fix: Restore all files lost during destructive rebase
A previous `git pull --rebase origin main` dropped 177 local commits,
losing 3400+ files across admin-v2, backend, studio-v2, website,
klausur-service, and many other services. The partial restore attempt
(660295e2) only recovered some files.
This commit restores all missing files from pre-rebase ref 98933f5e
while preserving post-rebase additions (night-scheduler, night-mode UI,
NightModeWidget dashboard integration).
Restored features include:
- AI Module Sidebar (FAB), OCR Labeling, OCR Compare
- GPU Dashboard, RAG Pipeline, Magic Help
- Klausur-Korrektur (8 files), Abitur-Archiv (5+ files)
- Companion, Zeugnisse-Crawler, Screen Flow
- Full backend, studio-v2, website, klausur-service
- All compliance SDKs, agent-core, voice-service
- CI/CD configs, documentation, scripts
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
This commit is contained in:
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backend/compliance/data/README.md
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backend/compliance/data/README.md
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# Compliance Data - Service Module Registry
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Diese Dateien enthalten die Seed-Daten für das Compliance-Modul.
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## Sprint 3: Service-Module Registry
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### Dateien
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- **`service_modules.py`**: Vollständige Registry aller 30+ Breakpilot Services mit:
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- Technische Details (Port, Stack, Repository)
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- Datenkategorien und PII-Verarbeitung
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- Anwendbare Regulierungen (GDPR, AI Act, BSI-TR, etc.)
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- Kritikalität und Ownership
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### Service-Typen
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| Typ | Beschreibung | Beispiele |
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|-----|--------------|-----------|
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| `backend` | API/Backend Services | consent-service, python-backend |
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| `database` | Datenbanken | PostgreSQL, Qdrant, Valkey |
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| `ai` | KI/ML Services | klausur-service, embedding-service |
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| `communication` | Chat/Video | Matrix, Jitsi |
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| `storage` | Speichersysteme | MinIO, DSMS |
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| `infrastructure` | Infrastruktur | Vault, Mailpit, Backup |
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| `monitoring` | Monitoring (geplant) | Loki, Grafana, Prometheus |
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| `security` | Sicherheit | Vault |
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### Relevanz-Stufen
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| Stufe | Bedeutung |
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|-------|-----------|
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| `critical` | Non-Compliance = Shutdown |
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| `high` | Hohes Risiko |
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| `medium` | Mittleres Risiko |
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| `low` | Geringes Risiko |
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### Verwendung
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```python
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from compliance.data.service_modules import (
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BREAKPILOT_SERVICES,
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get_service_count,
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get_services_by_type,
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get_services_processing_pii,
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get_services_with_ai,
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get_critical_services
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)
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# Alle Services
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total = get_service_count()
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# Backend Services
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backends = get_services_by_type("backend")
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# PII-verarbeitende Services
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pii_services = get_services_processing_pii()
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# KI-Services
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ai_services = get_services_with_ai()
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# Kritische Services
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critical = get_critical_services()
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```
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### Seeding
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Services werden automatisch beim ersten Start geseedet:
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```bash
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# Nur Service-Module seeden
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python -m compliance.scripts.seed_service_modules --mode modules
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# Vollständige Compliance-DB seeden
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python -m compliance.scripts.seed_service_modules --mode all
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```
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### Validierung
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Vor dem Seeding können die Daten validiert werden:
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```bash
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python -m compliance.scripts.validate_service_modules
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```
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Prüft:
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- Pflichtfelder vorhanden
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- Keine Port-Konflikte
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- Regulierungen existieren
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- Datenkategorien bei PII-Services
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## Service-Dokumentation
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Jeder Service ist dokumentiert mit:
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1. **Identifikation**
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- `name`: Technischer Name (Docker-Container)
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- `display_name`: Anzeigename
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- `description`: Kurzbeschreibung
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2. **Technische Details**
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- `service_type`: Typ (backend, database, etc.)
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- `port`: Hauptport (falls vorhanden)
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- `technology_stack`: Verwendete Technologien
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- `repository_path`: Pfad im Repository
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- `docker_image`: Docker Image Name
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3. **Datenschutz**
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- `data_categories`: Welche Datenkategorien werden verarbeitet
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- `processes_pii`: Verarbeitet personenbezogene Daten?
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- `processes_health_data`: Verarbeitet Gesundheitsdaten?
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- `ai_components`: Enthält KI-Komponenten?
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4. **Compliance**
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- `criticality`: Kritikalität (critical, high, medium, low)
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- `owner_team`: Verantwortliches Team
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- `regulations`: Liste anwendbarer Regulierungen mit Relevanz
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### Beispiel: consent-service
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```python
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{
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"name": "consent-service",
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"display_name": "Go Consent Service",
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"description": "Kernlogik für Consent-Management, Einwilligungsverwaltung und Versionierung",
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"service_type": "backend",
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"port": 8081,
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"technology_stack": ["Go", "Gin", "GORM", "PostgreSQL"],
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"repository_path": "/consent-service",
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"docker_image": "breakpilot-pwa-consent-service",
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"data_categories": ["consent_records", "user_preferences", "audit_logs"],
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"processes_pii": True,
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"processes_health_data": False,
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"ai_components": False,
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"criticality": "critical",
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"owner_team": "Backend Team",
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"regulations": [
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{"code": "GDPR", "relevance": "critical", "notes": "Art. 7 Einwilligung, Art. 30 VVZ"},
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{"code": "TDDDG", "relevance": "critical", "notes": "§ 25 Cookie-Consent"},
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{"code": "BSI-TR-03161-2", "relevance": "high", "notes": "Session-Management"}
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]
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}
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```
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## Datenbank-Schema
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Die Service-Module werden in folgenden Tabellen gespeichert:
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### `compliance_service_modules`
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Haupttabelle für Services:
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- `id`, `name`, `display_name`, `description`
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- `service_type`, `port`, `technology_stack`
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- `data_categories`, `processes_pii`, `ai_components`
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- `criticality`, `owner_team`
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- `compliance_score` (berechnet)
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### `compliance_module_regulations`
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Mapping Service ↔ Regulation:
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- `module_id`, `regulation_id`
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- `relevance_level` (critical, high, medium, low)
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- `notes`
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- `applicable_articles` (JSON Liste)
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### `compliance_module_risks`
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Service-spezifische Risikobewertungen:
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- `module_id`, `risk_id`
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- `module_likelihood`, `module_impact`
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- `module_risk_level`
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- `assessment_notes`
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## API Endpoints
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Nach dem Seeding stehen folgende Endpoints zur Verfügung:
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```
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GET /api/compliance/modules
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Liste aller Service-Module
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GET /api/compliance/modules/{module_id}
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Details zu einem Service
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GET /api/compliance/modules/{module_id}/regulations
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Anwendbare Regulierungen für einen Service
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GET /api/compliance/modules/{module_id}/compliance-score
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Compliance-Score für einen Service
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```
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## Erweiterung
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Um einen neuen Service hinzuzufügen:
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1. Service zu `BREAKPILOT_SERVICES` in `service_modules.py` hinzufügen
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2. Validierung ausführen: `python -m compliance.scripts.validate_service_modules`
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3. Seeding ausführen: `python -m compliance.scripts.seed_service_modules`
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Oder über die API (wenn aktiviert):
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```bash
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POST /api/compliance/modules
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{
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"name": "new-service",
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"display_name": "New Service",
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...
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}
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```
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## Aktueller Stand (Sprint 3)
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- ✅ 30+ Services dokumentiert
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- ✅ Alle docker-compose.yml Services erfasst
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- ✅ Regulation Mappings definiert
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- ✅ Seeder implementiert
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- ✅ Validierung verfügbar
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- 🔄 Compliance-Score Berechnung (geplant)
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- 🔄 Gap-Analyse pro Service (geplant)
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