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cf6005a47c |
perf(audit): vendor_llm_extractor + mc_solution_generator nutzen P31 LLM-Cascade
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Beide rufen jetzt llm_cascade.call_with_cascade() statt direkter Qwen/OVH- Aufrufe. Damit: * Cache-Hit auf identische Eingaben (Valkey, 7d TTL) → ~50ms statt 4-6min beim Re-Run derselben Cookie-Doc. * Tiered Cascade automatisch: Qwen → OVH 120B → Anthropic Claude Haiku wenn lower-tier under confidence-threshold. * Confidence-Scoring (JSON-parse + items_per_input_size) entscheidet ob weiter delegiert wird. Fallback auf alte _call_ollama/_call_ovh bleibt bestehen wenn der Cascade-Aufruf scheitert. Erwartete Wirkung beim 2. VW-Lauf: ~10min statt ~25min (Cache-Hit auf identische Cookie-Doc + MC-Solutions). Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> |
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b663e2508f |
feat(audit): P107 Branchen-Benchmark-Cockpit fuer Big-4-Demos
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benchmark_extractor.py — extract_kpis() liefert 18 KPIs pro Snapshot: * vendors_total, vendors_us, vendors_non_eu (mit % je Vendor-Land) * source_breakdown (llm/library/flat_pattern/table_paste/html_table_dom) * max/avg cookies_per_vendor (Konzentrations-Mass) * cookies_in_browser, cookies_detailed_count, cookie_doc_chars * banner_detected, banner_provider, banner_violations * compliance_score, data_quality_pct (wie viele unserer Datenquellen haben Inhalt) * saving_low/high_eur (Heuristik: (vendors - 10) × 1k-5k) anonymize_kpis() ersetzt site_label durch 'OEM 1/2/3' (Industry-Prefix Map: automotive→OEM, banking→Bank, chemistry→Chem, luftfahrt→Airline). GET /api/compliance/agent/admin/benchmark?industry=automotive&sites= VW,BMW,Mercedes&anonymized=true — liefert kpis + summary (n_sites, avg_vendors, total_saving_high). Admin-Page /sdk/benchmark: * Filter-Leiste: Industry-Dropdown, Sites-Input + 5 Preset-Gruppen (Automotive OEMs / Zulieferer, Chemie DAX, Luftfahrt, Banking DAX) * Anonymize-Toggle prominent * 5 Summary-KPI-Karten oben * Vergleichstabelle 13 Spalten (Score, Vendors, US%, Drittland%, Cookies-Browser, Cookie-Doc-kB, Banner ✓/✗, Provider, Verstoesse, Saving €/Jahr, Daten-Qualitaet, Captured-Time) * Red-/Amber-/Green-Indikatoren bei US%/Score/Drittland * Big-4-Hinweis-Footer Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> |
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e2be51b0aa |
feat(audit): P106 MC-Audit-Type + P83 BUILD_SHA in Dockerfiles + P80 v2 full
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P106 — mc_audit_type.py: zentrales Quality-Thema. Klassifiziert pro MC: verifiable / process_internal / doc_internal / ambiguous. Pattern-Match auf check_question + title + fail_criteria (Schulung, AVV abgeschlossen, TOM umgesetzt, DSFA durchgefuehrt, Ausnahmen dokumentieren, kostenfrei zur Verfuegung, opt-out intern ermoeglichen, …). Interne MCs werden in der MC-Auswertung NICHT mehr als FAIL gewertet, sondern als CHECK markiert (audit_status='check'). Sie zaehlen im build_scorecard als skipped (nicht failed) damit der Score realistisch ist. build_internal_checks_block_html() rendert sie als separaten blauen Block 'Pruefungen die wir von aussen NICHT durchfuehren koennen' nach dem MC-Scorecard. Erwartete Wirkung: bei VW 95 FAILs → wahrscheinlich 30-40 echte verifiable_fails + 50-60 internal_checks. GF-Mail wird drastisch realistischer (statt 'Sie haben 95 Verstoesse' → 'Sie haben 35 extern sichtbare Themen + 60 interne Checks, bitte mit DSB klaeren'). P83 — BUILD_SHA in backend/admin/consent-tester Dockerfiles als ARG + ENV. check-rebuild-needed.sh kann jetzt deployed vs local SHA vergleichen + REBUILD REQUIRED melden. P80 v2 — check_replay.py macht jetzt vollstaendigen Replay aller post-fetch Quality-Generatoren: vendor_normalizer (Dedup), audit_quality_checks, cookie_compliance_audit, tcf_vendor_authority, cookie_value_entropy, cookie_network_tracer. Snapshots aus alter Zeit zeigen jetzt im Replay den aktuellen Audit-Stand. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> |
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bd65b6f318 |
feat(audit): Phase 2+3 — P54 + P68 + P69 + P6/P53/P55 + P31 + P80v2
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P54 — consent_diff_for_user.py: USP-Feature fuer wiederkehrende Besucher. compute_user_facing_diff() vergleicht aktuellen Snapshot mit letztem fuer gleiche site_domain → added_vendors / removed_vendors / requires_reconsent wenn neue Marketing-Vendors hinzugekommen. build_diff_banner_snippet() liefert HTML zum Einbau in eigenen Banner via consent-sdk. P68 — reverse_audit.py: Self-Audit unserer Template-Bibliothek. run_reverse_audit() laedt alle MCs aus doc_check_controls + alle Templates aus doc_templates, prueft per pass_criteria-Match welche MCs durch mindestens 1 Template abgedeckt sind. Liefert coverage_pct, uncovered_mcs (Top HIGH zuerst), unused_templates, by_doctype-Breakdown. P69 — data/ecall_regulation.json: eCall-VO (EU) 2015/758 als 7 Chunks fuer RAG-Ingest (Art. 3/6/7 + compliance_implications fuer Automotive-OEMs). Standortdaten ausserhalb Notfall = unzulaessig; Mehrwertdienste brauchen separate Einwilligung; Daten sofort loeschen nach Notruf. P6+P53+P55 — industry_library.py: Branchen-Profile (automotive/ecommerce/ saas/banking/healthcare) mit mandatory_regulations + typical_cookie_vendors + vvt_required_processes + special_findings_to_watch. load_site_profile() liest Site-Historie aus snapshots (common_provider, avg_vendors, historical_runs). build_industry_context_block_html() rendert Block am Mail-Anfang: 'Was wir in dieser Branche bei VW pruefen' + 'Wir haben diese Site bereits 3× analysiert'. P31 — llm_cascade.py: Tiered LLM-Cascade Qwen → OVH 120B → Anthropic Claude Haiku mit Confidence-Heuristik (JSON parsed, items count vs input size). Valkey-Cache (redis://) mit 7-Tage-TTL plus In-Process- Fallback. Wenn Tier-1 unter Confidence-Threshold → Tier-2, dann Tier-3. Reduziert Lauf-Zeit drastisch bei Re-Runs. P80 v2 — check_replay.py: replay nutzt jetzt audit_quality_checks mit den Snapshot-Daten. Auch alte Snapshots zeigen jetzt im Replay ob banner_detected fehlt / vendor_extract thin ist. Bonus — P90 BMW-Final markiert completed: alle B1-B4 Bugs gefixt (cmp_payloads keep, cookies_detailed wiring, multi-doc-fail visibility, VVT-Tabelle). Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> |
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8cbb513e2c |
feat(audit): Phase 1 Quick-Wins (P81 + P85 + P70 + P83) + TCF DELETE/INSERT-Fix
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P81 — tests/fixtures/golden_truth/vw_de.json: GT-Fixture mit must_find_cookies (47 VW-Cookies) + expected_vendors (Google, Adobe, Trade Desk, ...). Basis fuer kuenftige Regression-Tests. P85 — banner_screenshot_block.py + consent_scanner.py + main.py: consent-tester macht beim Banner-Detect einen base64-PNG-Screenshot (< 1.5MB). Backend rendert ihn als <img src="data:..."> direkt nach dem GF-1-Pager. Visueller Beweis 'so sah das Banner aus' fuer Dispute mit Marketing/DSB. P70 — rag_provenance.py: classify_finding_provenance() klassifiziert ein Finding als 'rag' (Norm + Quelle), 'mixed' (Norm ohne Quelle) oder 'heuristic' (eigene Interpretation). provenance_badge_html() rendert kleine Badges (✓ RAG / NORM / ⚠ HEURISTIK). Modul ist generisch, kann bei jedem Finding-Renderer einklinkt werden. P83 — scripts/check-rebuild-needed.sh: Prueft ob die im Container deployten BUILD_SHA mit local HEAD uebereinstimmen. Bei Mismatch exit 1 mit 'REBUILD REQUIRED'-Hinweis. Verhindert das 'alter Code im Container'-Problem das uns mehrfach erwischt hat (Frontend-Tabs sichtbar, Backend ohne neuen Service). TCF-Fix — tcf_vendor_authority.py: cookie_library hat keinen UNIQUE-Index auf cookie_name → ON CONFLICT war unmoeglich. Loesung: vor Insert DELETE WHERE source_name='iab_tcf_v2'. Idempotent. + per-Vendor-Commit damit ein Fail die naechsten nicht blockt. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> |
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6c35bcf116 |
fix(tcf): per-vendor commit damit ein Fail die naechsten Inserts nicht blockt
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19d4b12e07 |
fix(tcf): Schema-Mapping fuer NOT NULL constraints (domain_pattern, source_name)
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2e87b74749 |
feat(audit): P103+P104+P105 Defeat-Device-Heuristik fuer Cookies
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Drei zusammenhaengende Stufen 'Cookie-Verhalten ist anders als deklariert' — analog zum VW-Diesel-Skandal-Pattern (Pruefstand vs Realbetrieb). P103 (Stufe 3) — cookie_value_entropy.py: Klassifiziert Cookie-Werte als flag/short_id/long_token/uuid/hash/json_blob via Shannon-Entropy + Regex-Patterns. Wenn ein als 'essential' deklarierter Cookie einen 64-char-Base64-Wert hat → MEDIUM-Finding 'Defeat-Device-Heuristik'. P104 (Stufe 4) — cookie_network_tracer.py: Vergleicht Cookie-Domain mit Site-Hauptdomain + bekannten Tracker-Vendoren (50 Domains gemapped: doubleclick.net, facebook.com, demdex.net, omtrdc.net, adsrvr.org, hotjar.com, ...). Wenn ein als 'essential' deklariertes Cookie von externer Tracker-Domain gesetzt wird → HIGH. Drittland-Cookies werden als 'DRITTLAND US/CN/...' markiert (Schrems-II-Folge). P105 (Stufe 5) — tcf_vendor_authority.py: Ingest-Endpoint POST /api/compliance/agent/admin/tcf-ingest holt die IAB TCF v2 Global Vendor List (vendor-list.consensu.org/v3) und upserted sie in cookie_library mit source='iab_tcf_v2'. cross_reference_with_tcf fuzzy-matched cmp_vendors gegen die TCF-Liste — wenn Vendor in TCF als Marketing gefuehrt aber Site sagt 'Funktional' → HIGH (externe Authority widerspricht der Deklaration). Alle drei rendern eigene Mail-Bloecke im Bereich Cookies (nach cookie_audit_html, vor library_mismatch_html). Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> |
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081e4f057a |
feat(audit): Cookie-Compliance-Audit (3-Quellen-Vergleich) + Vendor-Dedup + Block-Parser
