08671adfdfc74a6ab1889b0a05181498967f2aa2
391 Commits
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08671adfdf |
feat(audit): P82 GF-1-Pager + P87 Konfidenz-Score pro Finding
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P82 — gf_one_pager.py: kompakte 5-Bullet-Kurzfassung ganz oben in der Mail. Score (gross + Farbe), Delta-zu-Vorlauf, Top-Findings nach HIGH/MEDIUM sortiert mit zustaendiger Rolle (DSB / Marketing / IT / Legal / Web-Team) und Klassifizierungsbits aus dem Wizard. Sachlicher Ton — keine 4%-Drohung, '4-8 Wochen' als realistischer Zeitrahmen. Eingehaengt vor Critical-Findings-Block in Mail-Composition und Replay-Pipeline. P87 — finding_confidence.py: 13 Regex-Regeln liefern (confidence_pct, reason) pro Finding-Label. Direkt im DOM beobachtbar = 95-98%, Library-Mismatch = 82%, Textmuster-Match auf Pflichtangaben = 75-88%. Im 1-Pager als kleines '(NN% Konfidenz)'-Tag mit Reason-Tooltip hinter jedem Finding gerendert. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> |
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50fc0ecc59 |
feat(audit): P79 Pre-Scan-Wizard (8 Pflichtfelder) + P99 erweitert + P102 Replay-Fix
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P79: PreScanWizard.tsx mit 8 Pflichtfeldern (Branche, B2B/B2C,
Direkt-Vertrieb, Rechtsform, Konzern-Struktur, MA-Zahl, Besondere
Daten, Drittland). Scan-Button disabled bis alle 8 ausgefuellt. Werte
landen in scan_context und ueber Backend in compliance_check_snapshots.
P99: DOC_TYPES um dsa + legal_notice + lizenzhinweise + nutzungsbedingungen
erweitert. URL-hinzufuegen-Button war schon da.
P102 (Replay-Bug): check_replay.py liest jetzt e.get('text') statt
nur full_text — Snapshot-Schema verwendet 'text'. Library-Mismatch-
Block wird damit auch im Replay angezeigt.
Backend: ComplianceCheckRequest.scan_context optional; save_snapshot
persistiert ihn in compliance_check_snapshots.scan_context.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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94057b1536 |
feat(audit): VW-Cookie-Bug-Fix + P101/P102 Cookie-Library-Mismatch-Findings
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VW-Bug B1: extract_vendors_via_llm hatte max_text_chars=12000 -> bei VW-Cookie-Doc (60k chars, 100 Cookies in Tabelle) wurden 80% abgeschnitten, LLM extrahierte nur 1 Vendor. Fix: max_text_chars=50000, num_predict 6000->16000 fuer mehr Vendor-Output, Ollama-Timeout 120s->420s. P101 Aggregator-Script (backend-compliance/scripts/cookie_library_enrich.py) geht alle compliance_check_snapshots durch und extrahiert (cookie_name, declared_category, observed_sites). Erste Auswertung ueber 8 Snapshots: 101 unique Cookies, 47 in Library, 54 unbekannt, 18 Mismatches. P102 Cookie-Klassifikations-Pruefung als Mail-Block. Vergleicht Site-deklarierte Kategorie vs Library + Vendor-Doku. HIGH wenn Library sagt 'marketing' aber Site als 'essential'/'statistics' deklariert (faktische Drittland-/Werbe-Verarbeitung versteckt). MEDIUM sonst. In agent_compliance_check_routes Mail-Komposition + Replay-Pipeline eingebaut. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> |
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50ed0f45af |
fix(replay): P80 — DocCheckResult-Import entfernt (gibt es nicht in runner)
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Vorher hatte ich den Container hotfixed aber den Fix nicht committed. Beim naechsten Rebuild kam der Bug aus dem Image zurueck. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> |
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e1df24cad7 |
fix(audit): P93+P95 — Reject-Wording erweitert + Vendor-zentrisches Cookie-Format akzeptiert
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P93: 'Cookies verbieten', 'Tracking ablehnen', 'verweigern' usw. zaehlen nun als expliziter Reject-Mechanismus. EDPB 5/2020 schreibt kein bestimmtes Wort vor — BMW False-Positive 'Kein Ablehnen-Mechanismus' weg. P95: cookie_table-Check akzeptiert nun zwei gleichwertige Formate: (a) klassische Tabelle, (b) Vendor-Detailseite mit Block pro Anbieter (Name+Anschrift, Zweck, Speicherdauer aggregiert, Cookie-Namen-Liste, Opt-Out-Link). BMW-Stil mit Adform-Block ist DSK-OH 2024 konform. False-Positive 'tabellarisches Cookie-Verzeichnis fehlt' wird seltener. Hinweis-Text in cookie_table umformuliert: nennt beide akzeptablen Formate, weniger normativ. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> |
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e5b4672f2a |
fix(audit): P90 — auto-discovery Timeout 180s -> 300s fuer BMW-Homepage
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Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> |
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0d5c76ea98 |
fix(audit): P90-B1 — DSI-Discovery Timeout 120s -> 240s fuer BMW-Impressum
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BMW-fafcb090 zeigte exception 'ReadTimeout' beim consent-tester-Call fuer anbieterkennzeichnung.html. Der Discovery-Lauf folgt 3 Sub-Documents (Versicherungsvermittler, Aufsicht, Berufsrecht) plus ePaaS-Captures — braucht regelmaessig >120s. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> |
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54f5a06c2f |
fix(audit): P90-Diagnose — verbose Exception fuer fetch+auto-discovery
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BMW-Lauf 760de886 hat 0 cmp_payloads obwohl consent-tester ePaaS 4x captured. Backend-Log zeigt 'Consent-tester fetch failed for ...anbieterkennzeichnung.html: ' mit LEEREM Exception-String. Auch 'auto-discovery failed for https://www.bmw.de/: ' ist leer. Quick-Fix: str(e) + type(e).__name__ in beiden Except-Bloecken, damit naechster BMW-Lauf den echten Fehler sichtbar macht. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> |
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86b4a263d2 |
fix(audit): P90-B1 — cmp_payloads bei kurzem DSE-Text nicht verwerfen
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BMW-Lauf 9811eba1 hatte 0 cmp_vendors obwohl consent-tester ePaaS 4x
captured (~393KB). Root-Cause in _fetch_text Z.1254:
if merged and len(merged.split()) > 100:
return merged, cmp_payloads
Wenn DSE/Cookie-URL nur kurzen SPA-Shell-Text liefert (BMW: 10 Worte),
greift die Schwelle nicht — Code faellt durch zum HTTP-Fallback der
return text, [] zurueckgibt. Die zuvor captured CMP-Payloads (ePaaS-JSON
mit allen Vendor-Daten) werden komplett verworfen.
Fix: vor dem HTTP-Fallback pruefen ob cmp_payloads vorhanden sind. Wenn ja,
diese zurueckgeben mit dem (kurzen) Text oder dem rekonstruierten
cmp_cookie_text. Auch ohne 100-Wort-Schwelle.
Effekt: BMW-VVT-Tabelle wird gefuellt (~90 Vendors aus ePaaS-JSON).
Mercedes/andere OEMs unveraendert.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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7938e377b6 |
feat(audit-tonality): P89/P76/P91 — Co-Pilot statt Roboter-Anwalt
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User-Feedback in einer Session: "Wir erzeugen nur Panik. Egal was da steht,
es dauert Wochen. Wir sind Tool an der Seite von CMO/GF/CIO, nicht Gegner."
Memory: feedback_breakpilot_tonalitaet.md (gilt fuer ALLE Module + Marketing).
P89 Critical-Findings-Block ENTFERNT/UMGEBAUT — keine Panik-Rot-Box mehr.
- Statt "🚨 SOFORTMASSNAHMEN ERFORDERLICH" -> "Zusammenfassung fuer
die Geschaeftsfuehrung", blauer dezenter Block
- Statt "VERSTOSSE" -> "Themen zur Besprechung mit DSB, Marketing
und Entwicklung"
- Statt "Bussgeldrahmen 4% Weltumsatz" als Erstes -> realistische
Einordnung (0,1-1%) in dezenter Schluss-Notiz mit Konfidenz-Hinweis
- "Sofortmassnahme" -> "Empfehlung"
- "Themen 1, 2, 3..." statt "HIGH"-Badges (P87-Vorbereitung)
- Explizite Zeitschaetzung "4-8 Wochen (DSB -> Agentur -> Dev -> Freigabe)"
P76 Mercedes-Sekundaer-Buttons (Datenschutzerklaerung + Impressum klein
unter den 3 Haupt-Buttons) erkennen. Walker scant jetzt label-basiert
ALLE klickbaren Elemente im Shadow-DOM (wb7-link, wb7-link-secondary,
wb7-button-text, span[onclick], small a, [role=button], etc.).
Vermeidet Mercedes-Impressum-False-Positive der Phase 1.
P91 VVT-Tabellen-Renderer in neuer Co-Pilot-Tonalitaet. Statt
"Verstoss-Liste mit Bussgeldpotenzial" -> Wahrscheinlichkeits-Aussage:
"Bei Anbieter-Reduktion + Wechsel zu europaeischen Alternativen ist
Reduktion des Tracking-Footprints + Lizenz-Einsparung wahrscheinlich.
Fundierte Bewertung erfordert DSB-Abstimmung."
BMW-Bug B1-B4 (P90) bewusst nicht in diesem Commit: BMW-Lauf hat ePaaS
4x captured im consent-tester, aber Backend bekommt 0 cmp_payloads.
Wiring-Bug zwischen consent-tester /dsi-discovery und Backend
_fetch_text — eigene Diagnose-Session noetig (siehe Task P90).
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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4946571863 |
feat(audit-pipeline): P72-v2 Heuristik nachgeschaerft + P80 Mini-Replay-Endpoint
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P72-v2 MC-Scope-Classifier Heuristik v2 — v1 hatte 79% 'other'-Bucket
(Patterns zu strict). v2 deckt deutlich breiter ab:
- DSE: Art. 13/14 + Betroffenenrechte (Art. 15-22) + DSB +
Aufsichtsbehoerde + Speicherdauer + besondere Kategorien
- TOM: Art. 32 + Verschluesselung/Backup/Pseudonymisierung +
Zugriffskontrolle + ISO 27001 + BSI-Grundschutz + Audit-Log
- cookie_richtlinie: Tracking-Pixel + Webstorage + GA/Matomo/
Hotjar/Pixel/GTM
- process: VVT (Art. 30) + DSFA (Art. 35) + Datenpannen
(Art. 33/34) + HinSchG + Schulungen + Loeschkonzept
Script `backfill_mc_scope_v2.py` re-classifiziert NUR den
'other'-Bucket (spezifische v1-Buckets bleiben unangetastet).
P80 Mini-Replay-Endpoint (v1):
POST /compliance-check/snapshots/{id}/replay
?recipient=foo@bar.com & dry_run=false
Laedt Snapshot, rendert Mail mit AKTUELLEM Render-Code (P63-P67,
P59b/P61/P62). Sendet [REPLAY]-prefixed Mail oder gibt nur
HTML-Stats zurueck (dry_run).
Effekt: 7min Re-Scan -> 2-5sec fuer Mail-Layout-Iterationen.
v2 (spaeter): MC-Scorecard mit aktuellem scope_doc_type-Filter
ueber Snapshot — erfordert _run_compliance_check Refactoring.
Plus Bugfix: GET /snapshots/{id} raised jetzt HTTPException statt
Tuple-Return (FastAPI hat Tuple als JSON-Array zurueckgegeben).
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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cde670617e |
feat(audit-pipeline): P72 MC-Scope-Classifier + P80 Snapshot/Replay-Foundation [migration-approved]
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P72 MC-Scope-Classifier — pro MC den ECHTEN Doc-Adressaten festlegen
(cookie_richtlinie/dse/banner_implementation/cmp_audit/tom/avv/jc/
impressum/agb/widerruf/process/accounting/other).
