feat: V1 Control Enrichment — Eigenentwicklung-Label, regulatorisches Matching & Vergleichsansicht
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863 v1-Controls (manuell geschrieben, ohne Rechtsgrundlage) werden als "Eigenentwicklung" gekennzeichnet und automatisch mit regulatorischen Controls (DSGVO, NIS2, OWASP etc.) per Embedding-Similarity abgeglichen. Backend: - Migration 080: v1_control_matches Tabelle (Cross-Reference) - v1_enrichment.py: Batch-Matching via BGE-M3 + Qdrant (Threshold 0.75) - 3 neue API-Endpoints: enrich-v1-matches, v1-matches, v1-enrichment-stats - 6 Tests (dry-run, execution, matches, pagination, detection) Frontend: - Orange "Eigenentwicklung"-Badge statt grauem "v1" (wenn kein Source) - "Regulatorische Abdeckung"-Sektion im ControlDetail mit Match-Karten - Side-by-Side V1CompareView (Eigenentwicklung vs. regulatorisch gedeckt) - Prev/Next Navigation durch alle Matches Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
This commit is contained in:
@@ -547,6 +547,15 @@ async def atomic_stats():
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}
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@router.get("/controls/v1-enrichment-stats")
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async def v1_enrichment_stats_endpoint():
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"""
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Uebersicht: Wie viele v1 Controls haben regulatorische Abdeckung?
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"""
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from compliance.services.v1_enrichment import get_v1_enrichment_stats
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return await get_v1_enrichment_stats()
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@router.get("/controls/{control_id}")
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async def get_control(control_id: str):
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"""Get a single canonical control by its control_id (e.g. AUTH-001)."""
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@@ -1567,6 +1576,57 @@ async def list_licenses():
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return get_license_matrix(db)
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# =============================================================================
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# V1 ENRICHMENT (Eigenentwicklung → Regulatorische Abdeckung)
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# =============================================================================
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@router.post("/controls/enrich-v1-matches")
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async def enrich_v1_matches_endpoint(
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dry_run: bool = Query(True, description="Nur zaehlen, nicht schreiben"),
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batch_size: int = Query(100, description="Controls pro Durchlauf"),
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offset: int = Query(0, description="Offset fuer Paginierung"),
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):
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"""
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Findet regulatorische Abdeckung fuer v1 Eigenentwicklung Controls.
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Eigenentwicklung = generation_strategy='ungrouped', pipeline_version=1,
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source_citation IS NULL, parent_control_uuid IS NULL.
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Workflow:
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1. dry_run=true → Statistiken anzeigen
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2. dry_run=false&batch_size=100&offset=0 → Erste 100 verarbeiten
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3. Wiederholen mit next_offset bis fertig
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"""
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from compliance.services.v1_enrichment import enrich_v1_matches
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return await enrich_v1_matches(
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dry_run=dry_run,
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batch_size=batch_size,
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offset=offset,
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)
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@router.get("/controls/{control_id}/v1-matches")
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async def get_v1_matches_endpoint(control_id: str):
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"""
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Gibt regulatorische Matches fuer ein v1 Control zurueck.
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Returns:
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Liste von Matches mit Control-Details, Source, Score.
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"""
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from compliance.services.v1_enrichment import get_v1_matches
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# Resolve control_id to UUID
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with SessionLocal() as db:
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row = db.execute(text("""
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SELECT id FROM canonical_controls WHERE control_id = :cid
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"""), {"cid": control_id}).fetchone()
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if not row:
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raise HTTPException(status_code=404, detail=f"Control {control_id} not found")
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return await get_v1_matches(str(row.id))
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# =============================================================================
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# INTERNAL HELPERS
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# =============================================================================
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301
backend-compliance/compliance/services/v1_enrichment.py
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301
backend-compliance/compliance/services/v1_enrichment.py
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@@ -0,0 +1,301 @@
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"""V1 Control Enrichment Service — Match Eigenentwicklung controls to regulations.
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Finds regulatory coverage for v1 controls (generation_strategy='ungrouped',
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pipeline_version=1, no source_citation) by embedding similarity search.
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Reuses embedding + Qdrant helpers from control_dedup.py.
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"""
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import logging
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from typing import Optional
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from sqlalchemy import text
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from database import SessionLocal
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from compliance.services.control_dedup import (
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get_embedding,
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qdrant_search_cross_regulation,
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)
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logger = logging.getLogger(__name__)
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# Similarity threshold — lower than dedup (0.85) since we want informational matches
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V1_MATCH_THRESHOLD = 0.75
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V1_MAX_MATCHES = 5
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def _is_eigenentwicklung_query() -> str:
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"""SQL WHERE clause identifying v1 Eigenentwicklung controls."""
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return """
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generation_strategy = 'ungrouped'
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AND (pipeline_version = '1' OR pipeline_version IS NULL)
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AND source_citation IS NULL
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AND parent_control_uuid IS NULL
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AND release_state NOT IN ('rejected', 'merged', 'deprecated')
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"""
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async def count_v1_controls() -> int:
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"""Count how many v1 Eigenentwicklung controls exist."""
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with SessionLocal() as db:
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row = db.execute(text(f"""
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SELECT COUNT(*) AS cnt
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FROM canonical_controls
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WHERE {_is_eigenentwicklung_query()}
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""")).fetchone()
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return row.cnt if row else 0
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async def enrich_v1_matches(
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dry_run: bool = True,
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batch_size: int = 100,
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offset: int = 0,
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) -> dict:
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"""Find regulatory matches for v1 Eigenentwicklung controls.
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Args:
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dry_run: If True, only count — don't write matches.
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batch_size: Number of v1 controls to process per call.
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offset: Pagination offset (v1 control index).
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Returns:
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Stats dict with counts, sample matches, and pagination info.
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"""
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with SessionLocal() as db:
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# 1. Load v1 controls (paginated)
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v1_controls = db.execute(text(f"""
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SELECT id, control_id, title, objective, category
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FROM canonical_controls
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WHERE {_is_eigenentwicklung_query()}
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ORDER BY control_id
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LIMIT :limit OFFSET :offset
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"""), {"limit": batch_size, "offset": offset}).fetchall()
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# Count total for pagination
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total_row = db.execute(text(f"""
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SELECT COUNT(*) AS cnt
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FROM canonical_controls
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WHERE {_is_eigenentwicklung_query()}
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""")).fetchone()
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total_v1 = total_row.cnt if total_row else 0
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if not v1_controls:
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return {
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"dry_run": dry_run,
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"processed": 0,
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"total_v1": total_v1,
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"message": "Kein weiterer Batch — alle v1 Controls verarbeitet.",
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}
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if dry_run:
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return {
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"dry_run": True,
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"total_v1": total_v1,
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"offset": offset,
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"batch_size": batch_size,
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"sample_controls": [
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{
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"control_id": r.control_id,
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"title": r.title,
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"category": r.category,
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}
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for r in v1_controls[:20]
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],
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}
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# 2. Process each v1 control
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processed = 0
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matches_inserted = 0
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errors = []
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sample_matches = []
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for v1 in v1_controls:
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try:
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# Build search text
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search_text = f"{v1.title} — {v1.objective}"
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# Get embedding
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embedding = await get_embedding(search_text)
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if not embedding:
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errors.append({
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"control_id": v1.control_id,
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"error": "Embedding fehlgeschlagen",
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})
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continue
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# Search Qdrant (cross-regulation, no pattern filter)
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results = await qdrant_search_cross_regulation(
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embedding, top_k=10,
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)
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# Filter: only regulatory controls (with source_citation)
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# and above threshold
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rank = 0
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for hit in results:
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score = hit.get("score", 0)
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if score < V1_MATCH_THRESHOLD:
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continue
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payload = hit.get("payload", {})
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matched_uuid = payload.get("control_uuid")
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if not matched_uuid or matched_uuid == str(v1.id):
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continue
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# Check if matched control has source_citation