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ZENTRALER USP: cookie_compliance_audit.py vergleicht 3 Quellen * DEKLARIERT in Cookie-Richtlinie (parse_cookie_table + parse_flat) * TATSAECHLICH im Browser geladen (banner_result.phases.after_accept) * LIBRARY-Metadaten (cookie_library lookup) Liefert 3 Listen mit Compliance-Verdict: * compliant (deklariert UND geladen) — gruener Block * undeclared_in_browser (geladen NICHT deklariert) — ROTER HIGH-Block → Art. 13(1)(c) DSGVO + § 25 TDDDG Verstoss * declared_not_loaded (deklariert NICHT geladen) — gelber Hinweis → Tabelle moeglicherweise veraltet parse_cookie_table erweitert um Block-Format (5 Zeilen pro Cookie wie beim User-Copy aus VW). Findet 35+ Cookies aus Copy-Paste statt 0. vendor_normalizer.py: 50+ Aliases (Google-Familie, Adobe-Familie, Trade Desk, AdForm, ...) + Garbage-Filter (URLs, leere Strings, 'click to select', 'Mehrere OEMs'). Mergt cookies-Listen beim Dedup. _guess_vendor erweitert: Adobe-Familie (s_ecid/AMCV/demdex/mbox/...), Trade Desk (TDID/TDCPM/TTDOptOut), AdForm (uid/cid/otsid), Salesforce LiveAgent, etracker, Akamai, EDAA. audit_quality_checks: vendor-thin-Threshold jetzt dynamisch nach Cookie-Doc-Wörter (3k→10 / 6k→20 / 10k→30 / 15k+→40). VW-Test-Fixture: tests/fixtures/cookie_gt/vw_cookie_richtlinie.txt (36-Cookie-Sample fuer Regression-Tests). Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> |
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4434e3827b |
fix(audit): parse_flat_cookie_text — Anchor-Pattern fuer VW-textContent
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VW Cookie-Doc-textContent verkettet HTML-Tabellen-Zellen OHNE Whitespace: 'Permanent/Protokoll_fbcTracking Cookies (Marketing)...' Neues Pattern hat 2 Anker: * Davor: typisches End-Token einer vorherigen Zelle (Permanent/Protokoll, Session Cookie, Persistent Cookie, TagePersistent, ...) * Danach: Kategorie-Token (Tracking Cookies, Funktionscookie, Marketing, Analytics, Necessary) Dazwischen: Cookie-Name (3-50 Zeichen, alphanum/_/-) VW-Test (snapshot 4a465783): findet jetzt 40 unique Cookie-Namen, aggregiert zu 6 Vendors (Google, DoubleClick, Cloudflare, Borlabs, Meta, Unbekannter Anbieter mit 22 VW-internen Cookies). Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> |
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07cc00da11 |
feat(licenses): Stufe 2 — auto-attribution footer in compliance PDF
Extends CompliancePDFGenerator with a "Quellen & Lizenzen" section
appended to every generated compliance PDF.
The footer is built from compliance.canonical_controls + control_parent_links
directly (no HTTP hop to /licenses/aggregate — same DB connection
already open in the generator). It groups by license_rule and lists
the top 8 source regulations per bucket.
For Rule-2 entries (CC-BY-SA, OECD-Public, Apache, etc.) it emits the
mandatory attribution paragraph required by the underlying licenses.
For Rule 1 a brief reference list satisfies the auditability goal
without legal obligation. Rule 3 is identifier-only by design.
Architecture decision: this is a PLATFORM-level footer (which sources
the platform draws on overall), not a per-export filter of "only the
sources actually cited in THIS document". The latter would require
control-uuid tracking across all sections (TOM/VVT/DSFA/etc.) which
the current PDF generator does not surface — that's a follow-up scope.
The platform-level footer fulfils the immediate legal mandate that
attribution be present on the work, not buried in AGB/Impressum.
Part of Attribution-Renderer Task #23. Stufe 1 (overview page) +
Stufe 3 (SourceBadge component) already shipped in commit
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1451873194 |
fix(audit): parse_flat_cookie_text fuer VW-Style Flat-Tabellen
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VW Cookie-Doc liefert die Tabelle als FLACHEN Text ohne Spalten-Trenner: 'IDE Tracking Cookies (Marketing) Beschreibung 13 Monate Permanent TAID Tracking Cookies (Marketing) ...' parse_flat_cookie_text matched mit Regex: NAME [Tracking|Session|Funktional|...] Cookies ... [13 Monate|Session|Permanent] Backend faellt bei parse_cookie_table=[] auf parse_flat zurueck. Damit holen wir aus dem 65k VW Cookie-Doc ~30-50 Cookies + Vendors deterministisch, auch wenn der HTML-Table-DOM-Extract leer ist (was passiert wenn die Tabelle aus mehreren append-Code-Pfaden geladen wird). Bonus: _extract_dom_tables Helper in dsi_discovery.py vorbereitet fuer spaeteres Einhaengen an allen 7 DiscoveredDSI.append-Stellen. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> |
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cb5dad1a2f |
feat(audit): A Audit-Transparenz + B Tabellen-Parse + D HTML-Tables aus DOM
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Drei zusammenhaengende Fixes fuer den VW-Befund (6 Vendors statt 100+): A — audit_quality_checks.py: drei systemische Vorbehalte die IMMER prominent gezeigt werden: * banner_detected=False trotz Cookie-Doc → HIGH 'CMP-Tool ungeladen' * cookie_doc >= 30k chars aber cmp_vendors < 15 → HIGH/MEDIUM 'Vendor-Liste auffaellig kurz fuer Doc-Groesse' * submitted URL aber 0/Mini-Text → MEDIUM 'URL nicht ladbar' Rote Audit-Vorbehalt-Box ueber dem GF-1-Pager. GF-Summary sagt 'Audit unvollstaendig' statt faelschlich 'Keine kritischen Themen'. gf_one_pager nimmt audit_quality_findings in top_findings auf (BEVOR andere Findings). B — cookies_table_parser laeuft jetzt auch auf gecrawltem Cookie-Doc- Text (nicht nur bei User-Paste). Wenn der dsi-discovery-Response Tab/ Pipe-getrennte Tabellen-Reihen liefert, parsen wir sie deterministisch. D — consent-tester/dsi-discovery extrahiert jetzt zusaetzlich zum Text die <table>-Elemente aus dem DOM als list[str] (Tab-getrennt pro Zeile, mind. 2 Zellen, mind. 3 Zeilen, max 10 Tabellen pro Doc). Backend schleust diese als 'html_table'-cmp_payload ein und jagt sie zuerst durch cookies_table_parser → 100% deterministische Vendor-Extraktion ohne LLM. VW-Erwartung: aus der 65k-Cookie-Tabelle werden jetzt 30-50 Vendors deterministisch geparst statt 6 vom LLM-Cascade. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> |
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e411c4f0d3 |
feat(audit): Text-Paste-Mode pro Row — Crawler optional umgehen
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Hintergrund: VW liefert ueber URL-Crawler nur 6 Vendors statt der 100+
die in der echten Cookie-Tabelle stehen. Wenn der User die Tabelle aber
direkt von der Site kopieren kann (was bei den meisten OEM-Sites moeglich
ist), umgehen wir den Crawler komplett und parsen den Text deterministisch.
Backend:
* doc_type_classifier.py — 7 Pattern-Gruppen (§5 TMG, Art.13 DSGVO,
AGB-Klauseln, Widerrufs-Frist, Cookie-Tabellen-Header, etc). Wenn der
User Text ins falsche Doc-Type-Feld kopiert (Impressum->DSE),
detect_mismatch liefert detected + action ('reclassify' bei sehr hoher
Konfidenz, 'warn' bei medium).
* cookies_table_parser.py — Tab/Pipe/Komma/Semicolon-Separator-Auto-
Detection, Spalten-Mapping per Header-Keyword. Aggregiert Cookie-
Eintraege zu Vendor-Records (mit _guess_vendor-Fallback). Voll
deterministisch, kein LLM.
* doc_input_warnings.py — Mail-Block ueber dem Audit, der Mismatches +
Auto-Reclassifies dem User transparent macht.
* Pipeline: text gewinnt ueber url (war schon im Schema vermerkt), neue
Felder declared_doc_type / input_source / reclassify_hint in doc_entries.
Pasted-Tabellen-Vendors haben Vorrang vor Library-Fallback + LLM-Cascade
(sind 100% genau).
Frontend (DocCheckTab):
* Pro Row Mode-Toggle 'URL' / 'Text einfuegen' (lila wenn aktiv).
* Textarea (h-32, monospace) im text-mode mit kontext-spezifischem
Placeholder (Cookie-Hinweis ggue. anderen Doc-Types) und Live-
Zeichen-/Wort-Counter.
