9 Commits

Author	SHA1	Message	Date
Benjamin Admin	603381a67f	feat(audit-mail): P58/P59c/P60b/P61/P62 — Mercedes-Cycle Phase 1 abgeschlossen ... P58 Anti-Audit-Detection robuster (script-domain + settings-spezifisch — war bereits im Code, jetzt sauber als completed dokumentiert). P59c DACH-Custom-Cookies in compliance.cookie_library: Borlabs, etracker, Matomo/Piwik, Userlike, Cookiebot/Cookieyes/Usercentrics, Akamai/Cloudflare/Datadome Bot-Manager + HubSpot. 21 neue Eintraege (3 von 24 schon via Open-Cookie-Database vorhanden). Script: backend-compliance/scripts/seed_dach_cookies.py. P60b Vendor-Pattern-Dedupe mit Fuzzy-Match (Jaccard >= 0.7) statt exakter Tuple-Equality. Vendors mit teilweise befuellten Feldern (z.B. Sitzland eingetragen) fallen nicht mehr aus der globalen Notice — Bug: Amazon/Psyma/Qualtrics hatten zuvor wiederholte per-row Actions. P61 "Untergeschobene Cookies"-Erkennung — wenn ein deklarierter Vendor (z.B. Google Tag Manager) automatisch weitere mitbringt (GA + GCL_AU + DoubleClick), werden diese als separater Mail-Block (gelb) mit COOKIE/VENDOR-Badges + Quellen-Doku ausgewiesen. Neuer Service: compliance.services.vendor_package_cookies (8 Primary-Vendors mit je 2-4 implicit Cookies/Vendors). P62 Marketing-Manager-Disclaimer "Was wir sehen / nicht sehen" als blauer Box-Block direkt unter dem Critical-Findings-Block. Erklaert Grenzen unseres Audits (Server-Side-Tracking, Vendor-interne Datenweitergabe, Cross-Page-Banner) und Risiko des Falschvertrauens in einen 100%-Score. Neuer Renderer: compliance.api.scope_disclaimer. Architektur: VVT-Tabellen-Renderer aus agent_doc_check_extras.py (552 LOC -> 242 LOC) in compliance.api.vvt_table_renderer ausgelagert, um den 500-LOC-Hardcap einzuhalten. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>	2026-05-21 08:01:27 +02:00
Benjamin Admin	57c0f940a2	feat(consent+report): P56-P67 Mercedes-Audit-Cycle (Anti-Audit, Phase G Vendors, Cookie-Behavior-Validator + 5 Mail-Polish-Items) [migration-approved] ... P56 Anti-Auditing-Detection als constructive Compliance-Finding (Audit-API- Empfehlung statt Anklage, weil Mercedes berechtigt Bots blockiert) P57 Phase G vendor_details Union mit cmp_vendors -> 42 Anbieter sichtbar P58 Anti-Audit-Detection robuster (Script-Domain-Check + Settings-spezifisch) P59 Cookie-Behavior-Validator (4 Layer, 3-Tier-Severity: MEDIUM=Kategorie- Mismatch / HIGH=Zweck-Mismatch / CRITICAL=beide=Vorsatz-Indiz) + Open Cookie Database (CC0) als Library-Seed (2264 Cookies) P59b Cookie-Behavior in Banner-Check verdrahtet + Mail-Block (BUGFIX: SessionLocal selbst oeffnen, db war im Background-Task nicht im Scope) Mail-Polish nach Mercedes-Review: P63 Banner-Footer-Links auch im wb7-link/role=link erkennen (Shadow-DOM- Walker label-based statt nur <a href>) P64 Re-Access-Severity: MEDIUM statt HIGH, wenn Footer "Einstellungen" oder Mercedes-typisch existiert; OEM-Footer-Detection (wb7-footer) P65 Text-Truncation: Word-Boundary statt Zeichen-Cut (kein "einfa"-Bruch mehr in Sofortmassnahmen) P66 GF-Aktionen: Service-Zweck vs Cookie-Zweck explizit erklaert (haeufige Verwechslung Marketing/GF: "Akamai-Beschreibung" != Cookie- Zweck pro DSK-OH 2024) P67 Stirring-Finding mit "Verlust-Framing"-Erklaerung + Alt-vs-Neutral- Beispiel, statt nur EDPB-Fachbegriff Compliance-Advisor FAQ (admin agent-core/soul): + CNIL/EDPB Top-Bussgelder (Google 100M, Meta 60M, Amazon 35M) + Deutsche Praezedenz (LG Muenchen Google Fonts, EuGH Planet49, BGH I ZR 7/16) + 4 Risiko-Pfade (Bussgeld/Abmahnung/Sammelklage/NOYB) + Berechnungs-Methodik Document-Generator Templates: AGB-DE (142), Impressum (140), Widerrufs- formular-Anlage (143), DSR-Process-Dedup (139), Cookie-Library (144). Architektur: doc_action_mappings.py + banner_dom_walkers.py + cookie_behavior_validator.py + vendor_detail_extractor.py rausgezogen, um die 500-LOC-Caps in agent_doc_check_report.py und banner_text_checker.py einzuhalten. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>	2026-05-21 06:28:25 +02:00
Benjamin Admin	6c223c7c9b	feat(compliance-check): exec-summary + voll-audit + TDM-respect + cookie-KB-extended + saving-scan-funnel ... P1 — Exec-Summary oben im Email-Report (4 KPIs + 2 CTAs, dunkler Gradient) P3 — no_direct_sales-Flag fuer OEM-Konfigurator-Sites; AGB/Widerruf/AGB als "NICHT ANWENDBAR" (grau) statt "NICHT GEFUNDEN" (rot) P5 — Voll-Audit Unification: alle Findings (MC + Pflichtangaben + Vendor + Redundanz) in /data/compliance_audits.db.unified_findings; neuer /api/compliance/agent/findings/<id> Endpoint + FindingsTab im Audit-UI mit Filter + CSV-Export P7 — Crawl-Hardening: TDM-Reservation-Check (robots.txt / ai.txt / Header / Meta) vor jedem Run mit 24h-Cache; HeadlessChrome-UA (Firma noch nicht gegruendet — Switch via BREAKPILOT_BRANDED_UA env); per-Domain Rate-Limit 1 req/s + max 2 concurrent P2 — Cookie-Knowledge-DB additiv erweitert (35 -> 74 Cookies): Adobe, Meta, Microsoft, LinkedIn, TikTok, HubSpot, Marketo, Salesforce, Hotjar, FullStory, Mouseflow, Intercom, Drift, Zendesk, Cloudflare, Stripe, OneTrust/Cookiebot/Usercentrics, Matomo, Pinterest, Snapchat, X/Twitter, YouTube, Vimeo, Klaviyo, Mailchimp, Mixpanel, Segment, Amplitude, Optimizely, Datadog; Wire-in in cookie_function_classifier liefert compliance_risk-Label (kritisch/hoch/mittel/gering) pro Vendor A — k-Anonymitaets-Helper (benchmark_k_anonymity) fuer P6-Vorbereitung B — Cross-Tenant-Domain-Assertion im /findings-Endpoint (expected_domain Query-Param -> 403 bei Mismatch) C — Saving-Scan-Funnel: /api/compliance/agent/saving-scan/start mit Validierung + 24h-Rate-Limit pro Domain + Lead-Persistenz in saving_scan_leads + Auto-Discovery via _run_compliance_check; 6 Tests D — Risk-Badge im Email-Vendor-Row Rechtliche Leitplanken (Memory feedback_oem_data_legal.md): nur eigene Knapp-Bewertungen + Source-Pointer, keine 1:1-Kopien fremder CMP-Texte. TDM-Opt-Out-Respect nach § 44b UrhG. KEINE Schema-Aenderungen — alles in Sidecar-SQLite. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>	2026-05-18 23:48:34 +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	6d29191e9b	fix(vvt): score INTERNAL/GROUP without opt-out/privacy penalty ... User feedback after BMW test: - 60 'BMW AG — XYZ' rows were rendered as ✗ for Opt-Out/Privacy and scored 38-52%. That's misleading: BMW processing for itself doesn't need a separate opt-out URL (cookie-banner is the consent mechanism) or a separate privacy policy (main DSI covers it). - Title 'Anbieter' was wrong for 60 of 90 rows (internal services). Three orthogonal fixes: 1. score_vendors becomes recipient_type aware: - INTERNAL/GROUP_COMPANY: opt_out_url, privacy_policy_url, country are NOT required (the user's main DSI + cookie-banner cover them). What IS required: name, purpose, cookies disclosed with name + expiry. Cookies-disclosure weight raised to 50 (was 15) so the VVT-relevant data is the score driver. - 'necessary' category: opt-out still skipped (§25 Abs. 2 TDDDG). - External (PROCESSOR/CONTROLLER): existing strict scoring stays. 2. _link_status_badge accepts na_label and renders a neutral em-dash with explanation tooltip instead of red ✗ when the column doesn't apply to that row. _render_vendor_row_full passes na_label based on recipient_type: - INTERNAL/GROUP -> 'Nicht erforderlich (eigene Verarbeitung)' - necessary -> 'Nicht erforderlich (§25 Abs. 2 TDDDG)' 3. Header + summary clarify the split: - h3 changed to 'Verarbeitungstaetigkeiten und Empfaenger aus der Cookie-Richtlinie' (was 'Drittanbieter aus Cookie-Richtlinie'). - Top line: '90 Verarbeitungen erfasst — 60 eigene + 30 externe Empfaenger'. - Disclaimer below: explains the INTERNAL/GROUP exemption so the reader understands why those rows don't show ✗ for missing URLs. - Section labels enriched with the relevant DSGVO article: 'Eigene Verarbeitungstaetigkeiten — fuer das VVT (Art. 30)', 'Auftragsverarbeiter — AVV erforderlich (Art. 28)', 'Joint Controller — Vereinbarung pruefen (Art. 26)'. Expected BMW result after fix: ~85% of the 60 BMW-AG rows jump from ~52% to 90-100% (the real issue, fehlende Cookies-Disclosure, stays flagged). The only true findings remaining are external links that return 4xx (e.g. Criteo 403, Teads 404).	2026-05-17 13:15:40 +02:00
Benjamin Admin	fab1e35847	feat(vvt): recipient-type classification + 3-section VVT table ... Per user request: BMW (and others) put their own services AND external vendors in the same cookie-policy widget. The VVT-Tabelle now groups them by Art. 30(1)(d) DSGVO recipient category so the DSB can act on the right buckets: - INTERNAL — owner processing for itself ('BMW AG — XYZ') - GROUP_COMPANY — same brand family, different legal entity ('BMW Bank') - PROCESSOR — Auftragsverarbeiter, AVV-pflichtig (Adobe, Akamai) - CONTROLLER — independent / joint controller (Meta Pixel, Google Ads, LinkedIn — they run their own profiles) - AUTHORITY — government bodies (rare in cookies) - OTHER — fallback New module vendor_classifier.py: - owner_from_url(url) — derive site-owner token (bmw.de -> 'BMW', mercedes-benz.de -> 'Mercedes-Benz') - classify(name, category, owner) — strict 5-tier heuristic: * INTERNAL: vendor name first-token is '<Owner>' / '<Owner> AG' / '<Owner> SE' / '<Owner> GmbH' / '<Owner> AG & Co. KG' * GROUP_COMPANY: starts with '<Owner> ' but isn't '<Owner> AG' * CONTROLLER: matches a known joint-controller list (Meta, Google Ads, YouTube, LinkedIn Insight, TikTok, Pinterest, Taboola, Outbrain, Criteo, Twitter, Reddit, ...) * PROCESSOR: legal-form suffix in name (GmbH, AG, Inc., A/S, B.V., S.A., Ltd., LLC, ...) * OTHER: anything else vendor_extractor.extract_vendors_from_payloads now takes owner_name: - Passes it through to classify() for every extracted vendor record - The route derives owner_name via _company_name_from_url(doc_entries) - LLM-extracted vendors are classified the same way (so V3 fallback also produces tagged records) agent_doc_check_extras.build_vvt_table_html rewritten: - Buckets vendors by recipient_type - Renders one section per non-empty bucket, in canonical order (RECIPIENT_TYPE_SECTIONS), each with section header + count + bad count + nested table - Within each section: sorted by compliance_score ascending - Response JSON cmp_vendors includes recipient_type so the frontend can later import per-category into the VVT module Expected BMW result: ~60 INTERNAL rows (BMW AG own services), ~25 PROCESSOR rows (Adobe, Adform, Akamai, AWS, ...), ~5 CONTROLLER rows (Meta Pixel, Google, LinkedIn, Pinterest, Outbrain, Taboola).	2026-05-17 12:31:49 +02:00
Benjamin Admin	ea4dbb223f	feat(vvt): per-vendor extraction + opt-out check + VVT table in email (V1) ... When a known CMP (ePaaS, OneTrust) renders the cookie policy, we now extract structured vendor records, probe their opt-out + privacy URLs, score each vendor (0-100), and append a 'VVT-Vorschlag' table to the compliance email — one row per vendor, sortable by compliance score. consent-tester: - DSIDiscoveryResult.cmp_payloads: surfaces raw CMP JSON to callers - DSIDiscoveryResponse: new cmp_payloads field - discover_dsi_documents sets cmp_payloads from cmp_capture - cmp_library/{epaas,onetrust}.py: new extract_vendors(d) returning list[VendorRecord] backend: - _fetch_text() now returns (text, cmp_payloads) tuple - doc_entries store cmp_payloads per doc (mostly cookie) - _autodiscover_missing forwards homepage payloads to the cookie entry - New module vendor_extractor.py: dispatches ePaaS/OneTrust/generic schemas; dedupes vendors across multiple payloads - cookie_link_validator.py extended with validate_vendor_urls(vendors) and score_vendors(vendors) — 0-100 score per vendor based on name, purpose, country, opt-out reachable, privacy URL reachable, cookies with names + expiry - agent_doc_check_extras.build_vvt_table_html: renders the table - Route appends VVT HTML after the provider list, before the document-by-document report - Response JSON gains cmp_vendors for future frontend rendering Example for BMW: ~30 ePaaS providers → table with Name | Kategorie | Sitz | Cookies | Opt-Out (✓/✗) | Privacy (✓/✗) | Score. Sorted by score ascending so the worst-compliant vendors are at the top.	2026-05-17 09:50:11 +02:00
Benjamin Admin	525038359a	feat(compliance-check): auto-discover missing doc types from homepage ... When the user leaves some doc-type rows empty, the tool now actively searches the website for them — only marks 'not found' as last resort. Flow: 1. User submits N URLs (e.g. just DSI) 2. For each canonical doc_type with no submitted URL/text, the route identifies the most-common base (scheme://netloc) from submitted URLs 3. Calls consent-tester /dsi-discovery on the homepage with max_documents=15 (180s timeout) 4. Classifies every discovered doc into a canonical doc_type via title/URL keyword rules (_DISCOVERY_RULES — covers cookie/widerruf/ social_media/agb/nutzungsbedingungen/dsb/impressum/dse) 5. Fills matching empty entries with the discovered text, marks auto_discovered=True and discovery_attempted=True Padding now differentiates: - 'Auf der Website nicht gefunden' — discovery was attempted, no doc matched. Amber badge, friendly hint to add URL manually. - 'Nicht eingereicht — Quelle nicht angegeben' — user gave NO URLs at all, nothing to crawl from. Grey badge. Email + frontend: - Status labels: NICHT GEFUNDEN (amber) vs NICHT EINGEREICHT (grey) - 'Gepruefte Quellen' table tags auto-discovered URLs with a small blue 'auto-entdeckt' badge so GF sees what tool found vs user submitted. Implementation only runs when ≥1 URL was submitted (no base to crawl from otherwise). Adds 30-90s for unsubmitted types but avoids the 'just say nicht gefunden' anti-pattern.	2026-05-17 01:14:05 +02:00
Benjamin Admin	e61e9d9e2a	feat(agent): progress_pct + 6 BMW-Run Verbesserungen ... Backend (agent_compliance_check_routes.py): - progress_pct (0-100%) im Job-State, ueber alle Phasen verteilt (Laden 0-30, Profil 35-40, Pruefen 40-80, Banner 80-92, Report 95-100) - Status-Texte vereinheitlicht ("Texte laden X/N", "Pruefen X/N") - Firmenname fuer Email-Subject jetzt aus URL abgeleitet (bmw.de -> "BMW", mercedes-benz.de -> "Mercedes-Benz") statt unzuverlaessigem extracted_profile.companyName (matchte oft juris.de) - E-Mail-Report enthaelt jetzt Banner+TCF-Vendor-Liste (build_provider_list_html) Backend (agent_doc_check_extras.py — neu): - build_scanned_urls_html: gepruefte URLs als Tabelle oben im Report (transparent fuer GF, welche Quellen wirklich gezogen wurden) - Cross-Domain-Hinweis bei >1 netloc (BMW: bmw.de / bmwgroup.com / bmwgroup.jobs — Auffindbarkeit nach Art. 12 DSGVO) - build_provider_list_html: Banner-Box + TCF-Vendor-Tabelle mit Spalten Name | Kategorie | Zweck | Drittland | Rechtsgrundlage Backend (business_profiler.py): - §34d-GewO Versicherungsvermittler-Hinweise zaehlen nicht mehr als "finance"-Industrie (BMW wurde dadurch falsch als B2B/finance erkannt) - Neue Industry "automotive" (Fahrzeug/KFZ/Konfigurator/Modellpalette) - B2B-Keywords: generische Begriffe wie "unternehmen", "beratung", "consulting" entfernt (matchten in jedem Konzerntext) - B2C-Fallback: bei Verbraucher-Signalen ("widerruf", "kunde", redaktioneller Inhalt) tendiert auf b2c statt b2b Frontend (ComplianceCheckTab.tsx): - Progress-Balken mit Width-% und XX%-Anzeige rechts - liest data.progress_pct aus Polling-Response Consent-Tester (dsi_discovery.py): - Cookie-Policy-Extraktion kritisch fixt: wait_for_function bis body.innerText > 500 chars (BMW SPA-Rendering brauchte mehr Zeit) - _extract_text_robust: 3-Strategien-Extraktion (Selektoren -> Body- Cleanup -> P/LI/TD-Tags) - _extract_text_from_iframes: liest OneTrust/Sourcepoint/Usercentrics Iframe-Inhalte (manche Cookie-Policies leben dort) Adressiert alle Findings aus dem BMW-Ground-Truth-Vergleich.	2026-05-16 17:53:14 +02:00