3 Commits

Author	SHA1	Message	Date
Benjamin Admin	575644c9c5	feat(audit): P8 — MC-Severity raus, Email nur harte Findings, MC-Audit als Checkliste ... Email-Hardening (mc_scorecard.top_fails): Neue _is_hard_finding-Heuristik filtert konditionale MCs ohne Negativ-Beleg aus den Top-Auffaelligkeiten. matched_text leer + Label enthaelt "falls/sofern/wenn/soweit/ggf." -> raus, landet nur noch im MC-Audit als "selbst pruefen". DATA-2066-A05 (kostenfreie Abschaltung Standortdaten) ist das prototypische Beispiel. MC-Audit-Frontend (audit/[checkId]/page.tsx): Severity-Spalte (CRITICAL/HIGH/MEDIUM/LOW) entfernt — der MC-Audit ist eine Checkliste, keine Severity-Drohung. Stattdessen: - Spalte "Prioritaet" mit 3-Tier aus regulation-Mapping: Gesetz (DSGVO/ePrivacy/TDDDG/...) / Behoerden-Leitlinie (EDPB/DSK/EuGH/...) / Best-Practice (ISO/NIST/BSI) - 3-Status: erfuellt (✓) / nicht erfuellt (✗) / selbst pruefen (?) / nicht anwendbar (—). rowReviewStatus() leitet "selbst pruefen" aus matched_text-leer + konditionalem Label ab. - Filter umgebaut auf 5 Stati statt 4 - Default-Filter "Nicht erfuellt" (vorher "Nur Fail") Bonus: f.payload.risk_label TS-Cast im FindingsTab clean gemacht (unknown -> string). Effekt: - Email an die GF zeigt nur noch echte Belege ("DSB fehlt", "Gebuehr fuer Widerruf") - MC-Audit ist eine sachliche Pruefliste fuer den Compliance-Officer Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>	2026-05-19 00:30:04 +02:00
Benjamin Admin	662327e8b4	feat(compliance-check): MC-Classification + Embedding + Vendor-Redundanz + Action-Recipes + Borlabs-Features ... Massiv-Update auf Basis BMW-Test-Iterationen (v1→v9): Core Compliance-Check - Sonnet check_type Klassifikation: text/process/review fuer alle 1874 MCs in compliance.doc_check_controls (script + Sidecar /data/mc_classification.db). rag_document_checker filtert auf check_type='text' fuer doc_check. Plus fits_doc_type-Audit (v2) + ui_only-Audit fuer DSA/E-Commerce-MCs in falscher doc_type-Schublade. - scope_requires-Filter: biometric/ai_decision/child_targeting MCs werden per business_profile gefiltert (FRT skipped fuer BMW etc.). - Embedding-Match (BGE-M3) als Phase-3 nach Regex-Match: Per-doc_type-Threshold-Override (impressum 0.50, dse/cookie 0.60), Short-Field-Rescue (15-Wort-Chunks) fuer Pflichtfelder im Impressum. Title+check_question als Embedding-Input fuer mehr Kontext. - Cookie-Text-Routing: consent-tester gibt cmp_cookie_text aus dem CMP-Reconstruct zurueck, Backend bevorzugt das gegen DOM-Extraction wenn richer (BMW 1824 vs 600 Worte). Vendor-Redundanz + EU-Alternativen + Cost-Saving - vendor_redundancy.analyze() — funktionale Kategorisierung der CMP-Vendors, Detektion von Mehrfach-Anbietern pro Kategorie, EU-Alternative-Lookup (Matomo, IONOS, HERE, Friendly Captcha, Smart AdServer, ...). - vendor_cost_estimator: Tier-Inferenz aus Cookie-Footprint (Cookie-Anzahl + Premium-Feature-Cookies + Third-Party-Quote → starter/professional/ enterprise/premier). - Self-Service-Werbung (Google/Meta/Pinterest/...) = 0 Lizenz-Kosten (nur Media-Spend, separat). DSP-Plattformen behalten enge Range. - Tier-aware Saving-Range: bei Enterprise/Premier nutzen wir den oberen 40-100%-Band der Listpreise, nicht starter→premier. - Multi-Function-Tools (Matomo Pro, SAP CX, IONOS Cloud, Userlike, Smart AdServer, HERE Maps, Vimeo Pro, LamaPoll) — ein Tool ersetzt mehrere Kategorien gleichzeitig. Cookie-Wissens-DB + Funktionale Klassifikation - cookie_knowledge_db: 50 kuratierte Top-Cookies (Google/Meta/Adobe/MS/...) mit vendor, exact_purpose, data_collected, IAB-TCF-IDs, reid_risk, schrems_ii_status, EuGH-Urteile, EU-Alternative. - cookie_function_classifier: pro Cookie funktionale Rolle (tracking_id, ad_pixel, session_id, ab_test, csrf, ...) + blocking_impact. Country-Inferenz aus Rechtsform - cookie_link_validator: Country-Field wird aus Vendor-Name abgeleitet (A/S=DK, GmbH=DE, Inc=US, B.V.=NL, ...) plus Vendor-Lookup-Table. Reduziert false-positive no_country-Flags bei eindeutig-EU-Vendors (Adform DK, Pinterest IE). Action-Recipes + Doc-Anchor-Locator - finding_action_recipes: pro Finding-Typ (no_cookies_listed, no_country, broken_opt_out, "Auftragsverarbeiter erwaehnen", "Art. 22 Profiling", ...) eine strukturierte Anweisung mit what/why/fix_text/where/example. Zum 1:1-Einfuegen in Kunden-Dokumente. - doc_anchor_locator: Embedding-basiert (BGE-M3 cosine) — sucht den passenden Absatz im existierenden Kundendokument fuer jeden Finding. Per-Run Thread-Local-Cache. Fallback: keyword-Match. - Email-Rendering integriert Recipe + Anchor pro Doc-Pruefungs-Fail + Vendor-Flag-Liste mit aufklappbarer Action-Liste. - Score-Erklaerung pro Vendor-Zeile (3/5-Untertitel + Tooltip). Migration-Pipeline (Compliance-Check -> Customer Banner/Documents) - migration_to_banner.py: Vendor-Liste -> CookieBannerConfig mit 4 Kategorien + Review-Flags. - migration_to_document.py: Vendor-Liste -> Cookie-Policy + VVT-Register + Privacy-Policy-Pre-Fills. - agent_migration_routes: 3 Preview-Endpoints (banner-preview, document-preview, summary). Persistierung der cmp_vendors in /data/compliance_audits.db check_payloads-Tabelle. Borlabs-Parity Cookie-Banner-Features - Consent-Historie im Banner: window.bpShowConsentHistory() + localStorage. - Content-Blocker: cookie-banner-content-blocker.ts — YouTube/Maps/Video Placeholder bis Einwilligung. - Google Consent Mode v2 erweitert: wait_for_update + region=EEA/CH/GB. - Consent-Log Export (CSV/JSON) per einwilligungen_export_routes. Bug-Fixes - canonical_control_routes: _jsonish-Helper fuer string-typed jsonb, similar-controls-Endpoint mit _has_embedding_col()-Cache (kein 500 mehr). - Control-Library Frontend: defensive .map-Coercer in 2 Detail-Views. - Embedding-Service-Batching (32er Batches statt 165 in einem Call). - KeyError 'control_id' in MC-Result-Aggregation (defensive .get). - Master-Controls-Klick-Through von /sdk/master-controls auf /sdk/control-library?control=<id> mit URL-Param-Auto-Open. - Dockerfile: /data pre-chowned auf appuser (Audit-DB-Schreibrecht). - Cookie-Text-Routing-Bug (cmp_reconstructed > DOM-extraction). - doc_type-aware MC-Filter (statt all-text-MCs). - Master-Contract-Dedup (60 BMW-Internal-Eintraege = 1 Adobe-Vertrag). - A3-v2-Audit hat 24 UI-Sprache-MCs als 'process' reklassifiziert. Tests - test_migration_mappers.py (9 Tests) - test_migration_endpoints.py (4 Tests) Skripte (one-shot) - classify_mc_check_type.py (v1) + _v2 (PK=control_id,doc_type) - audit_mc_doctype_fit.py (v1 fits) + _v2 (ui_only + scope_requires) BMW-Run-Bilanz v1 (broken) -> v9 (alle Fixes): DSE 7,5% -> 81-83% Impressum 4% -> 100% (6 echte MCs alle erfuellt) Cookie 0% -> 79-83% (CMP-Text-Routing + Embedding) Plus: 10 Konsolidierungs-Kategorien, geschaetzte Saving 200k-3M / Jahr Plus: Action-Recipes + Doc-Anchors fuer jeden Fail Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>	2026-05-18 18:30:08 +02:00
Benjamin Admin	6ed30dae5b	feat(agent): MC scorecard + audit drill-down + tenant trend (A1-A6) ... Now that all 1874 MCs run per check (Task #30 cap removal), the report was about to drown in noise. This commit adds the full aggregation / persistence / drill-down stack so each MC is actionable, not just counted. A1 mc_scorecard.py (new): build_scorecard(checks) -> per-regulation PASS/FAIL/SKIP + severity top_fails(checks, n) -> N most severe failed MCs full_audit_records(...) -> flat rows ready for sidecar SQLite A2 Email rendering: agent_doc_check_scorecard.py (new) builds an HTML scorecard table (regulation × passed/failed/HIGH/MEDIUM/score) shown at the top of the email. agent_doc_check_report._render_document now collapses the 500-MC L2 forest into 'X/Y bestanden (Z Fail)' summary plus a top-10 fails block per doc — old verbose render is gone. A3 compliance_audit_log.py (new) — sidecar SQLite at /data/compliance_audits.db (separate from compliance Postgres schema to comply with the no-new-migrations rule in CLAUDE.md): check_runs(check_id, ts, tenant_id, site_name, base_domain, doc_count, scorecard json, vvt_summary json) mc_results(check_id, doc_type, mc_id, label, passed, skipped, severity, regulation, matched_text, hint) Route persists every run after the email is sent. docker-compose.yml adds compliance-audit volume + env. A4 backfill_mc_regulation_llm.py (new) — Qwen-tagged backfill for the 1636 MCs the regex pass couldn't classify. Batches of 25, format=json, output constrained to the canonical regulation list. Run manually: docker exec bp-compliance-backend python3 \ /app/scripts/backfill_mc_regulation_llm.py [--dry-run] A5 Admin audit tab — GET /api/compliance/agent/audit/<check_id> proxied via /api/sdk/v1/agent/audit/<id>. New page /sdk/agent/audit/[checkId] renders scorecard + filterable MC table (status / doc_type / regulation, expandable rows with matched_text + hint). ComplianceCheckTab now shows 'Voll-Audit oeffnen' link. A6 Trend per tenant — GET /api/compliance/agent/audit/tenant/<id> returns recent runs. Email scorecard shows per-regulation delta badges ('(+12%)', '(-3%)') compared with the previous run for the same tenant + base_domain. Lookup is one SQLite query. Plumbing: rag_document_checker.py — SELECT now includes 'article'; MC results carry 'regulation' + 'article' through to CheckItem. agent_doc_check_routes.CheckItem schema gains regulation + article fields (defaults '') so old clients still parse. agent_compliance_check_routes — response gains 'check_id' so the frontend can build the audit link.	2026-05-17 13:45:58 +02:00