313982c6f1913f30fd39233300a86f89a4f4a76f
36 Commits
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313982c6f1 |
feat(profile+report): P17 — 4 Polish-Items
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A) Cookie-Policy-Architecture-Block Fallback auf DSE-Text wenn cookie via P15 deduped wurde. Erkennt jetzt auch single-doc Sites (Safetykon-Pattern). B) Konkrete-Aufgaben-Liste: Per-Doc-Cap (3) entfernt + globaler Cap 10→20. Safetykon zeigt jetzt 7 statt 4 Aufgaben. C) business_type-Klassifizierer: B2B-Service-Cluster aus P14 als Boost. Bei 2+ Service-Indikatoren (CE-Zertifizierung/Compliance/Auditierung) wird b2b_score angehoben. Safetykon: "B2C consulting" → "B2B (consulting)". D) Vendor-Extract Fallback auf DSE-Text wenn cookie deduped + keine CMP- Payloads. LLM extrahiert dann Vendors aus dem DSE-Text. Safetykon: 0 → 1 Vendor (Google Analytics aus dem DSE-Text erkannt). Smoke-Test Safetykon: alle 4 Polish-Items wirken, kein Regression. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> |
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479ce2225b |
feat(profile): P14+P15+P16 — B2B-Heuristik + Doc-URL-Dedup + Homepage-Profile
P14 — _detect_no_direct_sales erweitert um 3 Cluster: A) OEM-Konfigurator (BMW/Audi/Mercedes/VW/Porsche-Markennamen + Vertragshaendler-Pattern) B) B2B-Dienstleister (CE-Zertifizierung, Compliance-Beratung, Schulungen, Auditierung, TISAX, ISO-Normen, Arbeitssicherheit, ...) C) NGO/Verein/Public (Spendenkonto, Vereinsregister, gemeinnuetzig, ...) Schwelle: pos >= 2 pro Cluster UND pos > neg. Bisher: nur OEM. P15 — Doc-URL-Dedup im Worker: wenn mehrere Doc-Types DASSELBE Dokument referenzieren (Safetykon-Pattern: User gibt /datenschutz fuer dse, cookie UND widerruf), wird nur dem primaeren Doc-Type (Priority: dse > impressum > cookie > widerruf > agb > nutzungsbedingungen) der Text gegeben. Andere landen als "Nicht separat vorhanden — wird im Dokument 'X' mit-geprueft." Eliminiert die 8+8 systematischen widerruf/cookie False Positives. P16 — Profile-Detection auch Homepage-Text: Homepage-HTML wird mit kurzem Fetch (8s timeout) gezogen, getrippt und zum profile_input gemerged. Vor- her wirkte P14 nur wenn B2B-Indikatoren im DSE/Impressum-Pflichttext standen — bei Safetykon stehen sie nur im Homepage-Menue. Plus Bonus: TDM-Override-Submit-Button wird deaktiviert wenn Reason < 10 Zeichen — verhindert dass User wie heute in den Bug rein klickt. Smoke-Test Safetykon (B2B Compliance-Dienstleister): dse geprueft (kein err) impressum geprueft (kein err) cookie "Nicht separat vorhanden — wird in DSE mit-geprueft" agb "Nicht anwendbar — kein Direkt-Kaufvertrag" widerruf "Nicht anwendbar — kein Direkt-Kaufvertrag" nutzungsbedingungen "Nicht anwendbar — kein Direkt-Kaufvertrag" Vorher: 16 False Positives. Jetzt: 0. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> |
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78b27d4684 |
feat(compliance-check): P12 — TDM-Override mit dokumentierter Kunden-Erlaubnis
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Backend: ComplianceCheckRequest um tdm_override + tdm_override_reason
erweitert. Worker im _run_compliance_check Pfad: bei
tdm_override=True UND Reason >= 10 Zeichen wird der TDM-Vorbehalt
nur dokumentiert (job.tdm_override.{reason, original_status}) und
NICHT als Abbruch-Grund gewertet. Ohne Reason: Override ignoriert.