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matched_row = db.execute(text("""
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SELECT id, control_id, title, source_citation, severity, category
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FROM canonical_controls
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WHERE id = CAST(:uuid AS uuid)
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AND source_citation IS NOT NULL
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"""), {"uuid": matched_uuid}).fetchone()
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if not matched_row:
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continue
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rank += 1
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if rank > V1_MAX_MATCHES:
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break
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# Extract source info
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source_citation = matched_row.source_citation or {}
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matched_source = source_citation.get("source") if isinstance(source_citation, dict) else None
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matched_article = source_citation.get("article") if isinstance(source_citation, dict) else None
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# Insert match (ON CONFLICT skip)
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db.execute(text("""
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INSERT INTO v1_control_matches
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(v1_control_uuid, matched_control_uuid, similarity_score,
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match_rank, matched_source, matched_article, match_method)
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VALUES
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(CAST(:v1_uuid AS uuid), CAST(:matched_uuid AS uuid), :score,
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:rank, :source, :article, 'embedding')
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ON CONFLICT (v1_control_uuid, matched_control_uuid) DO UPDATE
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SET similarity_score = EXCLUDED.similarity_score,
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match_rank = EXCLUDED.match_rank
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"""), {
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"v1_uuid": str(v1.id),
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"matched_uuid": str(matched_row.id),
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"score": round(score, 3),
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"rank": rank,
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"source": matched_source,
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"article": matched_article,
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})
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matches_inserted += 1
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# Collect sample
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if len(sample_matches) < 20:
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sample_matches.append({
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"v1_control_id": v1.control_id,
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"v1_title": v1.title,
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"matched_control_id": matched_row.control_id,
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"matched_title": matched_row.title,
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"matched_source": matched_source,
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"matched_article": matched_article,
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"similarity_score": round(score, 3),
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"match_rank": rank,
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})
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processed += 1
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except Exception as e:
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logger.warning("V1 enrichment error for %s: %s", v1.control_id, e)
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errors.append({
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"control_id": v1.control_id,
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"error": str(e),
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})
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db.commit()
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# Pagination
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next_offset = offset + batch_size if len(v1_controls) == batch_size else None
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return {
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"dry_run": False,
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"offset": offset,
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"batch_size": batch_size,
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"next_offset": next_offset,
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"total_v1": total_v1,
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"processed": processed,
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"matches_inserted": matches_inserted,
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"errors": errors[:10],
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"sample_matches": sample_matches,
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}
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async def get_v1_matches(control_uuid: str) -> list[dict]:
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"""Get all regulatory matches for a specific v1 control.
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Args:
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control_uuid: The UUID of the v1 control.
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Returns:
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List of match dicts with control details.
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"""
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with SessionLocal() as db:
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rows = db.execute(text("""
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SELECT
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m.similarity_score,
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m.match_rank,
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m.matched_source,
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m.matched_article,
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m.match_method,
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c.control_id AS matched_control_id,
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c.title AS matched_title,
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c.objective AS matched_objective,
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c.severity AS matched_severity,
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c.category AS matched_category,
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c.source_citation AS matched_source_citation
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FROM v1_control_matches m
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JOIN canonical_controls c ON c.id = m.matched_control_uuid
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WHERE m.v1_control_uuid = CAST(:uuid AS uuid)
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ORDER BY m.match_rank
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"""), {"uuid": control_uuid}).fetchall()
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return [
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{
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"matched_control_id": r.matched_control_id,
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"matched_title": r.matched_title,
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"matched_objective": r.matched_objective,
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"matched_severity": r.matched_severity,
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"matched_category": r.matched_category,
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"matched_source": r.matched_source,
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"matched_article": r.matched_article,
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"matched_source_citation": r.matched_source_citation,
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"similarity_score": float(r.similarity_score),
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"match_rank": r.match_rank,
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"match_method": r.match_method,
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}
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for r in rows
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]
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async def get_v1_enrichment_stats() -> dict:
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"""Get overview stats for v1 enrichment."""
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with SessionLocal() as db:
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total_v1 = db.execute(text(f"""
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SELECT COUNT(*) AS cnt FROM canonical_controls
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WHERE {_is_eigenentwicklung_query()}
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""")).fetchone()
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matched_v1 = db.execute(text(f"""
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SELECT COUNT(DISTINCT m.v1_control_uuid) AS cnt
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FROM v1_control_matches m
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JOIN canonical_controls c ON c.id = m.v1_control_uuid
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WHERE {_is_eigenentwicklung_query().replace('release_state', 'c.release_state').replace('generation_strategy', 'c.generation_strategy').replace('pipeline_version', 'c.pipeline_version').replace('source_citation', 'c.source_citation').replace('parent_control_uuid', 'c.parent_control_uuid')}
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""")).fetchone()
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total_matches = db.execute(text("""
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SELECT COUNT(*) AS cnt FROM v1_control_matches
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""")).fetchone()
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avg_score = db.execute(text("""
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SELECT AVG(similarity_score) AS avg_score FROM v1_control_matches
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""")).fetchone()
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return {
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"total_v1_controls": total_v1.cnt if total_v1 else 0,
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"v1_with_matches": matched_v1.cnt if matched_v1 else 0,
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"v1_without_matches": (total_v1.cnt if total_v1 else 0) - (matched_v1.cnt if matched_v1 else 0),
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"total_matches": total_matches.cnt if total_matches else 0,
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"avg_similarity_score": round(float(avg_score.avg_score), 3) if avg_score and avg_score.avg_score else None,
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}
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18
backend-compliance/migrations/080_v1_control_matches.sql
Normal file
18
backend-compliance/migrations/080_v1_control_matches.sql
Normal file
@@ -0,0 +1,18 @@
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-- V1 Control Enrichment: Cross-reference table for matching
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-- Eigenentwicklung (v1, ungrouped, no source) → regulatorische Controls
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CREATE TABLE IF NOT EXISTS v1_control_matches (
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id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
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v1_control_uuid UUID NOT NULL REFERENCES canonical_controls(id) ON DELETE CASCADE,
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matched_control_uuid UUID NOT NULL REFERENCES canonical_controls(id) ON DELETE CASCADE,
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similarity_score NUMERIC(4,3) NOT NULL,
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match_rank SMALLINT NOT NULL DEFAULT 1,
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matched_source TEXT, -- e.g. "DSGVO (EU) 2016/679"
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matched_article TEXT, -- e.g. "Art. 32"
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match_method VARCHAR(30) NOT NULL DEFAULT 'embedding',
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created_at TIMESTAMPTZ DEFAULT NOW(),
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CONSTRAINT uq_v1_match UNIQUE (v1_control_uuid, matched_control_uuid)
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);
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CREATE INDEX IF NOT EXISTS idx_v1m_v1 ON v1_control_matches(v1_control_uuid);
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CREATE INDEX IF NOT EXISTS idx_v1m_matched ON v1_control_matches(matched_control_uuid);
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220
backend-compliance/tests/test_v1_enrichment.py
Normal file
220
backend-compliance/tests/test_v1_enrichment.py
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@@ -0,0 +1,220 @@
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"""Tests for V1 Control Enrichment (Eigenentwicklung matching)."""
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import sys
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sys.path.insert(0, ".")
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import pytest
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from unittest.mock import AsyncMock, MagicMock, patch
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from compliance.services.v1_enrichment import (
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enrich_v1_matches,
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get_v1_matches,
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count_v1_controls,
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)
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class TestV1EnrichmentDryRun:
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"""Dry-run mode should return statistics without touching DB."""
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@pytest.mark.asyncio
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async def test_dry_run_returns_stats(self):
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mock_v1 = [
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MagicMock(
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id="uuid-v1-1",
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control_id="ACC-013",
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title="Zugriffskontrolle",
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objective="Zugriff einschraenken",
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category="access",
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),
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MagicMock(
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id="uuid-v1-2",
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control_id="SEC-005",
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title="Verschluesselung",
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objective="Daten verschluesseln",
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category="encryption",
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),
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]
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mock_count = MagicMock(cnt=863)
|
||||
|
||||
with patch("compliance.services.v1_enrichment.SessionLocal") as mock_session:
|
||||
db = MagicMock()
|
||||
mock_session.return_value.__enter__ = MagicMock(return_value=db)
|
||||
mock_session.return_value.__exit__ = MagicMock(return_value=False)
|
||||
# First call: v1 controls, second call: count
|
||||
db.execute.return_value.fetchall.return_value = mock_v1
|
||||
db.execute.return_value.fetchone.return_value = mock_count
|
||||
|
||||
result = await enrich_v1_matches(dry_run=True, batch_size=100, offset=0)
|
||||
|
||||
assert result["dry_run"] is True
|
||||
assert result["total_v1"] == 863
|
||||
assert len(result["sample_controls"]) == 2
|
||||
assert result["sample_controls"][0]["control_id"] == "ACC-013"
|
||||
|
||||
|
||||
class TestV1EnrichmentExecution:
|
||||
"""Execution mode should find matches and insert them."""
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_processes_and_inserts_matches(self):
|
||||
mock_v1 = [
|
||||
MagicMock(
|
||||
id="uuid-v1-1",
|
||||
control_id="ACC-013",
|
||||
title="Zugriffskontrolle",
|
||||
objective="Zugriff auf Systeme einschraenken",
|
||||
category="access",
|
||||
),
|
||||
]
|
||||
|
||||
mock_count = MagicMock(cnt=1)
|
||||
mock_matched_row = MagicMock(
|
||||
id="uuid-reg-1",
|
||||
control_id="SEC-042",
|
||||
title="Verschluesselung personenbezogener Daten",
|
||||
source_citation={"source": "DSGVO (EU) 2016/679", "article": "Art. 32"},
|
||||
severity="high",
|
||||
category="encryption",
|
||||
)
|
||||
|
||||
mock_qdrant_results = [
|
||||
{
|
||||
"score": 0.89,
|
||||
"payload": {
|
||||
"control_uuid": "uuid-reg-1",
|
||||
"control_id": "SEC-042",
|
||||
"title": "Verschluesselung",
|
||||
},
|
||||
},
|
||||
{
|
||||
"score": 0.65, # Below threshold
|
||||
"payload": {
|
||||
"control_uuid": "uuid-reg-2",
|
||||
"control_id": "SEC-100",
|
||||
},
|
||||
},
|
||||
]
|
||||
|
||||
with patch("compliance.services.v1_enrichment.SessionLocal") as mock_session:
|
||||
db = MagicMock()
|
||||
mock_session.return_value.__enter__ = MagicMock(return_value=db)
|
||||
mock_session.return_value.__exit__ = MagicMock(return_value=False)
|
||||
|
||||
# Multiple execute calls: v1 list, count, matched_row lookup, insert
|
||||
call_count = [0]
|
||||
def side_effect_execute(query, params=None):
|
||||
call_count[0] += 1
|
||||
result = MagicMock()
|
||||
# fetchall for v1 controls list
|
||||
result.fetchall.return_value = mock_v1
|
||||
# fetchone for count and matched row
|
||||
if "COUNT" in str(query):
|
||||
result.fetchone.return_value = mock_count
|
||||
elif "source_citation IS NOT NULL" in str(query):
|
||||
result.fetchone.return_value = mock_matched_row
|
||||
else:
|
||||
result.fetchone.return_value = mock_count
|
||||
return result
|
||||
|
||||
db.execute.side_effect = side_effect_execute
|
||||
|
||||
with patch("compliance.services.v1_enrichment.get_embedding") as mock_embed, \
|
||||
patch("compliance.services.v1_enrichment.qdrant_search_cross_regulation") as mock_qdrant:
|
||||
mock_embed.return_value = [0.1] * 1024
|
||||
mock_qdrant.return_value = mock_qdrant_results
|
||||
|
||||
result = await enrich_v1_matches(dry_run=False, batch_size=100, offset=0)
|
||||
|
||||
assert result["dry_run"] is False
|
||||
assert result["processed"] == 1
|
||||
assert result["matches_inserted"] == 1
|
||||
assert len(result["sample_matches"]) == 1
|
||||
assert result["sample_matches"][0]["matched_control_id"] == "SEC-042"
|
||||
assert result["sample_matches"][0]["similarity_score"] == 0.89
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_empty_batch_returns_done(self):
|
||||
mock_count = MagicMock(cnt=863)
|
||||
|
||||
with patch("compliance.services.v1_enrichment.SessionLocal") as mock_session:
|
||||
db = MagicMock()
|
||||
mock_session.return_value.__enter__ = MagicMock(return_value=db)
|
||||
mock_session.return_value.__exit__ = MagicMock(return_value=False)
|
||||
db.execute.return_value.fetchall.return_value = []
|
||||
db.execute.return_value.fetchone.return_value = mock_count
|
||||
|
||||
result = await enrich_v1_matches(dry_run=False, batch_size=100, offset=9999)
|
||||
|
||||
assert result["processed"] == 0
|
||||
assert "alle v1 Controls verarbeitet" in result["message"]
|
||||
|
||||
|
||||
class TestV1MatchesEndpoint:
|
||||
"""Test the matches retrieval."""
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_returns_matches(self):
|
||||
mock_rows = [
|
||||
MagicMock(
|
||||
matched_control_id="SEC-042",
|
||||
matched_title="Verschluesselung",
|
||||
matched_objective="Daten verschluesseln",
|
||||
matched_severity="high",
|
||||
matched_category="encryption",
|
||||
matched_source="DSGVO (EU) 2016/679",
|
||||
matched_article="Art. 32",
|
||||
matched_source_citation={"source": "DSGVO (EU) 2016/679"},
|
||||
similarity_score=0.89,
|
||||
match_rank=1,
|
||||
match_method="embedding",
|
||||
),
|
||||
]
|
||||
|
||||
with patch("compliance.services.v1_enrichment.SessionLocal") as mock_session:
|
||||
db = MagicMock()
|
||||
mock_session.return_value.__enter__ = MagicMock(return_value=db)
|
||||
mock_session.return_value.__exit__ = MagicMock(return_value=False)
|
||||
db.execute.return_value.fetchall.return_value = mock_rows
|
||||
|
||||
result = await get_v1_matches("uuid-v1-1")
|
||||
|
||||
assert len(result) == 1
|
||||
assert result[0]["matched_control_id"] == "SEC-042"
|
||||
assert result[0]["similarity_score"] == 0.89
|
||||
assert result[0]["matched_source"] == "DSGVO (EU) 2016/679"
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_empty_matches(self):
|
||||
with patch("compliance.services.v1_enrichment.SessionLocal") as mock_session:
|
||||
db = MagicMock()
|
||||
mock_session.return_value.__enter__ = MagicMock(return_value=db)
|
||||
mock_session.return_value.__exit__ = MagicMock(return_value=False)
|
||||
db.execute.return_value.fetchall.return_value = []
|
||||
|
||||
result = await get_v1_matches("uuid-nonexistent")
|
||||
|
||||
assert result == []
|
||||
|
||||
|
||||
class TestEigenentwicklungDetection:
|
||||
"""Verify the Eigenentwicklung detection query."""
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_count_v1_controls(self):
|
||||
mock_count = MagicMock(cnt=863)
|
||||
|
||||
with patch("compliance.services.v1_enrichment.SessionLocal") as mock_session:
|
||||
db = MagicMock()
|
||||
mock_session.return_value.__enter__ = MagicMock(return_value=db)
|
||||
mock_session.return_value.__exit__ = MagicMock(return_value=False)
|
||||
db.execute.return_value.fetchone.return_value = mock_count
|
||||
|
||||
result = await count_v1_controls()
|
||||
|
||||
assert result == 863
|
||||
# Verify the query includes all conditions
|
||||
call_args = db.execute.call_args[0][0]
|
||||
query_str = str(call_args)
|
||||
assert "generation_strategy = 'ungrouped'" in query_str
|
||||
assert "source_citation IS NULL" in query_str
|
||||
assert "parent_control_uuid IS NULL" in query_str
|
||||
Reference in New Issue
Block a user