6c223c7c9baa8b006c5a09a4577ed60a1621a4d0
11 Commits
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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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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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e61e9d9e2a |
feat(agent): progress_pct + 6 BMW-Run Verbesserungen
Backend (agent_compliance_check_routes.py):
- progress_pct (0-100%) im Job-State, ueber alle Phasen verteilt
(Laden 0-30, Profil 35-40, Pruefen 40-80, Banner 80-92, Report 95-100)
- Status-Texte vereinheitlicht ("Texte laden X/N", "Pruefen X/N")
- Firmenname fuer Email-Subject jetzt aus URL abgeleitet
(bmw.de -> "BMW", mercedes-benz.de -> "Mercedes-Benz") statt
unzuverlaessigem extracted_profile.companyName (matchte oft juris.de)
- E-Mail-Report enthaelt jetzt Banner+TCF-Vendor-Liste (build_provider_list_html)
Backend (agent_doc_check_extras.py — neu):
- build_scanned_urls_html: gepruefte URLs als Tabelle oben im Report
(transparent fuer GF, welche Quellen wirklich gezogen wurden)
- Cross-Domain-Hinweis bei >1 netloc (BMW: bmw.de / bmwgroup.com /
bmwgroup.jobs — Auffindbarkeit nach Art. 12 DSGVO)
- build_provider_list_html: Banner-Box + TCF-Vendor-Tabelle mit Spalten
Name | Kategorie | Zweck | Drittland | Rechtsgrundlage
Backend (business_profiler.py):
- §34d-GewO Versicherungsvermittler-Hinweise zaehlen nicht mehr als
"finance"-Industrie (BMW wurde dadurch falsch als B2B/finance erkannt)
- Neue Industry "automotive" (Fahrzeug/KFZ/Konfigurator/Modellpalette)
- B2B-Keywords: generische Begriffe wie "unternehmen", "beratung",
"consulting" entfernt (matchten in jedem Konzerntext)
- B2C-Fallback: bei Verbraucher-Signalen ("widerruf", "kunde",
redaktioneller Inhalt) tendiert auf b2c statt b2b
Frontend (ComplianceCheckTab.tsx):
- Progress-Balken mit Width-% und XX%-Anzeige rechts
- liest data.progress_pct aus Polling-Response
Consent-Tester (dsi_discovery.py):
- Cookie-Policy-Extraktion kritisch fixt: wait_for_function bis
body.innerText > 500 chars (BMW SPA-Rendering brauchte mehr Zeit)
- _extract_text_robust: 3-Strategien-Extraktion (Selektoren -> Body-
Cleanup -> P/LI/TD-Tags)
- _extract_text_from_iframes: liest OneTrust/Sourcepoint/Usercentrics
Iframe-Inhalte (manche Cookie-Policies leben dort)
Adressiert alle Findings aus dem BMW-Ground-Truth-Vergleich.
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d45e08e25f | fix: reduce Playwright timeout 180s→60s, increase poll limit 15→25min | ||
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08fcb5f239 |
feat(compliance-check): scenario badges + extracted profile display
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- Show extracted profile fields (company name, legal form, address, DPO, USt-IdNr) with "In Company Profile uebernehmen" button - Show Compliance Scope hints extracted from documents - Scenario badges per document: Neugenerierung (red), Korrekturen (amber), Konform (green) - Summary line shows scenario counts Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |
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ce77cde309 |
fix(compliance-check): batch LLM verification + increase poll timeout
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- LLM verify now sends ALL failed checks in one batched call instead of one Ollama call per check (80+ calls → 1 per document) - Increase frontend poll timeout from 6 min to 15 min Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |
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a127dd971b |
fix(compliance-check): resume polling after navigation away
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Save active check_id to localStorage so polling resumes when the user navigates away via sidebar and comes back. Same pattern as scan tab. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |
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ed3ebbc246 |
fix(compliance-check): send 'documents' instead of 'entries' to backend
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Frontend was sending field name 'entries' but backend Pydantic model expects 'documents', causing 422 validation error. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |
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f3751a4efa |
feat(compliance-check): show business profile + banner check result in UI
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Add two info boxes above the checklist results: - Business profile (B2B/B2C, industry, regulated profession) - Banner check status (CMP detected, violations count, cross-check hint) Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |
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0d0e705117 |
feat: Unified Compliance-Check — 8 document types in one form
New 3-tab structure: Website-Scan, Compliance-Check, Banner-Check. Compliance-Check Tab (replaces Dokumenten-Pruefung + Impressum-Check): - 8 document rows: DSI, Impressum, Social Media, Cookie, AGB, Nutzungsbedingungen, Widerruf, DSB-Kontakt - Each row: URL input + "Text laden" + file upload + manual text - "Text laden" extracts via consent-tester, shows in editable textarea - User verifies/corrects text before checking - Empty fields = "not present" → own finding Business Profiler (business_profiler.py): - Detects B2B/B2C/B2G from all documents together - Recognizes regulated professions, online shops, editorial content - Context-aware: INFO checks become PASS/FAIL based on profile Backend: /compliance-check + /extract-text endpoints Frontend: ComplianceCheckTab.tsx + DocumentRow.tsx API proxies: compliance-check/route.ts + extract-text/route.ts Also: Impressum regex fixes (Telefon, AG, Geschaeftsfuehrung) and INFO severity for context-dependent checks. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |