9 Commits

Author	SHA1	Message	Date
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	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
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	bc21480a2a	fix(compliance-check): always render 8 doc types + 4 BMW GT-gap fixes ... Always-show-8 (user-requested): - agent_compliance_check_routes.py: _pad_results_with_missing pads the results list to always include all 8 canonical doc_types in canonical order. Missing types get a placeholder DocCheckResult with error= 'Nicht eingereicht' + scenario='missing'. - agent_doc_check_report.py: NICHT EINGEREICHT status label (neutral), friendly grey body block instead of red error. - ChecklistView.tsx: 'Nicht eingereicht' chip (neutral grey, not red 'Fehler'); SCENARIO_LABELS adds missing entry + header chip counter. Impressum-Regression fix (#18): - _fetch_text(url, doc_type): cookie/dse/social_media -> max_documents=1 (CMP capture authoritative, sub-pages dilute). Other types -> =3 (Impressum needs Versicherungsvermittler, Aufsicht, Berufsrecht sub- pages). 15s networkidle bail keeps timing safe. ODR/Verbraucherstreitbeilegung filter (#19): - _apply_profile_filter: when profile.needs_odr=True (B2C), override the check's default B2B-oriented hint with action-oriented B2C guidance pointing at Art. 14 EU-VO 524/2013 + §36 VSBG. Previously the check contradicted itself: 'profile says B2C' + hint 'only relevant for B2C online vendors'. Registergericht regex (#20): - impressum_checks.py: accept colon/dot/dash between keyword and city (BMW writes 'registergericht: münchen hrb 42243'). Add 'sitz und registergericht: X' as separate pattern. Industry detection (#21): - business_profiler.py: 'automotive' keywords broadened (antriebs, motor, leasing, werkstatt, probefahrt, plus brand names BMW/Mercedes/ Audi/VW/Porsche/Opel). 'it_services' keywords narrowed — software/ cloud/hosting are mentioned in every privacy policy and were biasing the result toward IT for any tech-aware company.	2026-05-17 01:03:58 +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
Benjamin Admin	d72aa10691	feat: management summary for GF + batch GT test script ... 1. Management Summary (agent_doc_check_report.py): - Plain-language action items for Geschaeftsfuehrer - Maps technical checks to business actions ("Ihren DSB erwaehnen", "Beschwerderecht ergaenzen", "Loeschfristen dokumentieren") - Shows at top of compliance check email before detail report - Max 10 actions, max 3 per document 2. Batch GT Test (zeroclaw/scripts/batch_gt_test.py): - Runs all 10 GT websites through compliance-check API - Prints comparison table with L1 scores, word counts, services - Saves raw JSON results for analysis - Usage: python3 batch_gt_test.py --sites 1,6 --backend-url URL Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>	2026-05-15 09:39:19 +02:00
Benjamin Admin	7be34552bb	feat(compliance-check): profile extraction + scenario classification ... - New profile_extractor.py: extracts Company Profile fields (name, legal form, address, DPO, USt-IdNr) and Compliance Scope hints (Art. 9 data, third country, profiling) from document texts - Scenario per document: regenerate (<30%), fix (30-95%), import (>95%) - Widerruf for B2B: no longer skipped, instead all checks flagged as INFO with "not needed for B2B" hint - Move _build_profile_html to report builder module - DocCheckResult gets scenario field Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>	2026-05-12 17:34:33 +02:00
Benjamin Admin	a3287cd5e6	feat: HTML email report with hints + fix duplicate Social Media sections ... 1. Email report now renders as styled HTML (matching frontend design): - Progress bars (green=completeness, blue=correctness) - Hierarchical L1→L2 check display - Red hint boxes under failed checks explaining what to fix - Matched text evidence for passed checks 2. Section splitter deduplicates: two "Social Media" headings on the same page are merged into one section instead of creating duplicates. 3. Extracted report builder to agent_doc_check_report.py (175 LOC) to keep routes file under 500 LOC (386 LOC). Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>	2026-05-07 15:13:00 +02:00