Audit-Spur via logger.warning(reason).
Frontend: ComplianceCheckTab um Checkbox + Pflicht-Reason-Feld
("Schriftliche Crawl-Erlaubnis vorhanden") direkt vor dem Submit-
Button. Pflicht: Reason >= 10 Zeichen. Submit sendet die Flags ans
Backend.
Anwendungsfall: Safetykon-Pattern — robots.txt + ai.txt setzen
Vorbehalt, aber Kunde hat schriftlich zugestimmt (Auftrags-Audit).
[guardrail-change] ComplianceCheckTab.tsx (511 LOC) in loc-exceptions
ergaenzt — Split nach _components/TDMOverride + CompliancePolling
ist P11-Tech-Debt.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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28a078ccb4 |
feat(compliance-check): P10 — Cookie-Policy-Architecture-Detection
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Neuer Service cookie_policy_architecture.detect_architecture(...) prueft
vier Diagnose-Punkte der Cookie-Policy einer Website:
1. Layer-Trennung: single (BMW-Pattern: Banner + Info in EINER URL)
| separate (Best Practice: getrennte Layer)
2. Versionierung: "Stand vom DD.MM.JJJJ" / "Version X.Y" / ...
3. Dynamic content: CMP-Capture auf Doc-URL oder Marker-Texte
4. Vendor-Count im Text: Indikator ob Liste statisch drinsteht
Risiko-Ampel:
- gruen: separate + versioned + statisch
- gelb : single+unversioned (BMW) ODER separate+unversioned
- rot : weder noch (Pflicht-Info fehlt)
Wire-in im Compliance-Check-Worker: nach Exec-Summary-Block wird der
Architecture-Block gerendert (build_architecture_html) mit konkreter
Empfehlung. Bei BMW-Pattern: "Snapshot der dynamischen Vendor-Tabelle
als versioniertes PDF im Archiv."
Hintergrund: BMW hat eine HTML-Seite die GLEICHZEITIG Banner-Re-Trigger
und Cookie-Richtlinie ist. Mindestanforderung nach §25 TDDDG + Art. 13
DSGVO erfuellt, aber bei einer Aufsichtsbehoerden-Pruefung kann nicht
belegt werden welche Vendor-Liste an einem bestimmten Stichtag aktiv
war. Das ist kein Verstoss aber best-practice-Luecke.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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0d37822b7c |
fix(impressum): P9 — 7 False-Positive-Fixes in Pflichtangaben-Checks
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#1 Name des Anbieters: \b Word-Boundary verhindert "ag" in "samstag", plus "aktiengesellschaft" als Volltreffer. #2 Vertretungsberechtigte: Klammer-Liste-Pattern erkennt jetzt BMW- Format "Vorstand (Milan Nedeljkovic, Jochen Goller, ...)" plus "Vorsitzender des Aufsichtsrats: Name". #3 V.i.S.d.P.: war schon INFO, OK. #4 OS-Plattform/VSBG: bei no_direct_sales=True (OEM-Pattern) jetzt als "Nicht anwendbar" skipped statt 0/1 fail. Profile fliesst neu durch check_document_completeness -> runner. #5 Zustaendige Kammer: IHK + Handwerkskammer + Tieraerztekammer in Pattern aufgenommen + severity LOW -> INFO (konditional). #6 Stammkapital: war schon INFO, OK. #7 Link-Disclaimer: neue Check-Eigenschaft "invert"=True. Anti-Pattern ist passed wenn NICHT gefunden, fail wenn gefunden. Vorher feuerte das Finding immer, jetzt nur wenn ein illegaler Disclaimer im Text ist. Plus: L2-INFO-Checks (z.B. profession_chamber) zaehlen nicht mehr in correctness-pct und erzeugen keine DSI-DETAIL-Findings. Konsistent mit P8-Modell: INFO = "selbst pruefen", nicht "fail". Verifiziert mit BMW-Impressum-Text — alle 7 Faelle korrekt klassifiziert: name=passed, representative_person=passed, profession_chamber=INFO, illegal_disclaimer=passed (kein Disclaimer im Text), dispute_resolution=skipped (no_direct_sales), editorial_visdp=INFO, share_capital=INFO. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> |
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6c223c7c9b |
feat(compliance-check): exec-summary + voll-audit + TDM-respect + cookie-KB-extended + saving-scan-funnel
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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>
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662327e8b4 |
feat(compliance-check): MC-Classification + Embedding + Vendor-Redundanz + Action-Recipes + Borlabs-Features
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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> |
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df7d83134b |
feat(agent): migrate compliance-check results to banner + documents (M1-M5)
After a compliance-check run finishes, the user can now apply the
extracted vendor inventory directly to their own:
- CookieBanner config (admin /sdk/einwilligungen)
- Cookie-Policy / VVT-Register / Privacy-Policy templates
(admin /sdk/document-generator)
Backend:
- migration_to_banner.py: vendor list -> CookieBannerConfig with
ESSENTIAL/PERFORMANCE/PERSONALIZATION/EXTERNAL_MEDIA buckets +
review flags (broken opt-out URLs, missing expiry, no cookies listed)
- migration_to_document.py: vendor list -> pre-fills for 3 doc
templates, recipient-type aware (INTERNAL/GROUP/PROCESSOR/CONTROLLER)
- agent_migration_routes.py: GET /banner-preview, /document-preview,
/summary keyed on check_id
- compliance_audit_log: new check_payloads table persists cmp_vendors +
extracted_profile so the preview survives an app restart
- tests: 9 mapper units + 4 endpoint integration tests
Frontend:
- MigrationPanel.tsx: modal showing banner-config diff + document
pre-fills, plus links into the existing editors
- ComplianceCheckTab.tsx: replaces standalone audit link with the
panel; net -3 lines, stays at the 500-cap
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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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. |
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8a44e67293 |
feat(compliance-check): unlock all 1874 MCs + close gap-table items
User: 'wir haben 1800 MCs erstellt um sie zu 10% zu nutzen — das ist Schwachsinn'. Fixed all 6 gaps from the audit. #1 max_controls=0 (was 20): - agent_compliance_check_routes _check_single: passes max_controls=0 to check_document_with_controls -> ALL MCs evaluated per doc_type. - 8 doc_types now use 1874 MCs instead of 160 (10x coverage). - Regex matching is cheap (<1s per doc); LLM-enrich cap of 10 stays. #2 LLM-verify fixed: - llm_verify.py was getting 0/N parsed. Causes: qwen3 thinking-mode wrapped output in <think>...</think>, /api/generate doesn't enforce JSON, prompt didn't handle code-fence wrappers. - Now uses /api/chat with format='json' (forces valid JSON). - _parse_batch_response strips <think> tags, accepts {results:[...]} AND bare [...], adds richer regex-fallback parse, logs raw head on total parse failure for diagnosis. #3 Loeschkonzept checklist (new): - doc_checks/loeschkonzept_checks.py — 9 L1 + 7 L2 checks per DIN 66398 + Art. 5(1)(e)/17/32 DSGVO: scope+responsibility, data categories, retention periods, legal basis refs (HGB/AO/BGB), deletion trigger, deletion process+technical+systems, deletion proof, exceptions + Art. 18 lock, review cycle, DSGVO references. - runner.py registered for loeschkonzept/loeschung/loeschfristen. #4 regulation backfill script: - backend-compliance/scripts/backfill_mc_regulation.py — regex-detects DSGVO/TDDDG/TMG/BGB/HGB/AO/MStV/UWG/VSBG/PAngV/GwG/BDSG/EU-VO references in MC title+question+pass_criteria, UPDATEs regulation + article fields. - Idempotent (only NULL rows), --dry-run flag, batched 200/UPDATE. - Run inside container: docker exec bp-compliance-backend python3 \ /app/scripts/backfill_mc_regulation.py #5 MC alias-fallback: - rag_document_checker._MC_ALIAS_FALLBACK maps doc_types without own MCs to a related set: nutzungsbedingungen->agb, social_media->dse, sub_processor/scc/tom_annex->avv, loeschfristen->loeschkonzept, eu_institution/dsb->dse. - _load_controls retries with the alias when the primary query returns 0 rows. - 14 additional doc_types now get MC coverage transparently. #6 cross-domain auto-discovery: - _autodiscover_missing builds a crawl plan: primary submitted base + up to 2 related domains sharing the owner SLD (e.g. BMW Group: bmw.de + bmwgroup.com + bmwgroup.jobs). - Detection: regex over submitted texts for https?://...<owner>... hostnames distinct from the primary base. - Each crawled base contributes documents + cmp_payloads to the discovery pool. Net effect for BMW: 1874 MCs evaluated (90 from cookie alone, was 20), Loeschkonzept Pflichtangaben benoten-bar, LLM overturns false regex FAILs, Joint-Controller policies on bmwgroup.jobs (Social Media) jetzt entdeckbar. Same wins will apply to CRA-Compliance check. |
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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).
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873997c13b |
feat(vvt): V3 — LLM vendor extraction fallback for unknown CMPs
When the cookie text has no captured CMP payload (long-tail sites that
don't use ePaaS/OneTrust/Cookiebot/etc.) we now fall back to a Qwen → OVH
LLM cascade to extract a structured vendor list from the policy text.
New module backend/compliance/services/vendor_llm_extractor.py:
- extract_vendors_via_llm(cookie_text): runs Qwen first (local Ollama),
then OVH if Qwen returns nothing usable.
- System prompt instructs the model to return STRICT JSON only:
{vendors: [{name, country, purpose, category, opt_out_url,
privacy_policy_url, persistence, cookies: [...]}]}
- Lenient JSON parser tolerates code-fences, prose wrappers, dict vs list.
- _normalize() caps array sizes (80 vendors, 30 cookies each), validates
URLs (must be http(s)), trims fields to reasonable lengths.
Route integration (agent_compliance_check_routes.py):
- After named-CMP extract: if cmp_vendors is empty AND the cookie text
has ≥500 words (otherwise it's likely navigation chrome), invoke the
LLM extractor. Progress message 'Vendor-Liste per LLM extrahieren...'.
- Vendors then run through the same validate_vendor_urls + score_vendors
pipeline → VVT table rendered identically regardless of source.
docker-compose.yml: backend-compliance gains OLLAMA_URL, CMP_LLM_MODEL,
OVH_LLM_URL/KEY/MODEL env vars (same names as consent-tester so the
configuration is unified).
This closes the 'every site eventually gets a VVT table' goal:
- Known CMP → V1/V2 structured extraction (fast, exact)
- Unknown CMP → V3 LLM extraction (slow, best-effort)
- No text at all → no vendors, but other compliance checks still run.
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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.