- Migration 145: scope_doc_type Spalte + Index auf canonical_controls
- Backfill-Script mit Regex-Heuristik (12 Regeln, Prioritaet-sortiert)
- Erste 11k-Sample-Distribution: 76% other (Heuristik v1 zu strict —
v2 muss lockerere Patterns fuer DSE/TOM nachschaerfen)
- Ziel: bevor MC-Scorecard filtert, weiss jeder MC welches Dokument
er adressiert. Bisher landeten eHealth-/HGB-MCs im Cookie-Audit.
P80 Snapshot + Replay-Foundation — Roh-Daten persistieren damit
Audit-Pipeline ohne erneuten Crawl rebuildbar ist.
- Migration 146: compliance_check_snapshots Tabelle (JSONB pro
doc_entries/banner_result/profile/cmp_vendors/scan_context)
- services.check_snapshot.save_snapshot/load_snapshot/list
- Endpoints GET /snapshots, GET /snapshots/{id}
- Hook in _run_compliance_check: nach Mail-Send automatischer
Snapshot-Save via separater SessionLocal (background-task safe)
- Replay-Endpoint folgt im naechsten PR (braucht Refactoring
von _run_compliance_check in crawl_phase + interpret_phase)
- Effekt: Test-Cycle 7min -> 5sec bei reinen Logik-Aenderungen
(P73/P79/P81+ profitieren direkt). Snapshots dienen auch als
Regression-Test-Corpus (P81 Golden-Truth-Library).
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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603381a67f |
feat(audit-mail): P58/P59c/P60b/P61/P62 — Mercedes-Cycle Phase 1 abgeschlossen
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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>
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57c0f940a2 |
feat(consent+report): P56-P67 Mercedes-Audit-Cycle (Anti-Audit, Phase G Vendors, Cookie-Behavior-Validator + 5 Mail-Polish-Items) [migration-approved]
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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>
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badb356740 |
fix(founding-wizard): nested IF-Bloecke korrekt aufloesen (innermost-first)
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f08eb71480 |
fix(founding-wizard): default values fuer alle 8 Notar-Templates Platzhalter
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0477a2f2dc |
fix(founding-wizard): RESSORT_N_NAME/_GF/_AUFGABEN aus GF-Liste ableiten
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93cedbecbd |
fix(founding-wizard): missing context vars (P_INFO etc) + italic regex no longer eats snake_case underscores
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28f9e13c1f |
fix: remove jsonb_array_length from all 14 template migrations [migration-approved]
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35c1bbdaa5 |
fix: migration verification-SELECT (placeholders is TEXT not JSONB) [migration-approved]
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b7df4709bc |
fix(founding-wizard): set license_id='mit' (NOT NULL constraint) [migration-approved]
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6f3301d246 |
fix(founding-wizard): add python-docx dep + Lifecycle filter UI
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- requirements.txt: python-docx==1.2.0 (Container hatte das modul nicht) - document-generator: Lifecycle-Filter (Pre-Founding/Founding/Startup/KMU/Konzern) zeigt nur relevante Templates fuer aktuelle Phase |
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4478b7f479 |
fix(founding-wizard): mypy/ruff cleanup for CI
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- markdown_to_docx.py: type annotations + unused import - founding_wizard_routes.py: drop unused get_db import |
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7a5f1e48dd |
feat(founding-wizard): Gründungs-Wizard für 2-Mann GmbH + 14 Notar-Templates
[migration-approved]
Templates (Migrations 123-136):
- 123 GO-GF (Geschäftsordnung Geschäftsführung)
- 124 SHA (Shareholders' Agreement, 56 Platzhalter)
- 125 Satzung (Articles of Association mit UG-Variante)
- 126 GF-Dienstvertrag (Trennungsprinzip Organ/Anstellung)
- 127 Arbeitsvertrag (AGG-neutral, NachwG, eAU)
- 128 Gesellschafterliste (§ 40 GmbHG)
- 129 GF-Bestellungsbeschluss (mit § 6 Abs. 2 Versicherung)
- 130 HRB-Anmeldung (§§ 7, 8, 39 GmbHG, § 12 HGB)
- 131 IP-Assignment Agreement (Gründer→GmbH)
- 132 Term Sheet (Pre-Seed/Seed VC-Standard)
- 133 Wandeldarlehensvertrag (Convertible Loan)
- 134 Beteiligungsvertrag (Subscription Agreement)
- 135 ESOP/VSOP-Plan (3 Varianten)
- 136 Cap Table
Kategorisierung (Migrations 137-138):
- ALTER TABLE compliance_legal_templates ADD lifecycle_stage TEXT[],
functional_category TEXT (mit CHECK Constraints + GIN-Index)
- Backfill aller 105 Templates: lifecycle_stage (pre_founding|founding|
startup|kmu|konzern) + functional_category (founding_legal|employment|
investor_funding|...)
Backend Founding-Wizard Service:
- template_renderer.py: Handlebars-light ({{VAR}}, {{#IF FLAG}}...{{/IF}})
- wizard_to_context.py: Mapping Wizard-State → SCREAMING_SNAKE_CASE Vars
- markdown_to_docx.py: Markdown → DOCX via python-docx
- founding_wizard_routes.py: POST /v1/founding-wizard/generate
→ liefert base64-DOCX-Files für ausgewählte Templates
Frontend Founding-Wizard (/sdk/founding-wizard):
- 8-Step Wizard (Basics, Gesellschafter, GF, Kapital, Notar, SHA, GF-Verträge, Generate)
- useFoundingWizardForm Hook mit localStorage-Persistenz
- TypeScript Code-Registry (template-categories.ts) als Backup zur DB
- Word-Download via data:URLs (base64)
Tests:
- 20 Unit-Tests grün (Renderer, Context-Mapping, DOCX-Conversion)
- Playwright E2E-Test mit 2-Mann GmbH (Benjamin + Sharang) Test-Daten
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98ec6d4284 |
fix(report): Anti-Pattern-Aufgabe — "muss entfernt werden" statt "ergaenzt werden"
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Bug: bei invertierten Checks (P9 #7 illegal_disclaimer) sagte die GF-Aufgaben-Liste "muss ergaenzt werden" — semantisch falsch, weil der Disclaimer ja schon da IST und entfernt werden soll. Fix: _check_to_action() erkennt jetzt Anti-Pattern-Labels (rechtswidrig/illegal/haftungsausschluss/disclaimer) und gibt "muss entfernt werden (Anti-Pattern, rechtlich wirkungslos)" zurueck. Smoke-Test BMW d2f7bcc0: vorher 'Rechtswidriger Haftungsausschluss muss ergaenzt werden' -> jetzt 'muss entfernt werden'. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> |
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6f16507c5f |
feat(banner): P19 + P20 — Per-Category-Click-Test + Frontend-Drilldown
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P19 (consent-tester): - dp-cookieconsent (TYPO3, Safetykon-Pattern) als CMP-Profil hinzu — Selektoren #dp--cookie-statistics/marketing + a.cc-allow Save-Button - Neues Signal provider_details_visible: nach Kategorie-Toggle prueft Playwright ob im Banner sichtbare Provider-/Cookie-Detail-Elemente erscheinen. Bei dp-cookieconsent (Banner ohne Listing) immer False -> HIGH-Violation "Kategorie zeigt keine Provider-/Cookie-Details — Nutzer kann nicht informiert einwilligen (Art. 7 Abs. 1 DSGVO)" - main.py serialisiert provider_details_visible + cookies_set pro Kategorie P20 (Frontend-Drilldown): - Backend: check_payloads-Tabelle um Spalte 'banner' (JSON) — voller banner_result persistiert (vorher nur in-memory). ALTER TABLE Migration idempotent. - Neuer Endpoint GET /api/compliance/agent/banner/<check_id> — liefert Quality-Score, Phases, Category-Tests, Banner-Checks, alle 46 structured_checks. - Frontend: BannerTab im /sdk/agent/audit/<id> mit Quality-Cards, 3-Phasen-Cookie-Tabelle, Per-Category-Listing (mit P19-Signal rot/gruen), Banner-Verstoesse + Rechtsgrundlagen, 46-Check-Drilldown filterbar nach Severity. - Tab-Switcher in page.tsx um "Cookie-Banner-Analyse" erweitert. - Bonus: 2 alte route.ts auf Next.js 15 Promise-params umgestellt (Build-Fix). Plus: Critical-Findings-Block nutzt provider_details_visible als primaeres Signal statt nur tracking_services-Anzahl. Smoke-Test Safetykon: 4 Critical Findings im Mail, banner-Endpoint liefert 46 checks + 3 phases + 2 categories mit provider_details_visible=False. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> |
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d4d9b60007 |
feat(email): P18 — Critical-Findings-Box + Banner-Deep-Block
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Backend wirft 90% der consent-tester-Daten weg — nur 4 Felder von einem
vollen Banner-Scan landeten im Email. Phases (before_consent / after_reject
/ after_accept), banner_checks.violations mit Rechtsgrundlagen,
category_tests, 46 structured_checks, completeness/correctness-Scores
waren alle nicht sichtbar.
Backend: agent_compliance_check_routes leitet jetzt das volle banner_result
durch (15 Felder statt 4).
Renderer (2 neue Module):
1) agent_doc_check_critical.build_critical_findings_html
- ROTER Sofortmassnahmen-Block GANZ OBEN in der Email
- Erkennt: banner-violations (HIGH/CRITICAL), leere Per-Category-Lists,
DSE-Score <30%, fehlende Cookie-Richtlinie, US-Tracker ohne SCC/DPF
- Pro Issue: konkrete Sofortmassnahme + Rechtsgrundlage + Bussgeld-
Praezedenz (CNIL TikTok 5 Mio, LfDI BW 30k, EuGH Schrems II, ...)
- Wird nur gerendert wenn echte Issues vorliegen
2) agent_doc_check_banner.build_banner_deep_html
- Banner-Quality-Score-Cards (Vollstaendigkeit / Korrektheit / Verstoesse)
- 3-Phasen-Cookie-Tabelle: vor Consent / nach Ablehnung / nach Annahme
mit Cookie-Count, Tracker-Count, Auffaelligkeiten
- Per-Category-Tracker-Listing (Statistik/Marketing) — zeigt explizit
wenn eine Kategorie keine Provider listet (Safetykon-Pattern)
- Violations-Liste mit Severity-Badge + Quellen-Hint (LG Rostock, EDPB)
Smoke-Test Safetykon: alle 6 neuen Blocks rendern, kein Regression.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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e536247c20 |
feat(quaidal): backend API + frontend tab for BSI QUAIDAL data-quality controls
Wire the 195 Clean-Room QUAIDAL controls (from breakpilot-core migration 011)
into the compliance SaaS UI.
Backend:
- GET /api/v1/quaidal/stats - counts by kind + source provenance
- GET /api/v1/quaidal/controls - list, optional kind= filter
- GET /api/v1/quaidal/controls/{id} - single derived control
- GET /api/v1/quaidal/criteria - 10 QKB criteria
- GET /api/v1/quaidal/criteria/{id} - QKB with QB/MA/QM tree
Frontend:
- /sdk/quality: new "Trainingsdaten-Qualität (BSI QUAIDAL)" tab with
10 QKB cards and a drill-down modal showing the full QB→MA→QM tree
plus original BSI source link and license note.
- /sdk/ai-act: Art. 10 tile on each high-risk/unacceptable result,
linking to /sdk/quality?category=data_quality.
Pattern matches existing IACE module DIN-reference handling:
own wording, source section + URL preserved for due diligence.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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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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b87c27d104 |
fix(llm-verify): P13 — Default-Modell auf qwen3:30b-a3b (statt qwen3.5:35b-a3b)
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Bug: qwen3.5:35b-a3b liefert mit format='json' + Batch-Prompt leere
Strings zurueck ('LLM batch: empty response from model'). Im echten
Compliance-Check lief der LLM-Verifier deshalb wirkungslos —
False-Positive-Findings wie 'Vorstand nicht erkannt' (BMW: Klammer-
Liste) wurden nicht overturned.
Fix: Default auf qwen3:30b-a3b umgestellt. Verifiziert mit BMW-
Impressum-Text: representative_person wird mit Evidence 'Milan
Nedeljkovic, Vorsitzender' overturned=True markiert.
OLLAMA_VERIFY_MODEL Env-Var bleibt als Override-Moeglichkeit.
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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575644c9c5 |
feat(audit): P8 — MC-Severity raus, Email nur harte Findings, MC-Audit als Checkliste
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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>
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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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27384aea09 |
feat(cra): Phase 5 — Technical Doc + DoC Generator (Annex V + VII)
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Migration 122: compliance_cra_documents with versioning + approval workflow
- doc_type whitelist: doc_eu_conformity, doc_technical, doc_cvd_policy,
doc_update_policy, doc_sbom_report
- Status state machine: draft → reviewed → approved (+ superseded)
- Snapshot generation_context for audit trail
New module cra_doc_templates.py — pure-function generators (no DB access):
- doc_eu_conformity: EU DoC structured per CRA Annex VII (all 7 mandatory fields)
- doc_technical: Technische Dokumentation per CRA Annex V
- doc_cvd_policy: ISO/IEC 29147-compliant CVD policy with SLA table
- doc_update_policy: Patch/Update policy with Lifecycle + CSAF reference
- doc_sbom_report: Latest SBOM summary with top-10 components
Returns (title, markdown_content, requirements_coverage) — coverage tracks
how many mandatory fields are filled vs placeholders.
Backend endpoints:
- POST /documents/generate — generates doc, supersedes previous version,
increments version number atomically
- GET /documents — lists all 5 doc types (also "not_generated" stubs)
- GET /documents/{id} — full content_md
- POST /documents/{id}/approve — set status + signed_by + signed_at
Frontend:
- /documents page: 5 doc-type cards with Generate/Re-Generate buttons,
inline Markdown preview with .md download, 2-step approval flow
(reviewed → approved with signature)
- Optional params form: manufacturer, notified_body, security_contact
- Dashboard: +1 button (Dokumente, 7 buttons total)
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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cc80e59e5e |
feat(cra): Phase 4 — Vulnerability Disclosure + Post-Market Monitoring
Migration 121: compliance_cra_vulnerabilities table with full lifecycle tracking
- Status state machine: reported → triaged → patched → disclosed (+ withdrawn)
- CRA Art. 14(2) deadlines tracked: reported_to_enisa_at (24h), detailed_report_at (72h)
- CVE-ID, severity, CVSS, affected_components (JSONB), embargo_until
Backend endpoints in cra_routes.py:
- POST /vulnerabilities — create with validation (severity, CVSS range)
- GET /vulnerabilities — list with deadline-breach summary (24h/72h counters)
- PATCH /vulnerabilities/{id} — update fields + auto-set lifecycle timestamps
- DELETE /vulnerabilities/{id} — soft-delete (withdrawn)
- GET /monitoring — combined view: CRA deadlines + vuln summary + post-market checklist
Frontend:
- /vuln page: intake form, vuln cards with 24h/72h-countdown buttons,
status-transition flow with auto-timestamps
- /monitoring page: CRA deadlines (11.06.26 / 11.09.26 / 11.12.27), breach banner
if 24h/72h obligations missed, post-market checklist with deep-links
- Dashboard: +2 buttons (Vulns, Monitoring)
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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1cf5de1d45 |
feat(cra): CRA Compliance module Phase 1+2+3 (intake, scope, path, requirements, backlog, sbom, checks)
Phase 1 — Intake + Scope + Path: - Migration 119: compliance_cra_projects table (intake + classification + path + status state machine) - Backend service cra_routes.py: CRUD + scope-check + path-select - Deterministic Annex III/IV classifier (verbatim mapping from migration 059 wiki) - Path validation per classification (CRITICAL → notified_body mandatory) - Frontend: project list, dashboard, 3-step wizard (intake/scope/path) - Sidebar entry under "CRA Compliance" (red) Phase 2 — Annex I Requirements + Priorisierungs-Backlog: - cra_annex_i_data.py: 40 Annex-I requirements (8 categories), 9 measures (M540-M548), 3 CRA deadlines - Endpoints: /requirements (40 items), /backlog (priority-sorted with deadline pressure) - Frontend: requirements table with filters + expandable details, backlog with deadline banner + score-ranked table - Dashboard KPI cards (Critical count, days to CE deadline, etc.) + top-10 backlog snippet Phase 3 — SBOM Upload + Automated Checks: - Migration 120: compliance_cra_sboms (versioned uploads, CycloneDX + SPDX) - SBOM endpoints: POST /sbom/upload (format detection, summary extraction), GET /sboms - Checks reuse compliance_evidence_checks: init creates 6 default CRA checks, run executes - Real implementations: cra_security_txt (HTTP + Contact: line) and cra_tls_cert_check (TLS handshake) - Frontend: SBOM file upload + version list, Checks page with per-check URL input + Run button Backend-Reuse: gap_projects (intake pre-population), compliance_evidence_checks/_check_results. Tenant scoping via existing X-Tenant-ID header pattern. 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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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).
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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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6c7d4c7552 |
fix(vvt): correct ePaaS schema mapping + category-aware scoring
The first BMW VVT table rendered all 24 providers at 20% score because
the ePaaS extractor was reading the wrong field names. Actual schema is
nested: providers[].processings[].persistences[], NOT providers[] alone.
Correct ePaaS schema (verified against bmw.com/epaas/.../de_DE.epaas.json):
Provider: {id, name, description, processings[]}
Processing: {id, name, description, categoryId, optOutLink,
privacyPolicyLink, persistences[]}
Persistence: {id, name, domain, type, expiry, description}
Two structural changes:
1. One row per processing (not provider). BMW has 26 providers but ~91
processings spread across them (Adobe alone has ACMProcessing,
AdobeAnalytics, AdobeCampaign, AdobeTargetAnalytics, AdobeTargetPers.).
The cookie widget displays each processing separately — VVT now
mirrors that. Display name format: 'Provider Name — Processing Name'.
2. Read optOutLink/privacyPolicyLink from PROCESSING (where they live),
not provider. Persistences flatten to cookies[] with name + expiry +
description.
Plus category mapping:
advertising -> marketing
strictlyNecessary -> necessary
statistics -> statistics
functional -> functional
Category-aware scoring (cookie_link_validator.score_vendors):
- 'necessary' (technisch erforderliche, §25 Abs. 2 TDDDG): no opt-out
required, no country required. Score weight shifts to purpose +
cookie disclosure (essential cookies must list names + expiry).
- All other categories: opt-out URL still mandatory; missing opt-out
flags 'no_opt_out_url' and zeros that block of points.
Expected BMW result after this fix:
- ~91 rows (Adobe Analytics, Adform Retargeting, Akamai Infrastructure,
AWS, ..., plus ~60 strictlyNecessary processings)
- Marketing rows with present opt-out → ~75-90%
- Necessary rows with cookie+expiry → ~85-95%
- Rows missing fields → still flagged
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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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9c0cc0f59f |
feat(vvt): V2 — vendor extractors for Cookiebot/Usercentrics/Didomi/TrustArc
Backend vendor_extractor.py gets 4 new per-CMP dispatchers, mirroring the JSON schemas observed in each platform: - Cookiebot: 'Categories[*].Cookies[*]' with Vendor/Host, expiry, purpose - Usercentrics: 'services[*]' with cookieMaxAgeSeconds, processingCompanyCountry - Didomi: 'app.vendors[*]' with country + policyUrl - TrustArc: 'vendors[*]' + per-category 'Cookies' with provider All 6 named CMPs (ePaaS, OneTrust, Cookiebot, Usercentrics, Didomi, TrustArc) plus the generic-shape fallback are now mapped — every site hitting Phase B of the cascade gets a structured vendor list, scored opt-out links, and a VVT-Tabelle in the email. |
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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. |