* Submit-Button accepted entries mit URL ODER text.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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7335f64f4f |
feat(founding-wizard): Per-Person IP-Assignment + Prefill + E2E-Tests
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Wizard unterstuetzt jetzt 2-4 Gesellschafter mit individuellem IP-Bereich: - Pro Gruender ein IP-Assignment-Vertrag (z.B. Benjamin: Compliance+RAG; Sharang: Security+Infrastruktur). Pro GF ein eigener Dienstvertrag. - Step 1: Prefill-Button aus Unternehmensprofil + Felder Registergericht und HRB-Nr. - Step 2: Rollen-Dropdown (CEO/CTO/CFO/COO/CPO/GF/Sonstige) statt freie Texteingabe, IP-Bereiche-Textarea pro Person. Backend: - generate_documents() iteriert pro Person fuer PER_PERSON_DOCS. - _build_person_context() injiziert ASSIGNOR_*, GF_*, IP_LIST_DETAILS aus person.ip_areas. - base_context() propagiert basics.register_court und basics.hrb_number. Tests: - 30/30 Pytest gruen (6 neue: Per-Person-Context, Slug-Helper, Registergericht-Propagation). - 4 neue Playwright-E2E-Specs (hermetisch via route.fulfill, mit Console-/Page-Error-Traps): kompletter 8-Step-Flow, Prefill-Fehlerpfad, Step-Navigation/Reset, Rollen-Dropdown + IP-Areas. - Spec setzt 'bp-sdk-cookie-consent' im addInitScript damit der CookieBannerOverlay nicht die Wizard-Buttons ueberlagert. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> |
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138d9068c4 |
fix(audit): VW-Cookie-Tabelle — Library-Fallback + Pattern-Extract verstaerkt
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VW-Lehre: cmp_vendors=6 (alle LLM-grob) wurde als ausreichend gewertet, obwohl die echte Cookie-Tabelle 30+ Eintraege hat. 3 Fixes: 1. fallback_vendors_for_run skip-Schwelle: existing_vendor_count >= 3 war zu niedrig. Jetzt nur skip wenn < 5 Cookies UND >= 5 Vendors schon vorhanden. 2. Library-Fallback wird jetzt aufgerufen bei < 20 cmp_vendors (statt < 3). VW-typische Setups (6 LLM-grob + 30 aus Library) bekommen damit eine vollstaendige Vendor-Liste. 3. _extract_cookie_names_from_doc: regex-Pattern-Extract aus dem Cookie-Doc-Text selbst — sucht nach 'NAME Tracking Cookies (Marketing)' etc. Findet Cookie-Namen die NICHT im Browser-Jar landen (z.B. nur nach Consent geladen werden). Diese werden zusaetzlich durch die Library matched. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> |
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c281464071 |
feat(audit): P71 JC-vs-AVV Entscheidungsbaum
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jc_avv_decision.py: detect_ambiguous_jc_avv prueft ob DSE-Text sowohl JC-Signale (gemeinsame Auswertung, Schwesterunternehmen, Konzern...) als auch AVV-Signale (Auftragsverarbeiter, weisungsgebunden...) enthaelt. Bei Treffer rendert build_jc_avv_decision_html einen Block mit 4 EDPB- basierten Leitfragen + jeweiliger Empfehlung. Quellen: EDPB Guidelines 7/2020, EuGH C-25/17, C-40/17. In Mail-Render zwischen Solutions-Block und VVT eingehaengt. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> |
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6dc427a754 |
fix(audit): VW-404-Recovery + P52 LLM-Merge + P51 Banner-UX-Checks
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VW-404-Fix: submitted_types zaehlt jetzt nur Doc-Types mit >= 200 Zeichen echtem Text. Eine eingegebene URL die 404/Mini-Text liefert (VW cookie- richtlinie.html) wird als 'missing' behandelt, sodass Auto-Discovery alternative URLs auf der Homepage probiert. In-place-Update statt Duplicate-Entry, rejected_url wird fuer Audit-Transparenz aufgehoben. P52 LLM-Cascade Merge: vendor_llm_extractor laeuft jetzt bei < 5 Vendors (nicht nur bei 0), und die Ergebnisse werden MIT existing cmp_vendors gemerged statt zu ueberschreiben. VW-typische Setups (Generic CMP + 0 cmp_payloads) bekommen damit den Text-basierten Vendor-Layer dazu. P51 — banner_consistency_checks erweitert: * check_banner_copyability: scannt banner_html nach user-select:none / oncopy=return false / onselectstart. MEDIUM Finding wenn Banner-Text nicht kopierbar (Art. 7 (2) DSGVO). * check_consent_history: prueft auf 'Meine Einwilligungen' / Consent- Historie / Datenschutz-Cockpit. MEDIUM wenn keine sichtbare Historie (Art. 7 (3) — Widerruf muss so einfach wie Erteilung sein). Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> |
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309c10c203 |
feat(audit): P72 MC-Scope-Filter + P73 MC-Solution-Generator
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P72 — rag_document_checker LEFT JOINs canonical_controls.scope_doc_type.