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c9c0fb5965 |
feat(cookie-check): enhanced patterns + active opt-out link validator
cookie_checks.py: - cookie_names_listed: now also matches CMP placeholder notation (BMW: 'Adfpc###', 'CT###') and 'Diese Datenverarbeitung verwendet die folgenden Cookies oder ähnliche Technologien' as list-shape signal. Cryptic vendor names like 'audience', 'adformfrpid' are accepted via the surrounding markup, not by hard-coding each one. - cookie_providers_named: new pattern 'Gesetzt von: <Firma>' (BMW/ePaaS per-cookie vendor naming) + recognition of full legal-form names (Adform A/S, BMW AG, Adobe Systems Software Ireland Limited). - cookie_duration_values: now matches 'Ablauf: 1 Jahr' / 'Speicherdauer: 30 Tage' (BMW format) in addition to the legacy '<n> <unit>'. New L1 + L2 checks for controller in cookie-policy: - cookie_controller (L1): the cookie policy must name Verantwortlich(er) - cookie_controller_address (L2): PLZ + Ort or address keywords - cookie_controller_contact_or_link (L2): email/phone OR link back to Datenschutzerklärung (the practical equivalent — BMW does this) New L2 checks (parented under opt_out): - cookie_optout_links: detects per-provider opt-out URLs in the text - cookie_privacy_policy_links: per-provider privacy-policy URLs New service: cookie_link_validator.py - extract_links(text): pulls all https?://… URLs that follow 'Opt-Out Link:' / 'Link zur Privacy Policy:' (deduped) - validate_links(links): probes every URL concurrently (HEAD first, GET fallback for 405/403). 10 parallel, 8s per request, 60s batch cap. Returns reachable=True/False + status + final_url. - build_check_items(): renders 2 CheckItems (opt-out + privacy-policy), each pass if ALL links 2xx/3xx, fail with up-to-5 broken-link examples. Hook in _check_single: doc_type=='cookie' triggers the validator after regex+MC checks. Recomputes correctness with the new L2 items. This addresses two concrete BMW observations: 1. BMW's per-cookie structure (Name + Zweck + Ablauf, Gesetzt von: …, Opt-Out Link: …) now recognised → 'Konkrete Cookie-Namen aufgelistet' and 'Konkrete Speicherdauern' should pass. 2. Defective opt-out URLs surface as compliance findings rather than silently passing — Art. 7(3) DSGVO requires a working withdrawal path per provider. |
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b090662524 |
fix(compliance-check): respect auto-discovery 'not found' verdict; DSB not canonical
Two related bugs in the BMW test result:
1. AGB rendered as 'MANGELHAFT 0/13' even though BMW has no public AGB:
- Auto-discovery correctly returned 'not found' for AGB (no link on
bmw.de matches AGB keywords).
- But auto_fill_from_dsi then found the substring 'AGB' in a section
of the DSI and pseudo-filled the AGB entry with a 264-word DSI
fragment.
- cross_search_documents would have done the same.
- Both now skip entries where discovery_attempted=True AND
auto_discovered=False — the 'not found' verdict stands.
2. DSB-Kontakt rendered as a separate 100% OK document with 7566 words
= the entire DSI text:
- GDPR practice: the DSB is named *inside* the DSI as an email or
contact block (Art. 13(1)(b)), not as a stand-alone page.
- cross_search_documents had been assigning the full DSI to the DSB
row because it matched 'datenschutzbeauftragte' keywords.
- DSB removed from _ALL_DOC_TYPES — no longer canonical, no longer
padded as missing, no longer auto-discovered. The frontend row
remains so a tenant with a separate DSB page can still submit one.
After this fix BMW should render:
- DSE: OK
- Impressum: LUECKENHAFT (unchanged — regex gaps to fix separately)
- Cookie-Richtlinie: OK
- Social Media: NICHT GEFUNDEN (bmw.de does not link to it)
- AGB: NICHT GEFUNDEN (correct — BMW has no public AGB)
- Nutzungsbedingungen: NICHT GEFUNDEN
- Widerruf: NICHT GEFUNDEN
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b2b4d77877 |
fix(auto-discovery): compute missing against canonical 8 types, not submitted
Frontend filters out empty doc rows -> req.documents only contains the
N submitted entries (3 in BMW case). The old auto-discovery loop
computed 'missing' as 'entries in doc_entries with empty text', which
was always empty for those N entries -> discovery never fired.
Fix:
- missing = _ALL_DOC_TYPES - {canonical doc_types in doc_entries}
- For each missing type, APPEND a new entry to doc_entries with
discovery_attempted=True. If a discovered doc matched, fill text/url
and set auto_discovered=True.
- Check loop: skip entries with no URL and no text (let padding label
them). Entries with URL but no text keep the 'Kein Text' error so the
user sees fetch failures explicitly.
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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. |
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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. |
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9814b56f2f |
fix(cookie-extract): max_documents=1 + faster networkidle bail (Phase 0 fix)
Root cause of the recurring 603-word BMW result: - DSI discovery for cookie-policy URL was hitting 4x networkidle timeouts (60s each = ~240s total). - Backend httpx timeout (180s after the previous fix) gave up before the consent-tester finished, falling through to the raw HTTP fetch which returned BMWs SSR navigation chrome (603 words) as the 'cookie policy'. Two orthogonal fixes: 1. _fetch_text now passes max_documents=1 for user-specified URLs. We only want self-extraction of THAT page; link-following is unnecessary noise. 2. networkidle wait_until window dropped 60s -> 15s. SPAs like BMW/Daimler never reach networkidle anyway; the 60s wait was pure latency. Falls through to domcontentloaded+5s render-wait, same as before. |
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6689b37f95 |
fix(agent): bump _fetch_text timeout 60s->180s
The dsi-discovery in consent-tester does self-extraction + follows up to 3 sub-links + waits for CMP JSON payloads. On big SPAs (BMW, Daimler) this routinely exceeds 60s. When it timed out, the HTTP fallback returned the SSR shell as text — for the BMW cookie page that's 603 words of site navigation, which then registered as 'Cookie-Richtlinie nicht im eingereichten Text' (33%). With 180s the consent-tester finishes cleanly and we get the CMP-captured 1824 words of real policy. |
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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.
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d45e08e25f | fix: reduce Playwright timeout 180s→60s, increase poll limit 15→25min | ||
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3dbf3aa34a |
feat: HTTP fallback for text extraction when Playwright times out
BMW Impressum/Cookie pages timeout in Playwright (>180s) because the SPA has many sub-links to follow. But the HTML source already contains the text (SSR). New fallback: direct HTTP GET + HTML tag stripping. Order: 1. Consent-tester (Playwright, 180s) → 2. HTTP GET (30s) Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |
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f34305c0a1 | fix: increase dsi-discovery timeout 90s→300s, reduce max_documents 10→5 | ||
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fca67c1f43 |
fix: accordion close bug + merge multi-page DSIs (BMW fix)
1. _expand_all_interactive(): Only click aria-expanded="false" buttons. Before: clicked ALL accordion buttons including open ones → BMW's pre-expanded accordions got CLOSED, reducing text from 1151 to 361w. 2. _fetch_text() + /extract-text: merge ALL documents found on a page (max_documents=10 instead of 1). BMW splits DSI across 5 sub-pages that the discovery finds as separate documents — now merged. 3. Tab panels: unhide hidden tabpanels instead of clicking tabs (clicking tabs can hide the currently visible panel). Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |
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9f87bc5a2c | fix: include website/company name in compliance-check email subject | ||
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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>
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826ce2a1b8 |
fix(cross-doc): suppress false positives when regex checks already pass
Cross-search "not in text" findings are only shown when regex L1 completeness < 50%. This prevents false positives where the text IS the right doc_type but doesn't contain the specific cross-search keywords (e.g. Impressum passes 9/13 checks but lacks "§5 TMG"). Also: cross-search now checks entries with wrong text, not just empty. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |
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4e9043f26d |
feat(cross-doc): search all texts for all doc_types + misplacement finding
Cross-Document Intelligence: When a doc_type row is empty, searches ALL other loaded documents for that content. If found (e.g. Widerruf in AGB), extracts the section, runs the check, AND creates a finding: "Widerrufsbelehrung in falschem Dokument gefunden — schwer auffindbar" Keywords for: widerruf, cookie, social_media, impressum, agb, dsb. Integrated as Step 1c in compliance check pipeline. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |
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c702260ec1 |
fix: 5 regex bugs + text extraction scroll + GT update
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Root cause: Spiegel DSI text was truncated (lazy-loading) — the rights/DSB/complaints sections at the bottom were never extracted. Fixes: 1. Text extraction: scroll to bottom before innerText (dsi_discovery.py) 2. V.i.S.d.P.: add "verantwortlicher i.s.v." + "§18 Abs. N MStV" pattern 3. USt-IdNr: add "umsatzsteuer-id" + "DE 212 442 423" (with spaces) 4. Profiler: remove generic "anwalt"/"praxis" (false positive on Spiegel "Redaktionsanwalt"), keep only "rechtsanwalt", "kanzlei" etc. 5. Section splitter: auto_fill_from_dsi() fills empty Cookie/Social-Media rows from sections found in the DSI text Ground Truth 06-spiegel.md fully rewritten with verified data from live website — 3 L1 False Negatives identified (DSB, Beschwerderecht, Betroffenenrechte all present on website but not in extracted text). Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |
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c867478791 |
feat(tcf-vendors): GVL cache + vendor extraction + VVT mapping
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Phase 1-2 of the closed quality loop: - GVL cache (consent-tester/services/gvl_cache.py): downloads and caches IAB Global Vendor List with 24h TTL, resolves vendor IDs to names, purposes, policy URLs, retention, country - Vendor extraction (consent_interceptor.py): extract_tcf_vendors() reads __tcfapi after accept phase, resolves via GVL - Scan response: tcf_vendors field added to /scan endpoint - VVT mapper (vendor_vvt_mapper.py): maps TCF vendors to VVT format with purpose labels, Rechtsgrundlage, Drittland detection - Vendor cross-check (banner_cookie_cross_check.py): checks all TCF vendors against DSI text — missing vendors, undocumented transfers - Compliance check integrates Step 3d: TCF vendors vs DSI Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |
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7be34552bb |
feat(compliance-check): profile extraction + scenario classification
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- 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> |
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be9cfdc2d4 |
feat(compliance-check): skip Widerruf for B2B, limit MCs, fix industry
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- Skip Widerrufsbelehrung check entirely for B2B/B2G businesses - Limit MC checks to top 20 per doc_type (by severity) to reduce noise (e.g. 75 impressum MCs → 20, avoiding 55 irrelevant FAILs) - Add consulting/manufacturing industry keywords (arbeitssicherheit, brandschutz, werkzeugbau, etc.) - Lower industry detection threshold from 2 to 1 keyword hit Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |
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74f00bbb0f |
feat(compliance-check): split shared URLs into sections per doc_type
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When the same URL is used for multiple document types (e.g. /datenschutz for DSI + Cookie + DSB), the section splitter now: - Detects duplicate URLs and fetches text only once - Splits text at classified headings (Cookie, Google Analytics, etc.) - Assigns matching sections to each doc_type - DSI always keeps the full text Extracted to section_splitter.py (170 LOC) to keep routes under 500. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |
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b6ad958b69 |
feat(compliance-check): integrate banner cross-check + extract to module
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Add automatic banner check (Step 3b) and banner-vs-cookie cross-check (Step 3c) to unified compliance check. Extract cross-check logic to banner_cookie_cross_check.py to keep routes under 500 LOC. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |
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0d0e705117 |
feat: Unified Compliance-Check — 8 document types in one form
New 3-tab structure: Website-Scan, Compliance-Check, Banner-Check. Compliance-Check Tab (replaces Dokumenten-Pruefung + Impressum-Check): - 8 document rows: DSI, Impressum, Social Media, Cookie, AGB, Nutzungsbedingungen, Widerruf, DSB-Kontakt - Each row: URL input + "Text laden" + file upload + manual text - "Text laden" extracts via consent-tester, shows in editable textarea - User verifies/corrects text before checking - Empty fields = "not present" → own finding Business Profiler (business_profiler.py): - Detects B2B/B2C/B2G from all documents together - Recognizes regulated professions, online shops, editorial content - Context-aware: INFO checks become PASS/FAIL based on profile Backend: /compliance-check + /extract-text endpoints Frontend: ComplianceCheckTab.tsx + DocumentRow.tsx API proxies: compliance-check/route.ts + extract-text/route.ts Also: Impressum regex fixes (Telefon, AG, Geschaeftsfuehrung) and INFO severity for context-dependent checks. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |