fix(freigabe): Vorbereitung-Module release prep — Python 3.9 fix, Scope Engine tests, MkDocs
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- fix: company_profile_routes.py — dict|None → Optional[dict] for Python 3.9 compat (9/9 tests grün) - test: 40 Vitest-Tests für ComplianceScopeEngine (calculateScores, determineLevel, evaluateHardTriggers, evaluate integration, buildDocumentScope, evaluateRiskFlags) - docs: vorbereitung-module.md — Profil, Scope, UCCA vollständig dokumentiert - docs: mkdocs.yml — Nav-Eintrag "Vorbereitung-Module (Paket 1)" vor Analyse-Module Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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# Vorbereitung-Module (Paket 1)
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Die drei Vorbereitung-Module bilden die Grundlage des SDK-Workflows. Sie erfassen das Unternehmensprofil, bestimmen den passenden Compliance-Umfang und bewerten konkrete KI/Daten-Anwendungsfälle.
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| Modul | Code | Route | Backend |
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|-------|------|-------|---------|
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| **Company Profile** | CP-PROF | `/sdk/company-profile` | FastAPI `backend-compliance` |
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| **Compliance Scope** | CP-SCOPE | `/sdk/compliance-scope` | FastAPI `backend-compliance` |
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| **Use-Case Assessment** | CP-UC | `/sdk/use-cases` | Go `ai-compliance-sdk` |
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---
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## Profil — company-profile (CP-PROF)
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### Übersicht
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6-Schritt-Wizard zur Erfassung des vollständigen Unternehmensprofils. Speichert hybrid in `localStorage` (Draft) und der DB (Endstand).
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### API-Endpunkte
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| Methode | Pfad | Beschreibung |
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|---------|------|--------------|
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| `GET` | `/v1/company-profile` | Profil für Tenant laden |
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| `POST` | `/v1/company-profile` | Profil erstellen oder aktualisieren (Upsert) |
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| `PATCH` | `/v1/company-profile` | Einzelne Felder aktualisieren |
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| `DELETE` | `/v1/company-profile` | Profil löschen (Art. 17 DSGVO) |
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| `GET` | `/v1/company-profile/audit` | Audit-Log der Profiländerungen |
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### Datenbankstruktur
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**Tabelle:** `compliance_company_profiles` (Migration 005)
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28 Felder, u.a.:
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```sql
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id UUID PRIMARY KEY
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tenant_id TEXT UNIQUE NOT NULL
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company_name TEXT
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legal_form TEXT -- GmbH, AG, GbR, ...
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industry TEXT -- tech, finance, healthcare, public, retail, education
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company_size TEXT -- micro, small, medium, large
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employee_count TEXT -- 1-9, 10-49, 50-249, 250-999, 1000+
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uses_ai BOOLEAN
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ai_use_cases JSONB
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dpo_name TEXT
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machine_builder JSONB -- IACE-Profil für Maschinenbauer
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is_complete BOOLEAN
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completed_at TIMESTAMPTZ
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```
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**Audit-Tabelle:** `compliance_company_profile_audit`
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```sql
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id UUID PRIMARY KEY
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tenant_id TEXT
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action TEXT -- create | update | delete
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changed_fields JSONB
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changed_by TEXT
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created_at TIMESTAMPTZ
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```
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### Request-Modell (CompanyProfileRequest)
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```json
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{
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"company_name": "Beispiel GmbH",
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"legal_form": "GmbH",
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"industry": "tech",
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"founded_year": 2018,
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"business_model": "B2B",
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"company_size": "small",
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"employee_count": "10-49",
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"annual_revenue": "2-10 Mio",
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"headquarters_country": "DE",
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"uses_ai": true,
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"ai_use_cases": ["Chatbot", "Dokumentenklassifikation"],
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"is_complete": true
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}
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```
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### Tests
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**Datei:** `backend-compliance/tests/test_company_profile_routes.py`
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9 Tests — alle grün:
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- `test_get_profile_not_found` — 404 wenn kein Profil
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- `test_create_profile` — POST legt Profil an
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- `test_upsert_profile_update` — POST auf bestehendem Profil → UPDATE
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- `test_delete_profile` — DELETE entfernt Profil
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- `test_delete_profile_not_found` — 404 bei fehlendem Profil
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- `test_get_audit_log_empty` — leeres Audit-Log
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- `test_audit_log_after_create` — Audit-Eintrag nach CREATE
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- `test_audit_log_after_delete` — Audit-Eintrag nach DELETE
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- `test_complete_profile_workflow` — End-to-End Workflow
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---
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## Scope — compliance-scope (CP-SCOPE)
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### Übersicht
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4-Tab-Oberfläche zur Bestimmung des optimalen Compliance-Levels (L1–L4):
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| Tab | Inhalt |
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|-----|--------|
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| **Overview** | Aktueller Level, Score-Visualisierung, Dokumenten-Anforderungen |
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| **Wizard** | 35 Fragen in 6 Blöcken (ca. 10–15 min) |
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| **Entscheidung** | Begründung, Hard Triggers, Gap-Analyse |
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| **Export** | JSON/PDF-Export der Scope-Entscheidung |
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### ComplianceScopeEngine
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Die Engine (`lib/sdk/compliance-scope-engine.ts`) implementiert eine 8-Schritt-Pipeline:
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```
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1. calculateScores(answers) → ComplianceScores
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2. evaluateHardTriggers(answers) → TriggeredHardTrigger[]
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3. determineLevel(scores, triggers) → ComplianceDepthLevel
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4. buildDocumentScope(level, ...) → RequiredDocument[]
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5. evaluateRiskFlags(answers, level) → RiskFlag[]
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6. calculateGaps(answers, level) → ScopeGap[]
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7. buildNextActions(docs, gaps) → NextAction[]
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8. buildReasoning(...) → ScopeReasoning[]
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```
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### Level-Modell
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| Level | Composite-Score | Bezeichnung |
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|-------|----------------|-------------|
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| **L1** | ≤ 25 | Lean Startup — Minimalansatz |
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| **L2** | 26–50 | KMU Standard |
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| **L3** | 51–75 | Erweitert |
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| **L4** | > 75 | Zertifizierungsbereit |
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Finale Stufe = `max(score-basiertes Level, höchstes Hard-Trigger-Level)`
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### Score-Gewichte
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```
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Composite = Risk × 0.4 + Complexity × 0.3 + Assurance × 0.3
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```
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Scores werden aus 35 gewichteten Fragen berechnet. Jede Frage hat individuelle Gewichte für `risk`, `complexity`, `assurance` (definiert in `QUESTION_SCORE_WEIGHTS`).
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### Hard Trigger Kategorien (50 Regeln)
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| Kategorie | Regeln | Beispiel-Trigger |
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|-----------|--------|-----------------|
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| `art9` | 9 | Gesundheits-, Biometrie-, Genetikdaten → mind. L3 |
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| `vulnerable` | 3 | Minderjährige → L3/L4 + DSFA |
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| `adm` | 6 | Autonome KI, Profiling, Scoring → L2/L3 |
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| `surveillance` | 5 | Videoüberwachung, Mitarbeitermonitoring → L2/L3 |
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| `third_country` | 5 | Drittland-Transfer → L2/L3 |
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| `certification` | 5 | ISO 27001, SOC2, TISAX → L4 |
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| `scale` | 5 | >1Mio Datensätze, >250 Mitarbeiter → L3 |
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| `product` | 7 | Webshop, Datenmakler, B2C → L2/L3 |
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| `process_maturity` | 5 | Fehlende Prozesse (DSAR, Löschung, Incident) |
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| `iace_*` | 5+ | Maschinenbauer: AI Act, CRA, NIS2 |
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### API-Endpunkte
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| Methode | Pfad | Beschreibung |
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|---------|------|--------------|
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| `GET` | `/v1/compliance-scope` | Scope-Zustand laden (`sdk_states` JSONB) |
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| `POST` | `/v1/compliance-scope` | Scope-Zustand speichern (JSONB UPSERT) |
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Scope-Daten werden in `sdk_states.state->'compliance_scope'` als JSONB gespeichert.
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### Tests
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**Datei:** `backend-compliance/tests/test_compliance_scope_routes.py` — 27 Tests
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**Datei:** `admin-compliance/lib/sdk/__tests__/compliance-scope-engine.test.ts` — 40 Vitest-Tests
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Engine-Tests decken ab:
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- `calculateScores`: Leer-Array, boolean/numeric/array Antworten, Composite-Gewichtung
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- `determineLevel`: L1–L4 Schwellenwerte, Hard-Trigger-Override, Level-Maximum
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- `evaluateHardTriggers`: Art. 9, Minderjährige, KI-Scoring, mehrere Trigger
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- `evaluate` (Integration): Vollständige ScopeDecision, Felder vorhanden, Level-Bestimmung
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- `buildDocumentScope`: Array-Rückgabe, Dokumentstruktur, Sortierung
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- `evaluateRiskFlags`: Verschlüsselung, Drittland, DPO-Pflicht
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---
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## Anwendung — use-case-assessment / UCCA (CP-UC)
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### Übersicht
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Bewertet konkrete Datenanwendungen hinsichtlich DSGVO- und AI-Act-Konformität. Gibt eine **Machbarkeitsentscheidung** (Feasibility) und detaillierte Befunde zurück.
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| Ansicht | Inhalt |
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|---------|--------|
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| **Liste** | Alle Assessments mit Filter, Pagination, RiskScoreGauge |
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| **Detail** | Vollständiger Befund-Report mit Kategorien, Controls |
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| **Neu** | Wizard-Formular zur Assessment-Erstellung |
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### Feasibility-Werte
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| Wert | Bedeutung |
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|------|-----------|
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| `YES` | Umsetzung ohne Einschränkungen empfohlen |
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| `CONDITIONAL` | Umsetzung nur mit spezifischen Maßnahmen |
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| `NO` | Umsetzung nicht empfohlen (unakzeptables Risiko) |
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### Risiko-Level
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| Level | Score-Bereich |
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|-------|--------------|
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| `MINIMAL` | 0–20 |
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| `LOW` | 21–40 |
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| `MEDIUM` | 41–60 |
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| `HIGH` | 61–80 |
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| `UNACCEPTABLE` | 81–100 |
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### Backend: ai-compliance-sdk (Go)
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**Service:** `bp-compliance-ai-sdk` (Port 8090 intern, 8093 extern)
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Relevante Module in `internal/ucca/`:
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| Datei | Funktion |
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|-------|---------|
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| `policy_engine.go` | Zentrale Regelauswertung |
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| `dsgvo_module.go` | DSGVO-spezifische Prüfungen (Art. 5–9, 22, 35) |
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| `ai_act_module.go` | AI-Act Risikokategorisierung |
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| `nis2_module.go` | NIS2-Anforderungen |
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| `escalation.go` | Eskalationslogik bei Hochrisiko |
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| `handlers.go` | HTTP Handler (Gin) |
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**Datenbanktabellen:**
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```sql
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ucca_assessments -- Assessments (tenant_id, title, description, status, feasibility, risk_level)
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ucca_findings -- Einzelbefunde pro Assessment
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ucca_controls -- Empfohlene Maßnahmen
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```
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### Proxy
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```
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Frontend /api/sdk/v1/ucca/**
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→ ai-compliance-sdk:8090/ucca/**
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```
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Proxy-Datei: `admin-compliance/app/api/sdk/v1/ucca/[[...path]]/route.ts`
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### Tests
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8 Go-Test-Dateien in `ai-compliance-sdk/internal/ucca/`:
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```
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handlers_test.go
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policy_engine_test.go
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dsgvo_module_test.go
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ai_act_module_test.go
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nis2_module_test.go
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escalation_test.go
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assessment_test.go
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feasibility_test.go
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```
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Ausführen auf Mac Mini:
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```bash
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ssh macmini "/usr/local/bin/docker exec bp-compliance-ai-sdk go test ./internal/ucca/... -v"
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```
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