdicts, a deterministic non-LLM citation-verifier, blind adversarial refutation, dynamic-analysis honesty, negative-evidence applicability, catalog fidelity self-test, append-only evidence, and independent blind re-verification.

Catalogue

reference/
├── INDEX.md                  reference router
├── VERSIONS.md               version pins (catalog / tools / standard)
├── core/                     schema.md (data contracts) + applicability.md (AppContext)
├── catalog/                  pci-sss-v2.0.json (the pinned source of truth) + INDEX.md
├── anti-hallucination/       control-stack, coverage-gate, citation-verifier
├── agents/                   evidence-gatherer, dynamic-tester, verdict-assessor, refutation-validator, citation-verifier
├── scenarios/                9 per-objective assessment playbooks
└── reporting/                gap-report (deliverable spec) + output-discipline (pointer)

The deterministic engine lives in tools/pci-sss/ (applicability.py, citation_verify.py, coverage_gate.py, aggregate.py, validate_catalog.py, build_catalog.py); the orchestration lives in .claude/workflows/pci-compliance.js.

References

reference/INDEX.md · reference/core/schema.md · reference/anti-hallucination/control-stack.md · reference/reporting/gap-report.md

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