_filter_by_canonical_scope wirft MCs raus deren scope explizit auf
einen inkompatiblen Doc-Type zeigt (Mapping in _SCOPE_COMPATIBLE).
Konservativ: 'other'/NULL/'process' bleiben drin — Heuristik v1 ist
noch nicht stark genug fuer hartes Filtern.
Erwartete Wirkung: ~10-15% weniger irrelevante MCs pro Doc, weil z.B.
ein TOM-MC nicht mehr als DSE-Finding auftaucht.
P73 — mc_solution_generator.py: Qwen->OVH Cascade generiert pro HIGH/
CRITICAL-Fail eine konkrete Einfuege-Empfehlung mit Anchor (wo + was)
und Aufwand-Schaetzung. JSON-Schema {solution_text, anchor_hint,
effort_min}. In-process LRU-Cache (500 entries) per (mc_id, doc_md5).
Max 3 Solutions pro Doc-Type, global Cap 8 — haelt Latenz < 60s. Bloecke
werden im Mail-Render unter VVT als 'Loesungs-Vorschlaege (KI-generiert)'
eingehaengt. Disclaimer: kein Rechts-Beratung, mit DSB pruefen.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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4183379dc5 |
feat(audit): P33 3-Spalten-Vendor-Konsistenz (DSE/Cookie-Doc/Banner)
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check_three_source_vendor_consistency: scannt DSE-, Cookie-Doc- und Banner-Vendor-Liste auf 15 typische Vendor-Signaturen (Google Analytics, Meta Pixel, Hotjar, HubSpot, LinkedIn Insight, ...). Listet Vendors die in mind. einer Quelle stehen, aber nicht in allen sources_with_data. Liefert MEDIUM-Finding mit konkreter 'fehlt in: DSE, Banner-Liste'- Liste pro Vendor. Empfehlung: zentrale Vendor-Liste pflegen + in alle drei Dokumenttypen propagieren. (Art. 13(1)(c)+(e) DSGVO) Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> |
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c93c88577c |
feat(audit): P88 PDF-Export via WeasyPrint
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GET /api/compliance/agent/snapshots/{id}/pdf liefert application/pdf
mit dem vollen Audit-Mail-Inhalt im A4-Print-Layout (Header mit
Site/Timestamp/Snapshot-ID, Seitenzahlen unten rechts).
check_replay.py liefert jetzt zusaetzlich 'full_html' (nicht nur
500-char-preview), damit der PDF-Renderer das komplette HTML hat.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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3207acea3e |
fix(audit): Replay-Pipeline um P35/P77/P78/P36 Signals-Block ergaenzen
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check_replay.py rendert jetzt auch die Textsignal-Findings (Save-Label- Ambiguitaet, Cookies-in-DSE-Akzeptanz, JC-Klausel positiv, Social-Embeds). Damit hat der Replay-Test parity mit der echten Mail-Pipeline. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> |
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9f06911ff9 |
feat(audit): Cookie-Library-Fallback fuer VW-Pattern (kein bekanntes CMP)
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Wenn nach Standard-Extract + Phase-G + LLM-Cascade weiterhin < 3 cmp_vendors aber >= 5 Cookies im after_accept stehen (typisch: Custom-CMP wie VW 'cookiemgmt'), matcht der Fallback die Cookie-Namen gegen die compliance.cookie_library und rekonstruiert Vendor-Records aus den Library-Eintraegen. Hintergrund: VW Run de2a029e zeigt 4 Vendors trotz 28 after_accept-Cookies. cmp_payloads ist 0 (kein bekanntes IAB-Tool erkannt) und die hinterlegte Cookie-URL liefert 404. Die DSE ist mit 34k zwar substanziell, listet aber keine Vendor-Tabelle. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> |
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4171cf0efd |
feat(audit): P36 Social-Media-Einbindungs-Check
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check_social_embedding: erkennt direkte FB/Insta/Twitter/YouTube- Embeds (connect.facebook.net, platform.twitter.com etc) vs Heise-Shariff vs 2-Klick-Loesungen (Embetty). Direkte Embeds ohne Schutz = HIGH (EuGH C-40/17 Fashion-ID — der Site-Betreiber wird zum gemeinsam Verantwortlichen und braucht Einwilligung VOR dem Drittanbieter-Call). Shariff oder 2-Klick erkannt = INFO (positives Signal). Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> |
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30e43afba6 |
feat(audit): P86 Branchen-Benchmark + P35/P77/P78 Textsignale
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P86 — industry_benchmark.py: zieht alle Snapshots mit derselben scan_context.industry, berechnet Median + Percentile, rendert 'Sie 42% — Automotive-Median 58% (Stichprobe: 12)'. Min Sample 3. P35 — banner_text 'Speichern' ohne 'Ablehnen' = MEDIUM. Mehrdeutiges Label nach EDPB 03/2022 Deceptive-Design-Guidelines. P77 — DSE mit prominenter Cookie-Sektion (Vendor-Hints: Speicherdauer, Anbieter, Datenkategorie) ersetzt die Forderung nach separater Cookie-Richtlinie. Positives Signal statt False-Positive. P78 — Art. 26-Klausel im DSE-Text erkannt → positives Signal 'JC-Konstrukt dokumentiert'. Vermeidet False-Positive bei Konzern-Schwester-Kooperationen. Alle in Mail eingehaengt: Branchen-Block nach GF-1-Pager, Signale-Block nach Konsistenz-Check. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> |
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df8832c521 |
feat(audit): P75 Banner-vs-CMP + P84 Diff-Mode + P74/P96/P97 Doc-Types
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P75 — check_banner_vs_cmp_partner_count: wenn Banner-Text 'N Partner' nennt und N < cmp_vendors * 0.6, HIGH-Finding (Art. 13(1)(e) DSGVO). Erkennt Verharmlosung der tatsaechlichen Vendor-Anzahl. P84 — run_diff.py: vergleicht aktuellen Lauf mit letztem Snapshot derselben Site (set-Diff auf normalisierten Finding-Labels). Block ueber dem GF-1-Pager: 'Seit letztem Lauf: X Findings weg, Y neue'. USP — keiner der grossen Anbieter hat das. P74/P96/P97 — Labels fuer legal_notice (Rechtliche Hinweise / IP / Forward-Looking), dsa (Art. 12+17 Digital Services Act), lizenzhinweise (OSS-Compliance) in _DOC_TYPE_LABELS registriert. Echte Pflichtangaben- Checks kommen separat. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> |
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7842c95532 |
feat(audit): P92 CMP-Tool-Verfuegbarkeit + P94 Banner-vs-Cookie-Doc-Konsistenz
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P92 — Wenn der Nutzer 'Anpassen'/'Einstellungen' klickt und der CMP-Settings-Bereich kein Fehlerfreies Laden zeigt (Error, Timeout, <80 Zeichen ohne Kategorien, keine Toggles), ist das ein HIGH- Finding. Granulare Wahl formal vorhanden, faktisch nicht funktionsfaehig (Art. 7 (3) DSGVO + EDPB 03/2022). P94 — Cookie-Liste im Banner-Settings vs Cookie-Richtlinie. Heuristik extrahiert Cookie-Namen aus dem Cookie-Doc-Text (regex auf typische camelCase/_underscored Patterns + Vendor-Prefixes _ga/_gid/ot_/uc_). Wenn |only_in_doc| >= 5 ODER |only_in_banner| >= 3 → MEDIUM-Finding. |only_in_doc| >= 15 UND |only_in_banner| >= 5 → HIGH. Beide Findings landen im neuen Mail-Block 'Banner-Konsistenz-Pruefung' (amber-yellow) zwischen Mismatch-Block und VVT. Auch in check_replay.py eingehaengt. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> |
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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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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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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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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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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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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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