ea4dbb223fbd6324661665b078fd5ccef0ae398b
343 Commits
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ea4dbb223f |
feat(vvt): per-vendor extraction + opt-out check + VVT table in email (V1)
When a known CMP (ePaaS, OneTrust) renders the cookie policy, we now
extract structured vendor records, probe their opt-out + privacy URLs,
score each vendor (0-100), and append a 'VVT-Vorschlag' table to the
compliance email — one row per vendor, sortable by compliance score.
consent-tester:
- DSIDiscoveryResult.cmp_payloads: surfaces raw CMP JSON to callers
- DSIDiscoveryResponse: new cmp_payloads field
- discover_dsi_documents sets cmp_payloads from cmp_capture
- cmp_library/{epaas,onetrust}.py: new extract_vendors(d) returning
list[VendorRecord]
backend:
- _fetch_text() now returns (text, cmp_payloads) tuple
- doc_entries store cmp_payloads per doc (mostly cookie)
- _autodiscover_missing forwards homepage payloads to the cookie entry
- New module vendor_extractor.py: dispatches ePaaS/OneTrust/generic
schemas; dedupes vendors across multiple payloads
- cookie_link_validator.py extended with validate_vendor_urls(vendors)
and score_vendors(vendors) — 0-100 score per vendor based on name,
purpose, country, opt-out reachable, privacy URL reachable, cookies
with names + expiry
- agent_doc_check_extras.build_vvt_table_html: renders the table
- Route appends VVT HTML after the provider list, before the
document-by-document report
- Response JSON gains cmp_vendors for future frontend rendering
Example for BMW: ~30 ePaaS providers → table with Name | Kategorie |
Sitz | Cookies | Opt-Out (✓/✗) | Privacy (✓/✗) | Score. Sorted by
score ascending so the worst-compliant vendors are at the top.
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c9c0fb5965 |
feat(cookie-check): enhanced patterns + active opt-out link validator
cookie_checks.py: - cookie_names_listed: now also matches CMP placeholder notation (BMW: 'Adfpc###', 'CT###') and 'Diese Datenverarbeitung verwendet die folgenden Cookies oder ähnliche Technologien' as list-shape signal. Cryptic vendor names like 'audience', 'adformfrpid' are accepted via the surrounding markup, not by hard-coding each one. - cookie_providers_named: new pattern 'Gesetzt von: <Firma>' (BMW/ePaaS per-cookie vendor naming) + recognition of full legal-form names (Adform A/S, BMW AG, Adobe Systems Software Ireland Limited). - cookie_duration_values: now matches 'Ablauf: 1 Jahr' / 'Speicherdauer: 30 Tage' (BMW format) in addition to the legacy '<n> <unit>'. New L1 + L2 checks for controller in cookie-policy: - cookie_controller (L1): the cookie policy must name Verantwortlich(er) - cookie_controller_address (L2): PLZ + Ort or address keywords - cookie_controller_contact_or_link (L2): email/phone OR link back to Datenschutzerklärung (the practical equivalent — BMW does this) New L2 checks (parented under opt_out): - cookie_optout_links: detects per-provider opt-out URLs in the text - cookie_privacy_policy_links: per-provider privacy-policy URLs New service: cookie_link_validator.py - extract_links(text): pulls all https?://… URLs that follow 'Opt-Out Link:' / 'Link zur Privacy Policy:' (deduped) - validate_links(links): probes every URL concurrently (HEAD first, GET fallback for 405/403). 10 parallel, 8s per request, 60s batch cap. Returns reachable=True/False + status + final_url. - build_check_items(): renders 2 CheckItems (opt-out + privacy-policy), each pass if ALL links 2xx/3xx, fail with up-to-5 broken-link examples. Hook in _check_single: doc_type=='cookie' triggers the validator after regex+MC checks. Recomputes correctness with the new L2 items. This addresses two concrete BMW observations: 1. BMW's per-cookie structure (Name + Zweck + Ablauf, Gesetzt von: …, Opt-Out Link: …) now recognised → 'Konkrete Cookie-Namen aufgelistet' and 'Konkrete Speicherdauern' should pass. 2. Defective opt-out URLs surface as compliance findings rather than silently passing — Art. 7(3) DSGVO requires a working withdrawal path per provider. |
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b090662524 |
fix(compliance-check): respect auto-discovery 'not found' verdict; DSB not canonical
Two related bugs in the BMW test result:
1. AGB rendered as 'MANGELHAFT 0/13' even though BMW has no public AGB:
- Auto-discovery correctly returned 'not found' for AGB (no link on
bmw.de matches AGB keywords).
- But auto_fill_from_dsi then found the substring 'AGB' in a section
of the DSI and pseudo-filled the AGB entry with a 264-word DSI
fragment.
- cross_search_documents would have done the same.
- Both now skip entries where discovery_attempted=True AND
auto_discovered=False — the 'not found' verdict stands.
2. DSB-Kontakt rendered as a separate 100% OK document with 7566 words
= the entire DSI text:
- GDPR practice: the DSB is named *inside* the DSI as an email or
contact block (Art. 13(1)(b)), not as a stand-alone page.
- cross_search_documents had been assigning the full DSI to the DSB
row because it matched 'datenschutzbeauftragte' keywords.
- DSB removed from _ALL_DOC_TYPES — no longer canonical, no longer
padded as missing, no longer auto-discovered. The frontend row
remains so a tenant with a separate DSB page can still submit one.
After this fix BMW should render:
- DSE: OK
- Impressum: LUECKENHAFT (unchanged — regex gaps to fix separately)
- Cookie-Richtlinie: OK
- Social Media: NICHT GEFUNDEN (bmw.de does not link to it)
- AGB: NICHT GEFUNDEN (correct — BMW has no public AGB)
- Nutzungsbedingungen: NICHT GEFUNDEN
- Widerruf: NICHT GEFUNDEN
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b2b4d77877 |
fix(auto-discovery): compute missing against canonical 8 types, not submitted
Frontend filters out empty doc rows -> req.documents only contains the
N submitted entries (3 in BMW case). The old auto-discovery loop
computed 'missing' as 'entries in doc_entries with empty text', which
was always empty for those N entries -> discovery never fired.
Fix:
- missing = _ALL_DOC_TYPES - {canonical doc_types in doc_entries}
- For each missing type, APPEND a new entry to doc_entries with
discovery_attempted=True. If a discovered doc matched, fill text/url
and set auto_discovered=True.
- Check loop: skip entries with no URL and no text (let padding label
them). Entries with URL but no text keep the 'Kein Text' error so the
user sees fetch failures explicitly.
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525038359a |
feat(compliance-check): auto-discover missing doc types from homepage
When the user leaves some doc-type rows empty, the tool now actively searches the website for them — only marks 'not found' as last resort. Flow: 1. User submits N URLs (e.g. just DSI) 2. For each canonical doc_type with no submitted URL/text, the route identifies the most-common base (scheme://netloc) from submitted URLs 3. Calls consent-tester /dsi-discovery on the homepage with max_documents=15 (180s timeout) 4. Classifies every discovered doc into a canonical doc_type via title/URL keyword rules (_DISCOVERY_RULES — covers cookie/widerruf/ social_media/agb/nutzungsbedingungen/dsb/impressum/dse) 5. Fills matching empty entries with the discovered text, marks auto_discovered=True and discovery_attempted=True Padding now differentiates: - 'Auf der Website nicht gefunden' — discovery was attempted, no doc matched. Amber badge, friendly hint to add URL manually. - 'Nicht eingereicht — Quelle nicht angegeben' — user gave NO URLs at all, nothing to crawl from. Grey badge. Email + frontend: - Status labels: NICHT GEFUNDEN (amber) vs NICHT EINGEREICHT (grey) - 'Gepruefte Quellen' table tags auto-discovered URLs with a small blue 'auto-entdeckt' badge so GF sees what tool found vs user submitted. Implementation only runs when ≥1 URL was submitted (no base to crawl from otherwise). Adds 30-90s for unsubmitted types but avoids the 'just say nicht gefunden' anti-pattern. |
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bc21480a2a |
fix(compliance-check): always render 8 doc types + 4 BMW GT-gap fixes
Always-show-8 (user-requested): - agent_compliance_check_routes.py: _pad_results_with_missing pads the results list to always include all 8 canonical doc_types in canonical order. Missing types get a placeholder DocCheckResult with error= 'Nicht eingereicht' + scenario='missing'. - agent_doc_check_report.py: NICHT EINGEREICHT status label (neutral), friendly grey body block instead of red error. - ChecklistView.tsx: 'Nicht eingereicht' chip (neutral grey, not red 'Fehler'); SCENARIO_LABELS adds missing entry + header chip counter. Impressum-Regression fix (#18): - _fetch_text(url, doc_type): cookie/dse/social_media -> max_documents=1 (CMP capture authoritative, sub-pages dilute). Other types -> =3 (Impressum needs Versicherungsvermittler, Aufsicht, Berufsrecht sub- pages). 15s networkidle bail keeps timing safe. ODR/Verbraucherstreitbeilegung filter (#19): - _apply_profile_filter: when profile.needs_odr=True (B2C), override the check's default B2B-oriented hint with action-oriented B2C guidance pointing at Art. 14 EU-VO 524/2013 + §36 VSBG. Previously the check contradicted itself: 'profile says B2C' + hint 'only relevant for B2C online vendors'. Registergericht regex (#20): - impressum_checks.py: accept colon/dot/dash between keyword and city (BMW writes 'registergericht: münchen hrb 42243'). Add 'sitz und registergericht: X' as separate pattern. Industry detection (#21): - business_profiler.py: 'automotive' keywords broadened (antriebs, motor, leasing, werkstatt, probefahrt, plus brand names BMW/Mercedes/ Audi/VW/Porsche/Opel). 'it_services' keywords narrowed — software/ cloud/hosting are mentioned in every privacy policy and were biasing the result toward IT for any tech-aware company. |
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9814b56f2f |
fix(cookie-extract): max_documents=1 + faster networkidle bail (Phase 0 fix)
Root cause of the recurring 603-word BMW result: - DSI discovery for cookie-policy URL was hitting 4x networkidle timeouts (60s each = ~240s total). - Backend httpx timeout (180s after the previous fix) gave up before the consent-tester finished, falling through to the raw HTTP fetch which returned BMWs SSR navigation chrome (603 words) as the 'cookie policy'. Two orthogonal fixes: 1. _fetch_text now passes max_documents=1 for user-specified URLs. We only want self-extraction of THAT page; link-following is unnecessary noise. 2. networkidle wait_until window dropped 60s -> 15s. SPAs like BMW/Daimler never reach networkidle anyway; the 60s wait was pure latency. Falls through to domcontentloaded+5s render-wait, same as before. |
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6689b37f95 |
fix(agent): bump _fetch_text timeout 60s->180s
The dsi-discovery in consent-tester does self-extraction + follows up to 3 sub-links + waits for CMP JSON payloads. On big SPAs (BMW, Daimler) this routinely exceeds 60s. When it timed out, the HTTP fallback returned the SSR shell as text — for the BMW cookie page that's 603 words of site navigation, which then registered as 'Cookie-Richtlinie nicht im eingereichten Text' (33%). With 180s the consent-tester finishes cleanly and we get the CMP-captured 1824 words of real policy. |
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e61e9d9e2a |
feat(agent): progress_pct + 6 BMW-Run Verbesserungen
Backend (agent_compliance_check_routes.py):
- progress_pct (0-100%) im Job-State, ueber alle Phasen verteilt
(Laden 0-30, Profil 35-40, Pruefen 40-80, Banner 80-92, Report 95-100)
- Status-Texte vereinheitlicht ("Texte laden X/N", "Pruefen X/N")
- Firmenname fuer Email-Subject jetzt aus URL abgeleitet
(bmw.de -> "BMW", mercedes-benz.de -> "Mercedes-Benz") statt
unzuverlaessigem extracted_profile.companyName (matchte oft juris.de)
- E-Mail-Report enthaelt jetzt Banner+TCF-Vendor-Liste (build_provider_list_html)
Backend (agent_doc_check_extras.py — neu):
- build_scanned_urls_html: gepruefte URLs als Tabelle oben im Report
(transparent fuer GF, welche Quellen wirklich gezogen wurden)
- Cross-Domain-Hinweis bei >1 netloc (BMW: bmw.de / bmwgroup.com /
bmwgroup.jobs — Auffindbarkeit nach Art. 12 DSGVO)
- build_provider_list_html: Banner-Box + TCF-Vendor-Tabelle mit Spalten
Name | Kategorie | Zweck | Drittland | Rechtsgrundlage
Backend (business_profiler.py):
- §34d-GewO Versicherungsvermittler-Hinweise zaehlen nicht mehr als
"finance"-Industrie (BMW wurde dadurch falsch als B2B/finance erkannt)
- Neue Industry "automotive" (Fahrzeug/KFZ/Konfigurator/Modellpalette)
- B2B-Keywords: generische Begriffe wie "unternehmen", "beratung",
"consulting" entfernt (matchten in jedem Konzerntext)
- B2C-Fallback: bei Verbraucher-Signalen ("widerruf", "kunde",
redaktioneller Inhalt) tendiert auf b2c statt b2b
Frontend (ComplianceCheckTab.tsx):
- Progress-Balken mit Width-% und XX%-Anzeige rechts
- liest data.progress_pct aus Polling-Response
Consent-Tester (dsi_discovery.py):
- Cookie-Policy-Extraktion kritisch fixt: wait_for_function bis
body.innerText > 500 chars (BMW SPA-Rendering brauchte mehr Zeit)
- _extract_text_robust: 3-Strategien-Extraktion (Selektoren -> Body-
Cleanup -> P/LI/TD-Tags)
- _extract_text_from_iframes: liest OneTrust/Sourcepoint/Usercentrics
Iframe-Inhalte (manche Cookie-Policies leben dort)
Adressiert alle Findings aus dem BMW-Ground-Truth-Vergleich.
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d45e08e25f | fix: reduce Playwright timeout 180s→60s, increase poll limit 15→25min | ||
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3dbf3aa34a |
feat: HTTP fallback for text extraction when Playwright times out
BMW Impressum/Cookie pages timeout in Playwright (>180s) because the SPA has many sub-links to follow. But the HTML source already contains the text (SSR). New fallback: direct HTTP GET + HTML tag stripping. Order: 1. Consent-tester (Playwright, 180s) → 2. HTTP GET (30s) Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |
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f34305c0a1 | fix: increase dsi-discovery timeout 90s→300s, reduce max_documents 10→5 | ||
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fca67c1f43 |
fix: accordion close bug + merge multi-page DSIs (BMW fix)
1. _expand_all_interactive(): Only click aria-expanded="false" buttons. Before: clicked ALL accordion buttons including open ones → BMW's pre-expanded accordions got CLOSED, reducing text from 1151 to 361w. 2. _fetch_text() + /extract-text: merge ALL documents found on a page (max_documents=10 instead of 1). BMW splits DSI across 5 sub-pages that the discovery finds as separate documents — now merged. 3. Tab panels: unhide hidden tabpanels instead of clicking tabs (clicking tabs can hide the currently visible panel). Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |
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9f87bc5a2c | fix: include website/company name in compliance-check email subject | ||
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d72aa10691 |
feat: management summary for GF + batch GT test script
1. Management Summary (agent_doc_check_report.py):
- Plain-language action items for Geschaeftsfuehrer
- Maps technical checks to business actions ("Ihren DSB erwaehnen",
"Beschwerderecht ergaenzen", "Loeschfristen dokumentieren")
- Shows at top of compliance check email before detail report
- Max 10 actions, max 3 per document
2. Batch GT Test (zeroclaw/scripts/batch_gt_test.py):
- Runs all 10 GT websites through compliance-check API
- Prints comparison table with L1 scores, word counts, services
- Saves raw JSON results for analysis
- Usage: python3 batch_gt_test.py --sites 1,6 --backend-url URL
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
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826ce2a1b8 |
fix(cross-doc): suppress false positives when regex checks already pass
Cross-search "not in text" findings are only shown when regex L1 completeness < 50%. This prevents false positives where the text IS the right doc_type but doesn't contain the specific cross-search keywords (e.g. Impressum passes 9/13 checks but lacks "§5 TMG"). Also: cross-search now checks entries with wrong text, not just empty. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |
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bd2d6976d6 |
fix(cross-doc): also check entries with wrong text, not just empty ones
Cross-search now validates if existing text matches the expected doc_type using keyword scoring. If text is present but doesn't match (e.g. Nutzungsbedingungen in Widerruf row), searches other texts and creates a finding explaining the mismatch. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |
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4e9043f26d |
feat(cross-doc): search all texts for all doc_types + misplacement finding
Cross-Document Intelligence: When a doc_type row is empty, searches ALL other loaded documents for that content. If found (e.g. Widerruf in AGB), extracts the section, runs the check, AND creates a finding: "Widerrufsbelehrung in falschem Dokument gefunden — schwer auffindbar" Keywords for: widerruf, cookie, social_media, impressum, agb, dsb. Integrated as Step 1c in compliance check pipeline. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |
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33bf2b7c5a |
feat(service-detector): detect 118 services in legal texts (was 20)
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New service_detector.py uses service_registry (88 entries) plus 30+ extra text patterns to detect services mentioned in DSI/legal texts. Results on Spiegel: 31/32 services detected (97%, was 5/32 = 16%). Includes metadata: name, category, country, EU adequacy status. - Profiler now uses detect_services_in_text() instead of 20-entry list - Profile extractor adds detected_services with full metadata - Auto-generates scope hint for non-EU services (Drittlandtransfer) 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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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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0b9150f16f |
feat(vendor-assessment): Pruefprotokoll + Frontend + Sidebar
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Phase 4-5: Professional Pruefprotokoll report builder with styled HTML output (Kopfdaten, Kategorie-Scores, L1/L2 Check-Hierarchie, Findings, Freigabe-Block). Frontend at /sdk/vendor-assessment with 3-step flow: DocumentUploader → AssessmentProgress → PruefprotokollView. Sidebar: "Use-Case Audits" → "Vertragspruefung" renamed. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |
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0326d5baab |
feat(vendor-assessment): AVV/SCC/TOM/Sub-Processor checklists + assessment service
Phase 1-3 of the Vendor Contract Assessment:
Backend checklists (Doc-Check L1/L2 engine compatible):
- avv_checks.py: 28 checks (11 L1 + 17 L2) for Art. 28(3) DSGVO
- scc_checks.py: 7 checks for EU SCC 2021 (modules, annexes, TIA)
- tom_annex_checks.py: 12 checks for Art. 32 (8 control objectives)
- sub_processor_checks.py: 7 checks for sub-processor list completeness
Assessment service:
- POST /vendor-compliance/assessments — async contract analysis
- GET /vendor-compliance/assessments/{id} — poll status
- Cross-check engine: detects missing SCC when AVV mentions third-country,
missing TOM annex, missing sub-processor list
All checklists registered in runner.py CHECKLIST_MAP (27 doc_types total).
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
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c867478791 |
feat(tcf-vendors): GVL cache + vendor extraction + VVT mapping
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Phase 1-2 of the closed quality loop: - GVL cache (consent-tester/services/gvl_cache.py): downloads and caches IAB Global Vendor List with 24h TTL, resolves vendor IDs to names, purposes, policy URLs, retention, country - Vendor extraction (consent_interceptor.py): extract_tcf_vendors() reads __tcfapi after accept phase, resolves via GVL - Scan response: tcf_vendors field added to /scan endpoint - VVT mapper (vendor_vvt_mapper.py): maps TCF vendors to VVT format with purpose labels, Rechtsgrundlage, Drittland detection - Vendor cross-check (banner_cookie_cross_check.py): checks all TCF vendors against DSI text — missing vendors, undocumented transfers - Compliance check integrates Step 3d: TCF vendors vs DSI Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |
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7be34552bb |
feat(compliance-check): profile extraction + scenario classification
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- New profile_extractor.py: extracts Company Profile fields (name, legal form, address, DPO, USt-IdNr) and Compliance Scope hints (Art. 9 data, third country, profiling) from document texts - Scenario per document: regenerate (<30%), fix (30-95%), import (>95%) - Widerruf for B2B: no longer skipped, instead all checks flagged as INFO with "not needed for B2B" hint - Move _build_profile_html to report builder module - DocCheckResult gets scenario field Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |
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be9cfdc2d4 |
feat(compliance-check): skip Widerruf for B2B, limit MCs, fix industry
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- Skip Widerrufsbelehrung check entirely for B2B/B2G businesses - Limit MC checks to top 20 per doc_type (by severity) to reduce noise (e.g. 75 impressum MCs → 20, avoiding 55 irrelevant FAILs) - Add consulting/manufacturing industry keywords (arbeitssicherheit, brandschutz, werkzeugbau, etc.) - Lower industry detection threshold from 2 to 1 keyword hit Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |
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b42e1cd091 |
feat(cmp): timezone→geo_country mapping + timezone parameter
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Add _resolve_geo_from_timezone() with 35-country IANA timezone map. Accept timezone field in ConsentCreate schema and pass through to service. Populate geo_country automatically from browser timezone. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |
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4a7e09bbb0 |
fix(impressum): regex [A-Z] never matches on lowercased text
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All patterns matched against text_lower but used [A-Z] character class. Changed to [a-zA-Z] so patterns like "geschäftsführung: dr. oliver" are found. Also added "Pflicht"/"Detail" labels to the two progress bars to clarify what 100% vs 8% means. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |
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edbf6d2be5 |
feat(dsms): Stufe 2+3 — Evidence/TechFile → DSMS + Version Chains + Audit Timeline
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Stufe 2A: Evidence Upload → automatische DSMS-Archivierung
- Nach SHA-256 Hash → archive_to_dsms(), CID im Audit-Trail
- Evidence mit CID wird automatisch zu E2 (hash-verifiziert) hochgestuft
Stufe 2B: IACE Tech-File Export → DSMS
- PDF/Excel/DOCX/Markdown Exporte werden nach DSMS archiviert
- archiveTechFile() Helper fuer alle 4 Formate
Stufe 3A: DSMS Gateway — parent_cid + History Endpoint
- parent_cid + tenant_id Felder in DocumentMetadata
- GET /documents/{cid}/history — folgt parent_cid-Chain (max 50 deep)
Stufe 3C: Audit Timeline UI
- Neue Seite /sdk/audit-timeline
- Vertikale Timeline mit farbigen Action-Dots
- Filter: Alle, Nachweis, DSMS-Archiv, Control, Dokument, DSFA, VVT, TOM
- CID-Badges fuer DSMS-archivierte Eintraege
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
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74f00bbb0f |
feat(compliance-check): split shared URLs into sections per doc_type
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When the same URL is used for multiple document types (e.g. /datenschutz for DSI + Cookie + DSB), the section splitter now: - Detects duplicate URLs and fetches text only once - Splits text at classified headings (Cookie, Google Analytics, etc.) - Assigns matching sections to each doc_type - DSI always keeps the full text Extracted to section_splitter.py (170 LOC) to keep routes under 500. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |
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407a9503e4 |
fix(profiler): fix B2G false positive + add consulting/manufacturing
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- Remove generic B2G keywords (behörde, amt, öffentlich) that match in every DSI due to "Aufsichtsbehörde", "Amtsgericht", "veröffentlichen" - Remove "server" from it_services (too generic, appears in every DSI) - Add consulting, manufacturing, media industries - Add B2B fallback for GmbH/AG without B2C signals - Add 10 ground truth files for unified compliance check 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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b6ad958b69 |
feat(compliance-check): integrate banner cross-check + extract to module
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Add automatic banner check (Step 3b) and banner-vs-cookie cross-check (Step 3c) to unified compliance check. Extract cross-check logic to banner_cookie_cross_check.py to keep routes under 500 LOC. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |
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66d30568e2 |
feat(dsms): Stufe 1 — Gap-Analyse Report wird in DSMS archiviert
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- Go DSMS Client (internal/dsms/client.go): Archive() + Verify() - Python DSMS Client (compliance/services/dsms_client.py): archive_to_dsms() + verify_dsms() - Gap-Analyse AnalyzeProject() archiviert Report-JSON nach DSMS - Response enthält dsms_cid wenn Archivierung erfolgreich - Frontend: Grünes "Revisionssicher archiviert" Badge mit CID im GapDashboard - DSMS Proxy Route (/api/sdk/v1/dsms/[...path]) für Verify-Abfragen Stufe 2 (Evidence Upload → DSMS) und Stufe 3 (Version Chains) folgen. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |
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397de741c1 |
feat(cmp): Phase 2 — script blocking + cookie tracking
Migration 108: scripts_blocked, scripts_released, cookies_set JSONB columns. Backend models/schema/service/serializer/routes extended. Admin detail modal shows released scripts and set cookies with categories. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |
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051890c370 |
feat(cmp): restore vendor-agnostic fields + module wiring
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Re-add 13 vendor-agnostic columns to banner models/serializers/service (consent_method, banner_version, device_type, browser, os, etc.) that were lost when another session overwrote the code. Keep vendor_consents dict from the other session. Add list_consents method back to BannerConsentService. Wire CookieBanner, Loeschfristen and UseCases into Document Generator contextBridge (CMP_NAME, analytics tools, retention months, feature flags). 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> |
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0c25832b5c |
fix: Context-aware Impressum checks + 3 regex fixes
3 Regex fixes: - Telefon: matches '0761 / 48 98 09 01' format (spaces around /) - Registergericht: matches 'AG Freiburg' (not just 'Amtsgericht') - Vertretung: matches 'Geschaeftsfuehrung:' (not just 'Geschaeftsfuehrer:') 6 checks changed from FAIL to INFO severity: - V.i.S.d.P.: only relevant if website has editorial content - Streitbeilegung: only relevant for B2C online shops - Berufsrecht: only relevant for regulated professions - Stammkapital: legally required but rarely enforced - Aufsichtsbehoerde: only for licensed activities - Berufshaftpflicht: only for mandatory insurance INFO checks don't count towards completeness percentage. They appear as hints, not findings. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |
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02ff96f74e |
fix: resolve all merge conflict markers from feat/zeroclaw-compliance-agent
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9 files had conflict markers from the branch merge. All resolved keeping the feature branch version. Also split agent_scan_routes.py (534→367 LOC) by extracting Pydantic models to agent_scan_models.py. [guardrail-change] Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |
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36c6101b91 |
Merge feat/zeroclaw-compliance-agent into main
Brings all compliance doc-check features: - 162 regex checks + 1874 Master Controls - LLM-agnostic agent with tool calling - Banner check (46 checks, 30 CMPs, stealth, Shadow DOM) - Impressum check (24 checks) - Deep consent verification (DataLayer, GCM, TCF) - CMP E2E tests (39 tests) - HTML email reports, FAQ, persistent history Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |
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91d6d8b1a7 |
feat: KI-Agent toggle button in Dokumenten-Pruefung
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Green pill button: 'KI-Agent aus' / 'KI-Agent aktiv (1.874 MCs)' Toggles use_agent flag which is passed through the full chain: Frontend → DocCheckRequest → _run_doc_check → _check_single_document → check_document_with_controls(use_agent=True) → ComplianceAgent with tool calling Default: OFF (deterministic regex). User can enable per scan. Also works via env var COMPLIANCE_USE_AGENT=true for always-on. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |
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289ec5f396 |
feat(cmp): vendor-agnostic consent data model — 13 new fields
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Extend banner consent records with consent_method, banner_version, banner_config_hash, geo, page_url, referrer, device info, session_id and consent_scope for full Art. 7 DSGVO proof with any tracking vendor. Migration 107, backward-compatible (all fields nullable). Admin detail modal shows tracking context, device info and technical data. Fix pre-existing str|None → Optional[str] for Python 3.9 compat. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |
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58f370f4ff |
feat: LLM-agnostic Compliance Agent with tool calling
New agent architecture for intelligent MC evaluation: agent_tools.py (367 LOC): - 5 tools in OpenAI function-calling format - query_controls: async DB query for MCs by doc_type - evaluate_controls_batch: deterministic keyword matching - search_document: text search with context - get_document_stats: word count, sections, language - submit_results: finalize check results compliance_agent.py (398 LOC): - ComplianceAgent class with agent loop - 3 LLM providers: Ollama, OpenAI-compatible (OVH), Anthropic - Tool call dispatch + result collection - System prompt for systematic compliance analysis - run_compliance_check() convenience function Hybrid mode: - COMPLIANCE_USE_AGENT=false (default): deterministic regex - COMPLIANCE_USE_AGENT=true: LLM agent with tool calling - Agent fallback to regex if LLM unavailable Works with Qwen 35B (Ollama), Qwen 120B (OVH vLLM), Claude. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |
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bdbc30e47b |
feat(cmp): unified consent view — Website-Besucher + Login-Nutzer tabs
Merges two separate consent views into one unified page at /sdk/einwilligungen: - Tab "Website-Besucher": device-based banner consents with site selector - Tab "Login-Nutzer": user-based DSGVO consents (existing, unchanged) Backend: - New endpoint GET /admin/consents for paginated banner consent records - Fix: categories JSON string parsing (was iterating chars instead of array) CMP Dashboard: - Dynamic site selector replacing hardcoded "preview-test-site" Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |
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9cbbc6ee2f |
feat: LLM interpretation layer for failed MC checks
Deterministic pass/fail stays unchanged. After keyword checking, ONE batched LLM call enriches the top 10 severity FAILs with context-specific recommendations based on the actual document. Example: If document uses Google Analytics but lacks transfer mechanism → LLM generates: "Sie nutzen Google Analytics (USA). Ergaenzen Sie einen Verweis auf das EU-US Data Privacy Framework und pruefen Sie die DPF-Zertifizierung unter dataprivacyframework.gov." - Pass/fail: deterministic (keyword matching, reproducible) - Hint enrichment: LLM (contextual, one call for all fails) - Temperature 0.3 for consistency - Graceful fallback if Ollama unavailable Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |
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5ea83e9b33 |
feat: Deterministic MC checking — ALL controls, no LLM, reproducible
Replaced LLM-based MC verification with deterministic keyword matching: - Extracts keywords from pass_criteria/fail_criteria - Matches against document text via regex (case-insensitive) - PASS if >= 60% of criteria keywords found AND no fail_criteria triggered - Same text + same MCs = same result every time Checks ALL MCs for the doc_type (max_controls=0): - DSE: all 571 controls checked in <1 second - Impressum: all 75 controls - Cookie: all 381 controls No LLM calls needed — purely deterministic keyword matching. Bigram extraction for compound terms (e.g. "standardvertragsklauseln"). Stop word filtering for German legal text. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |
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26b222d53d |
feat: Integrate 1.874 Master Controls into document checking
Rewritten rag_document_checker.py to use doc_check_controls table instead of generic canonical_controls. Each MC has: - check_question: binary YES/NO for LLM - pass_criteria: JSONB list of concrete requirements - fail_criteria: JSONB list of common mistakes Flow: Regex checks (fast) → LLM verify FAILs → MC deep check (15 per doc) MC results appear as additional L2 checks in the report. Coverage: 571 DSE, 381 Cookie, 309 Loeschkonzept, 153 Widerruf, 147 DSFA, 125 AVV, 113 AGB, 75 Impressum = 1.874 total. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |
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a14e5ad97d |
fix: Non-DSE doc checks prefer self-extracted text from actual URL
When checking impressum/agb/widerruf, the DSI discovery would follow links away from the page and return the wrong document (e.g. /impressum → finds link to /datenschutz → returns datenschutz text). Now: for non-DSE doc_types, prefer the html_full_page document (self-extracted from the actual URL the user provided) over linked pages found by the crawler. Fixes safetykon.de/impressum returning datenschutz text. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |
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82951785ec |
feat: Impressum checks expanded from 16 to 24 (GAP analysis)
8 new checks: Reglementierte Berufe, Grundkapital, Aufsichtsbehoerde, Berufshaftpflicht, rechtswidrige Disclaimer, Kammer, Berufsbezeichnung, berufsrechtliche Regelungen. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |
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1b8e9881bb |
feat: Banner-Check — Historie, persistentes Ergebnis, E-Mail-Report
1. localStorage Persistenz: URL, letztes Ergebnis, Historie (30 Eintraege) 2. Historie: Zeigt URL, Datum, Provider, Violations, Prozent 3. Letztes Ergebnis bleibt nach Tab-Wechsel/Reload sichtbar 4. E-Mail-Report: HTML-formatiert mit Violations + Hints an mailpit 5. Email-Status Anzeige im Frontend Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |