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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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9c11b5463c |
fix(audit): P98 + P100 — Cookie-Tabellen-Whitespace + Anpassen-Button-Check
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P98: HTML-Tabellen-Zellen wurden bei VW-Cookie-Richtlinie ohne Whitespace
verkettet ('smartSignals2UiDsmartSignals2sUiDsmartSignals2CPs...'). Grund:
el.textContent ignoriert Block-Element-Grenzen. Fix: innerText (whitespace-
respecting) statt textContent. Cookie-Namen werden jetzt einzeln erkannt —
VW-Lauf sollte ~100 Cookies statt 1 finden.
P100: Banner-Check fuer 'Anpassen'/'Einstellungen'-Button im Initial-Banner.
VW-Pattern: nur 2 Buttons (Nur technisch notwendige / Alle akzeptieren),
keine granulare Wahl vor Akzeptanz/Ablehnung. Faktische Manipulation
Richtung Pauschal-Akzeptanz. HIGH-Finding nach EDPB 5/2020 §82.
Pattern: anpassen/einstellungen/cookie-einstellungen/manage cookies/
preferences/customize.
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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189918b043 |
fix(cmp): stricter heuristic + only replace DOM when CMP is strictly larger
Two bugs observed in BMW BMW test run: 1. Generic JSON heuristic captured /de-de/login/bmw/api/flyout/data (4KB, user login fly-out data) and reconstruct_generic produced 56 words of noise. The CMP-prefer logic then 'replaced' the 185-word imprint DOM extraction with those 56 words because self_wc(185) < 300 — even though cmp_wc(56) < self_wc(185). 2. The strict prefilter list was too short. Login/auth/cart endpoints often have category-shaped JSON without being cookie policies. Fixes: - dsi_discovery: replace DOM with CMP only when cmp_wc > self_wc AND meets one of the existing conditions. Tiny captures can no longer silently destroy a bigger DOM extraction. - cmp_extractor: skip non-cookie URLs (/login, /auth, /user, /session, /cart, /checkout, /search, /flyout, /menu, /nav, /translation, /i18n, /locale, /feature-flag). - cmp_extractor: require ≥5KB payload size — real CMP policies are always larger (BMW ePaaS is ~393KB). Tiny matches drop out before reconstruction. |
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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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5f2da1de88 |
feat(consent-tester): Phase E — self-improving CMP library
cmp_discovery_log.py:
- sqlite log at /data/cmp_discoveries.db: every LLM-discovered CMP
pattern recorded with domain, strategy, value, sample text
- Auto-promote (user-chosen 'voll automatisch' mode): when LLM returns
strategy=url AND extracted text >= 800 words, write a new module
/data/auto_cmp/auto_<slug>.py with derived regex matcher + reconstruct
- record_discovery() called from dsi_discovery._try_llm_cascade on success
cmp_library/_registry.py:
- Loads both hand-written modules from services/cmp_library/ AND
auto-promoted modules from /data/auto_cmp/ (CMP_AUTO_DIR env)
- Auto modules use importlib.util.spec_from_file_location, no package
install needed; restart consent-tester to pick up new ones
dsi_discovery.py:
- _try_llm_cascade now calls record_discovery() on every successful
LLM analysis (cached AND fresh)
main.py:
- GET /cmp-discoveries — admin endpoint listing all logged discoveries
- DELETE /cmp-discoveries/{id} — rollback (unlinks auto_*.py)
This closes the self-improving loop: first encounter with a new CMP fires
the LLM (cost) → discovery is auto-promoted → all future runs against the
same vendor pattern hit Phase B (Named CMP) at <50ms with no LLM call.
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2400aa6a9e |
feat(consent-tester): Phase C+D — LLM cascade fallback (Qwen → OVH)
New module consent-tester/services/cmp_llm_fallback.py:
- LLMCookieExtractor: single-endpoint adapter (Ollama OR OpenAI-compat)
- LLMCascade: tries Qwen (local Mac Mini Ollama) first; falls through to
OVH (managed 120B) when Qwen returns no usable strategy
- LLMCascade.from_env(): reads OLLAMA_URL/CMP_LLM_MODEL + OVH_LLM_URL/
OVH_LLM_KEY/OVH_LLM_MODEL from environment
- LLM returns JSON {strategy: url|selector|text, value: ...}
- Valkey-backed cache per netloc (cmp:hint:<netloc>, 7-day TTL) — next run
against the same domain skips the LLM entirely
dsi_discovery.py:
- Wired network_log collector (URL/status/content-type/size of every JSON
response on the page) — passed to LLM prompt as observation
- After Named CMP (Phase B) + Heuristic (Phase A) both fail AND DOM
< 300 words: invoke LLMCascade.analyze(...)
- _apply_llm_hint executes the LLM's strategy: refetch URL via Playwright
request context, query DOM selector, or use text directly
- Cache HIT path: apply cached hint, only fall back to LLM if cache is stale
docker-compose.yml:
- consent-tester gets env vars + cmp-data volume (for Phase E)
- All LLM endpoints configurable via env, sensible defaults
consent-tester/requirements.txt:
- redis>=5.0 (asyncio client, Valkey-compatible)
- httpx>=0.27
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17a93bc694 |
fix(consent-tester): prefer CMP-JSON over thin DOM extraction
Previous threshold (DOM < 300 words) missed the BMW case where Playwright extracted 346 words of pure site navigation. The CMP JSON had 1673 words of real policy content but was discarded. New heuristic: prefer CMP when ANY of: - DOM < 300 words (existing) - CMP text >= 1000 words (authoritative at scale) - CMP text >1.5x longer than DOM |
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1792c6f896 |
fix(consent-tester): capture CMP JSON to extract dynamically-loaded cookie policies
BMW (and other big enterprise sites) do NOT render cookie policies as static HTML. Their widget loads structured data from a JSON endpoint (BMW: ePaaS at /epaas/prod/policypage/.../<locale>.epaas.json) and renders it client-side after consent. Our DOM extraction therefore only captured site navigation (603 words of header/footer chrome), not the actual policy. New module consent-tester/services/cmp_extractor.py: - CMPCapture: response listener that catches policy JSON during navigation - Reconstructors for ePaaS (BMW) + OneTrust placeholder - Returns Cookie-Richtlinie text built from policyPageMetadata + categories + providers (BMW: 1673 words reconstructed vs. 603 noise) dsi_discovery.py: - Attach CMPCapture before page.goto - After self-extraction: if rendered DOM < 300 words AND CMP captured a payload, prefer the CMP-reconstructed text. This bypasses the empty '.cookie-policy' div problem entirely. |
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e61e9d9e2a |
feat(agent): progress_pct + 6 BMW-Run Verbesserungen
Backend (agent_compliance_check_routes.py):
- progress_pct (0-100%) im Job-State, ueber alle Phasen verteilt
(Laden 0-30, Profil 35-40, Pruefen 40-80, Banner 80-92, Report 95-100)
- Status-Texte vereinheitlicht ("Texte laden X/N", "Pruefen X/N")
- Firmenname fuer Email-Subject jetzt aus URL abgeleitet
(bmw.de -> "BMW", mercedes-benz.de -> "Mercedes-Benz") statt
unzuverlaessigem extracted_profile.companyName (matchte oft juris.de)
- E-Mail-Report enthaelt jetzt Banner+TCF-Vendor-Liste (build_provider_list_html)
Backend (agent_doc_check_extras.py — neu):
- build_scanned_urls_html: gepruefte URLs als Tabelle oben im Report
(transparent fuer GF, welche Quellen wirklich gezogen wurden)
- Cross-Domain-Hinweis bei >1 netloc (BMW: bmw.de / bmwgroup.com /
bmwgroup.jobs — Auffindbarkeit nach Art. 12 DSGVO)
- build_provider_list_html: Banner-Box + TCF-Vendor-Tabelle mit Spalten
Name | Kategorie | Zweck | Drittland | Rechtsgrundlage
Backend (business_profiler.py):
- §34d-GewO Versicherungsvermittler-Hinweise zaehlen nicht mehr als
"finance"-Industrie (BMW wurde dadurch falsch als B2B/finance erkannt)
- Neue Industry "automotive" (Fahrzeug/KFZ/Konfigurator/Modellpalette)
- B2B-Keywords: generische Begriffe wie "unternehmen", "beratung",
"consulting" entfernt (matchten in jedem Konzerntext)
- B2C-Fallback: bei Verbraucher-Signalen ("widerruf", "kunde",
redaktioneller Inhalt) tendiert auf b2c statt b2b
Frontend (ComplianceCheckTab.tsx):
- Progress-Balken mit Width-% und XX%-Anzeige rechts
- liest data.progress_pct aus Polling-Response
Consent-Tester (dsi_discovery.py):
- Cookie-Policy-Extraktion kritisch fixt: wait_for_function bis
body.innerText > 500 chars (BMW SPA-Rendering brauchte mehr Zeit)
- _extract_text_robust: 3-Strategien-Extraktion (Selektoren -> Body-
Cleanup -> P/LI/TD-Tags)
- _extract_text_from_iframes: liest OneTrust/Sourcepoint/Usercentrics
Iframe-Inhalte (manche Cookie-Policies leben dort)
Adressiert alle Findings aus dem BMW-Ground-Truth-Vergleich.
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fca67c1f43 |
fix: accordion close bug + merge multi-page DSIs (BMW fix)
1. _expand_all_interactive(): Only click aria-expanded="false" buttons. Before: clicked ALL accordion buttons including open ones → BMW's pre-expanded accordions got CLOSED, reducing text from 1151 to 361w. 2. _fetch_text() + /extract-text: merge ALL documents found on a page (max_documents=10 instead of 1). BMW splits DSI across 5 sub-pages that the discovery finds as separate documents — now merged. 3. Tab panels: unhide hidden tabpanels instead of clicking tabs (clicking tabs can hide the currently visible panel). Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |
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5e317d2f0f |
fix: text extraction 50k char limit was root cause of all Spiegel FNs
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ROOT CAUSE: main.py line 338 truncated full_text at 50,000 chars. Spiegel DSI has 107,720 chars (13,705 words) — only 47% was extracted. DSB, Art. 77, Betroffenenrechte were all in the truncated portion. Fixes: 1. Raise text limit from 50k to 200k chars in API response + discovery 2. click_button(): add iframe fallback for Sourcepoint/Quantcast 3. dsi_helpers: iterate ALL page.frames for consent buttons 4. Profiler: only check impressum (not full text) for regulated professions, and "rechtsanwalt" must be in first 500 chars (company description) 5. GT: save full Spiegel DSI text (13,705 words) as reference Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |
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b2c1f0ae84 |
fix(consent): add Sourcepoint iframe handler + banner_detector fallback
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Root cause: Spiegel DSI text was truncated because Sourcepoint consent wall was not dismissed — dsi_helpers.py had no Sourcepoint handler. Fixes: 1. Add Sourcepoint iframe click (frame_locator + .sp_choice_type_11) 2. Add banner_detector fallback (reuses 30 CMP selectors from scanner) 3. After banner dismiss, wait and re-navigate if page redirected 4. Add "Zustimmen und weiter" to generic text button list Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |
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c702260ec1 |
fix: 5 regex bugs + text extraction scroll + GT update
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Root cause: Spiegel DSI text was truncated (lazy-loading) — the rights/DSB/complaints sections at the bottom were never extracted. Fixes: 1. Text extraction: scroll to bottom before innerText (dsi_discovery.py) 2. V.i.S.d.P.: add "verantwortlicher i.s.v." + "§18 Abs. N MStV" pattern 3. USt-IdNr: add "umsatzsteuer-id" + "DE 212 442 423" (with spaces) 4. Profiler: remove generic "anwalt"/"praxis" (false positive on Spiegel "Redaktionsanwalt"), keep only "rechtsanwalt", "kanzlei" etc. 5. Section splitter: auto_fill_from_dsi() fills empty Cookie/Social-Media rows from sections found in the DSI text Ground Truth 06-spiegel.md fully rewritten with verified data from live website — 3 L1 False Negatives identified (DSB, Beschwerderecht, Betroffenenrechte all present on website but not in extracted text). Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |
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fde2f551d7 |
fix: Add impressum keywords to dsi_discovery.py inline DSI_KEYWORDS
The inline DSI_KEYWORDS in dsi_discovery.py was missing 'impressum'. This caused self-extraction to skip impressum pages, returning datenschutz text instead. Added: impressum, anbieterkennzeichnung, imprint, legal notice, site notice. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |
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686834cea0 |
feat: 4 remaining tasks — EU institutions, banner integration, JS-sites, Caritas fixes
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1. EU Institution Checks (Verordnung 2018/1725): - New doc_type "eu_institution" with 9 L1 + 15 L2 checks - Both German + English patterns (EU institutions are multilingual) - Auto-detection via "2018/1725", "EDSB", "EDPS" keywords - Correct article references (Art. 15 instead of 13, Art. 5 instead of 6) 2. Banner Check Integration: - banner_runner.py maps scan results to 36 L1/L2 structured checks - BannerCheckTab shows hierarchical ChecklistView with hints - 3-phase summary (cookies/scripts before/after consent) - /scan endpoint now includes structured_checks in response 3. JS-heavy Website Fixes (dm, Zalando, HWK): - dsi_helpers.py: goto_resilient (networkidle→domcontentloaded fallback) - try_dismiss_consent_banner before text extraction - PDF redirect detection (dm.de redirects to GCS PDF) 4. Caritas False Positive Fixes: - Phone regex allows parentheses: +49 (0)761 → now matches - "Recht auf Widerspruch" (3 words) + §23 KDG → matches Art. 21 - Church authorities: "Katholisches Datenschutzzentrum" recognized Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |
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608fb7faf5 |
fix: DSI self-extraction + banner L1/L2 check definitions
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1. DSI Discovery fix for direct-URL use case (e.g. example.com/datenschutz):
- Self-extraction: if the URL itself is a DSE page, extract its text
directly from the page body (main/article/content element)
- Remove "datenschutz" from NOISE_TITLES — it's a legitimate doc title
- Fixes safetykon.de/datenschutz returning 0 documents
2. Banner check definitions (36 checks: 6 L1 + 30 L2):
- consent-tester/checks/banner_checks.py with expert-level hints
- EDPB 3/2022, CNIL rulings, EuGH C-673/17, §25 TDDDG references
- check_key maps to existing consent_scanner check codes
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
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e494cf62bb |
fix: Increase page load timeouts — IHK site needs >30s for networkidle
- Initial page.goto timeout: 30s → 60s (IHK loads many JS resources) - Per-page navigation timeout: 20s → 45s (heavy JS sites) - Reduced extra wait from 3s+1s back to 2s+0.5s (goto timeout handles slow loads) - Playwright scanner page timeout: 20s → 45s Root cause: IHK website has heavy JavaScript that takes >30s to reach 'networkidle' state, causing DSI discovery to fail immediately. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |
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d547e63663 |
fix: DSI dedup prefers 'Datenschutzinformation*' titles + better JS content extraction
Bug 1 fix: When merging documents with identical word_count, prefer titles starting with 'Datenschutzinformation' over generic section headings like 'Zweck und Rechtsgrundlage'. This restores the main 'Datenschutzinformationen zum Internetangebot' document. Bug 2 fix: After navigating to a document page, wait 3s (was 2s) for JS content loading, then try 10+ content selectors before falling back to body text (with nav/header/footer removed). Handles IHK-style JS navigation where content loads after page.goto() completes. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |
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6c5e086356 |
fix: DSI dedup — skip anchor links, filter noise, merge duplicates + fix false positives
Dedup fixes: - Anchor links (#cookies, #betroffenenrechte) on same page are skipped entirely - Noise titles filtered: 'drucken', 'nach oben', 'Datenschutz' (too generic) - Documents with < 50 words filtered (navigation snippets) - Documents with identical word_count merged (same page, different title) - URL-only titles filtered False positive fixes (dsi_document_checker.py): - 'Kontaktdaten des Verantwortlichen' pattern for controller check - 'Zweck und Rechtsgrundlage' combined heading pattern - 'Welche Daten werden verarbeitet' question-style headings - 'Betroffenenrechte' as standalone heading - 'Welche Rechte hat der Betroffene' question pattern - 'Daten werden geloescht' retention pattern - 'Auftragsverarbeiter' as recipient indicator Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |
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7c7513525e |
feat: Document-centric scan results + DSI deduplication
DSI Dedup (consent-tester): - Only H1/H2 headings count as documents (not H3/H4 sub-sections) - Sub-sections (Cookies, Betroffenenrechte, Social Media) are part of parent document's full text, not separate documents - Reduces IHK result from 30 to ~11 real documents Backend (agent_scan_routes): - ScanFinding gets doc_title field linking each finding to its document - doc_title set when creating DSI findings for document attribution Frontend (ScanResult.tsx): - 3 sections: Services table, Document cards, General findings - Documents: expandable cards with completeness bar (green/yellow/red) - Findings grouped under their parent document - Each card shows: title, word count, findings count, % completeness - Findings without doc_title go to "Allgemeine Findings" section Email Summary (agent_scan_helpers): - Findings listed under their parent document - General findings in separate section - No more flat mixed list Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |
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a846bd8910 |
fix: Exhaustive crawl — no arbitrary page/document limits
Both scanners now search until done, not until a counter runs out: playwright_scanner.py: - Default max_pages raised from 15 to 50 - Added 3-minute timeout as safety net - Recursive link discovery on EVERY visited page (not just DSE pages) - Stops when: all links visited OR max_pages OR timeout dsi_discovery.py: - Default max_documents raised from 30 to 100 - Added 5-minute timeout as safety net - Recursive: on each visited page, searches for MORE DSI links - Processes ALL discovered links exhaustively - Stops when: no more pending links OR max_documents OR timeout The scanners now behave like a real user: they follow every relevant link they find, and on each new page they look for more links. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |
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4e63a6050d |
feat: Generic legal document discovery (DSI, AGB, Widerruf, Cookie-Richtlinie)
New service: dsi_discovery.py — finds ALL legal documents on any website:
- Technology-agnostic: HTML, SPA, WordPress, Typo3, custom CMS
- Structure-agnostic: accordions, sidebars, footers, inline links, tabs
- Format-agnostic: HTML pages, anchor sections, PDFs, cross-domain links
- Language-agnostic: 26 EU/EEA languages with document-type keywords
Document types discovered:
- Datenschutzinformationen / Privacy Policies (Art. 13/14 DSGVO)
- AGB / Terms of Service / Nutzungsbedingungen
- Widerrufsbelehrung / Right of Withdrawal (§355 BGB)
- Cookie-Richtlinie / Cookie Policy
- All cross-domain variants (e.g. help.instagram.com from instagram.com)
API: POST /dsi-discovery { url, max_documents }
Returns: list of documents with title, url, language, type, word_count, text_preview
Features:
- Expands all accordions, details, tabs, dropdowns before scanning
- Follows cross-domain links (same registrable domain)
- Re-expands after navigation back to source page
- Handles anchor links (#sections) separately from full pages
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
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