Commit Graph

351 Commits

Author SHA1 Message Date
Benjamin Admin 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>
2026-05-17 14:06:28 +02:00
Benjamin Admin 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.
2026-05-17 13:45:58 +02:00
Benjamin Admin 6d29191e9b fix(vvt): score INTERNAL/GROUP without opt-out/privacy penalty
User feedback after BMW test:
- 60 'BMW AG — XYZ' rows were rendered as ✗ for Opt-Out/Privacy and
  scored 38-52%. That's misleading: BMW processing for itself doesn't
  need a separate opt-out URL (cookie-banner is the consent
  mechanism) or a separate privacy policy (main DSI covers it).
- Title 'Anbieter' was wrong for 60 of 90 rows (internal services).

Three orthogonal fixes:

1. score_vendors becomes recipient_type aware:
   - INTERNAL/GROUP_COMPANY: opt_out_url, privacy_policy_url, country
     are NOT required (the user's main DSI + cookie-banner cover them).
     What IS required: name, purpose, cookies disclosed with name +
     expiry. Cookies-disclosure weight raised to 50 (was 15) so the
     VVT-relevant data is the score driver.
   - 'necessary' category: opt-out still skipped (§25 Abs. 2 TDDDG).
   - External (PROCESSOR/CONTROLLER): existing strict scoring stays.

2. _link_status_badge accepts na_label and renders a neutral em-dash
   with explanation tooltip instead of red ✗ when the column doesn't
   apply to that row. _render_vendor_row_full passes na_label based on
   recipient_type:
     - INTERNAL/GROUP -> 'Nicht erforderlich (eigene Verarbeitung)'
     - necessary       -> 'Nicht erforderlich (§25 Abs. 2 TDDDG)'

3. Header + summary clarify the split:
   - h3 changed to 'Verarbeitungstaetigkeiten und Empfaenger aus der
     Cookie-Richtlinie' (was 'Drittanbieter aus Cookie-Richtlinie').
   - Top line: '90 Verarbeitungen erfasst — 60 eigene + 30 externe
     Empfaenger'.
   - Disclaimer below: explains the INTERNAL/GROUP exemption so the
     reader understands why those rows don't show ✗ for missing URLs.
   - Section labels enriched with the relevant DSGVO article:
     'Eigene Verarbeitungstaetigkeiten — fuer das VVT (Art. 30)',
     'Auftragsverarbeiter — AVV erforderlich (Art. 28)',
     'Joint Controller — Vereinbarung pruefen (Art. 26)'.

Expected BMW result after fix: ~85% of the 60 BMW-AG rows jump from
~52% to 90-100% (the real issue, fehlende Cookies-Disclosure, stays
flagged). The only true findings remaining are external links that
return 4xx (e.g. Criteo 403, Teads 404).
2026-05-17 13:15:40 +02:00
Benjamin Admin 8a44e67293 feat(compliance-check): unlock all 1874 MCs + close gap-table items
User: 'wir haben 1800 MCs erstellt um sie zu 10% zu nutzen — das ist
Schwachsinn'. Fixed all 6 gaps from the audit.

#1 max_controls=0 (was 20):
- agent_compliance_check_routes _check_single: passes max_controls=0 to
  check_document_with_controls -> ALL MCs evaluated per doc_type.
- 8 doc_types now use 1874 MCs instead of 160 (10x coverage).
- Regex matching is cheap (<1s per doc); LLM-enrich cap of 10 stays.

#2 LLM-verify fixed:
- llm_verify.py was getting 0/N parsed. Causes: qwen3 thinking-mode
  wrapped output in <think>...</think>, /api/generate doesn't enforce
  JSON, prompt didn't handle code-fence wrappers.
- Now uses /api/chat with format='json' (forces valid JSON).
- _parse_batch_response strips <think> tags, accepts {results:[...]}
  AND bare [...], adds richer regex-fallback parse, logs raw head on
  total parse failure for diagnosis.

#3 Loeschkonzept checklist (new):
- doc_checks/loeschkonzept_checks.py — 9 L1 + 7 L2 checks per DIN 66398
  + Art. 5(1)(e)/17/32 DSGVO: scope+responsibility, data categories,
  retention periods, legal basis refs (HGB/AO/BGB), deletion trigger,
  deletion process+technical+systems, deletion proof, exceptions +
  Art. 18 lock, review cycle, DSGVO references.
- runner.py registered for loeschkonzept/loeschung/loeschfristen.

#4 regulation backfill script:
- backend-compliance/scripts/backfill_mc_regulation.py — regex-detects
  DSGVO/TDDDG/TMG/BGB/HGB/AO/MStV/UWG/VSBG/PAngV/GwG/BDSG/EU-VO
  references in MC title+question+pass_criteria, UPDATEs regulation +
  article fields.
- Idempotent (only NULL rows), --dry-run flag, batched 200/UPDATE.
- Run inside container: docker exec bp-compliance-backend python3 \
    /app/scripts/backfill_mc_regulation.py

#5 MC alias-fallback:
- rag_document_checker._MC_ALIAS_FALLBACK maps doc_types without own
  MCs to a related set: nutzungsbedingungen->agb, social_media->dse,
  sub_processor/scc/tom_annex->avv, loeschfristen->loeschkonzept,
  eu_institution/dsb->dse.
- _load_controls retries with the alias when the primary query
  returns 0 rows.
- 14 additional doc_types now get MC coverage transparently.

#6 cross-domain auto-discovery:
- _autodiscover_missing builds a crawl plan: primary submitted base
  + up to 2 related domains sharing the owner SLD (e.g. BMW Group:
  bmw.de + bmwgroup.com + bmwgroup.jobs).
- Detection: regex over submitted texts for https?://...<owner>...
  hostnames distinct from the primary base.
- Each crawled base contributes documents + cmp_payloads to the
  discovery pool.

Net effect for BMW: 1874 MCs evaluated (90 from cookie alone, was
20), Loeschkonzept Pflichtangaben benoten-bar, LLM overturns false
regex FAILs, Joint-Controller policies on bmwgroup.jobs (Social
Media) jetzt entdeckbar. Same wins will apply to CRA-Compliance check.
2026-05-17 13:07:50 +02:00
Benjamin Admin fab1e35847 feat(vvt): recipient-type classification + 3-section VVT table
Per user request: BMW (and others) put their own services AND external
vendors in the same cookie-policy widget. The VVT-Tabelle now groups
them by Art. 30(1)(d) DSGVO recipient category so the DSB can act on
the right buckets:

  - INTERNAL      — owner processing for itself ('BMW AG — XYZ')
  - GROUP_COMPANY — same brand family, different legal entity ('BMW Bank')
  - PROCESSOR     — Auftragsverarbeiter, AVV-pflichtig (Adobe, Akamai)
  - CONTROLLER    — independent / joint controller (Meta Pixel, Google
                    Ads, LinkedIn — they run their own profiles)
  - AUTHORITY     — government bodies (rare in cookies)
  - OTHER         — fallback

New module vendor_classifier.py:
- owner_from_url(url) — derive site-owner token (bmw.de -> 'BMW',
  mercedes-benz.de -> 'Mercedes-Benz')
- classify(name, category, owner) — strict 5-tier heuristic:
  * INTERNAL: vendor name first-token is '<Owner>' / '<Owner> AG' /
    '<Owner> SE' / '<Owner> GmbH' / '<Owner> AG & Co. KG'
  * GROUP_COMPANY: starts with '<Owner> ' but isn't '<Owner> AG'
  * CONTROLLER: matches a known joint-controller list (Meta, Google
    Ads, YouTube, LinkedIn Insight, TikTok, Pinterest, Taboola,
    Outbrain, Criteo, Twitter, Reddit, ...)
  * PROCESSOR: legal-form suffix in name (GmbH, AG, Inc., A/S,
    B.V., S.A., Ltd., LLC, ...)
  * OTHER: anything else

vendor_extractor.extract_vendors_from_payloads now takes owner_name:
- Passes it through to classify() for every extracted vendor record
- The route derives owner_name via _company_name_from_url(doc_entries)
- LLM-extracted vendors are classified the same way (so V3 fallback
  also produces tagged records)

agent_doc_check_extras.build_vvt_table_html rewritten:
- Buckets vendors by recipient_type
- Renders one section per non-empty bucket, in canonical order
  (RECIPIENT_TYPE_SECTIONS), each with section header + count + bad
  count + nested table
- Within each section: sorted by compliance_score ascending
- Response JSON cmp_vendors includes recipient_type so the frontend
  can later import per-category into the VVT module

Expected BMW result: ~60 INTERNAL rows (BMW AG own services),
~25 PROCESSOR rows (Adobe, Adform, Akamai, AWS, ...), ~5 CONTROLLER
rows (Meta Pixel, Google, LinkedIn, Pinterest, Outbrain, Taboola).
2026-05-17 12:31:49 +02:00
Benjamin Admin 6c7d4c7552 fix(vvt): correct ePaaS schema mapping + category-aware scoring
The first BMW VVT table rendered all 24 providers at 20% score because
the ePaaS extractor was reading the wrong field names. Actual schema is
nested: providers[].processings[].persistences[], NOT providers[] alone.

Correct ePaaS schema (verified against bmw.com/epaas/.../de_DE.epaas.json):
  Provider:    {id, name, description, processings[]}
  Processing:  {id, name, description, categoryId, optOutLink,
                privacyPolicyLink, persistences[]}
  Persistence: {id, name, domain, type, expiry, description}

Two structural changes:

1. One row per processing (not provider). BMW has 26 providers but ~91
   processings spread across them (Adobe alone has ACMProcessing,
   AdobeAnalytics, AdobeCampaign, AdobeTargetAnalytics, AdobeTargetPers.).
   The cookie widget displays each processing separately — VVT now
   mirrors that. Display name format: 'Provider Name — Processing Name'.

2. Read optOutLink/privacyPolicyLink from PROCESSING (where they live),
   not provider. Persistences flatten to cookies[] with name + expiry +
   description.

Plus category mapping:
  advertising -> marketing
  strictlyNecessary -> necessary
  statistics -> statistics
  functional -> functional

Category-aware scoring (cookie_link_validator.score_vendors):
- 'necessary' (technisch erforderliche, §25 Abs. 2 TDDDG): no opt-out
  required, no country required. Score weight shifts to purpose +
  cookie disclosure (essential cookies must list names + expiry).
- All other categories: opt-out URL still mandatory; missing opt-out
  flags 'no_opt_out_url' and zeros that block of points.

Expected BMW result after this fix:
- ~91 rows (Adobe Analytics, Adform Retargeting, Akamai Infrastructure,
  AWS, ..., plus ~60 strictlyNecessary processings)
- Marketing rows with present opt-out → ~75-90%
- Necessary rows with cookie+expiry → ~85-95%
- Rows missing fields → still flagged
2026-05-17 11:19:31 +02:00
Benjamin Admin 873997c13b feat(vvt): V3 — LLM vendor extraction fallback for unknown CMPs
When the cookie text has no captured CMP payload (long-tail sites that
don't use ePaaS/OneTrust/Cookiebot/etc.) we now fall back to a Qwen → OVH
LLM cascade to extract a structured vendor list from the policy text.

New module backend/compliance/services/vendor_llm_extractor.py:
- extract_vendors_via_llm(cookie_text): runs Qwen first (local Ollama),
  then OVH if Qwen returns nothing usable.
- System prompt instructs the model to return STRICT JSON only:
  {vendors: [{name, country, purpose, category, opt_out_url,
   privacy_policy_url, persistence, cookies: [...]}]}
- Lenient JSON parser tolerates code-fences, prose wrappers, dict vs list.
- _normalize() caps array sizes (80 vendors, 30 cookies each), validates
  URLs (must be http(s)), trims fields to reasonable lengths.

Route integration (agent_compliance_check_routes.py):
- After named-CMP extract: if cmp_vendors is empty AND the cookie text
  has ≥500 words (otherwise it's likely navigation chrome), invoke the
  LLM extractor. Progress message 'Vendor-Liste per LLM extrahieren...'.
- Vendors then run through the same validate_vendor_urls + score_vendors
  pipeline → VVT table rendered identically regardless of source.

docker-compose.yml: backend-compliance gains OLLAMA_URL, CMP_LLM_MODEL,
OVH_LLM_URL/KEY/MODEL env vars (same names as consent-tester so the
configuration is unified).

This closes the 'every site eventually gets a VVT table' goal:
- Known CMP → V1/V2 structured extraction (fast, exact)
- Unknown CMP → V3 LLM extraction (slow, best-effort)
- No text at all → no vendors, but other compliance checks still run.
2026-05-17 09:55:42 +02:00
Benjamin Admin 9c0cc0f59f feat(vvt): V2 — vendor extractors for Cookiebot/Usercentrics/Didomi/TrustArc
Backend vendor_extractor.py gets 4 new per-CMP dispatchers, mirroring the
JSON schemas observed in each platform:

- Cookiebot: 'Categories[*].Cookies[*]' with Vendor/Host, expiry, purpose
- Usercentrics: 'services[*]' with cookieMaxAgeSeconds, processingCompanyCountry
- Didomi: 'app.vendors[*]' with country + policyUrl
- TrustArc: 'vendors[*]' + per-category 'Cookies' with provider

All 6 named CMPs (ePaaS, OneTrust, Cookiebot, Usercentrics, Didomi,
TrustArc) plus the generic-shape fallback are now mapped — every site
hitting Phase B of the cascade gets a structured vendor list, scored
opt-out links, and a VVT-Tabelle in the email.
2026-05-17 09:52:10 +02:00
Benjamin Admin 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.
2026-05-17 09:50:11 +02:00
Benjamin Admin 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.
2026-05-17 09:38:32 +02:00
Benjamin Admin 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
2026-05-17 01:53:09 +02:00
Benjamin Admin 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.
2026-05-17 01:28:51 +02:00
Benjamin Admin 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.
2026-05-17 01:14:05 +02:00
Benjamin Admin 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.
2026-05-17 01:03:58 +02:00
Benjamin Admin 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.
2026-05-16 22:53:23 +02:00
Benjamin Admin 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.
2026-05-16 22:00:42 +02:00
Benjamin Admin 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.
2026-05-16 17:53:14 +02:00
Benjamin Admin d45e08e25f fix: reduce Playwright timeout 180s→60s, increase poll limit 15→25min 2026-05-16 00:47:28 +02:00
Benjamin Admin 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>
2026-05-15 23:16:10 +02:00
Benjamin Admin f34305c0a1 fix: increase dsi-discovery timeout 90s→300s, reduce max_documents 10→5 2026-05-15 14:21:13 +02:00
Benjamin Admin 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>
2026-05-15 13:32:04 +02:00
Benjamin Admin 9f87bc5a2c fix: include website/company name in compliance-check email subject 2026-05-15 10:15:34 +02:00
Benjamin Admin 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>
2026-05-15 09:39:19 +02:00
Benjamin Admin 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>
2026-05-15 00:54:33 +02:00
Benjamin Admin 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>
2026-05-15 00:19:40 +02:00
Benjamin Admin 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>
2026-05-14 23:19:39 +02:00
Benjamin Admin 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>
2026-05-13 16:00:15 +02:00
Benjamin Admin 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>
2026-05-13 15:22:38 +02:00
Benjamin Admin 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>
2026-05-13 01:20:55 +02:00
Benjamin Admin 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>
2026-05-12 23:24:12 +02:00
Benjamin Admin 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>
2026-05-12 23:14:54 +02:00
Benjamin Admin 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>
2026-05-12 18:18:50 +02:00
Benjamin Admin 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>
2026-05-12 17:34:33 +02:00
Benjamin Admin 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>
2026-05-12 17:03:57 +02:00
Benjamin Admin 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>
2026-05-12 14:43:13 +02:00
Benjamin Admin 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>
2026-05-12 14:02:25 +02:00
Benjamin Admin 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>
2026-05-12 13:55:07 +02:00
Benjamin Admin 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>
2026-05-12 12:49:57 +02:00
Benjamin Admin 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>
2026-05-12 12:20:44 +02:00
Benjamin Admin 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>
2026-05-12 11:49:30 +02:00
Benjamin Admin 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>
2026-05-12 00:08:47 +02:00
Benjamin Admin 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>
2026-05-11 23:39:26 +02:00
Benjamin Admin 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>
2026-05-11 22:52:26 +02:00
Benjamin Admin 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>
2026-05-11 21:57:54 +02:00
Benjamin Admin 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>
2026-05-11 20:56:10 +02:00
Benjamin Admin 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>
2026-05-11 15:23:19 +02:00
Benjamin Admin 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>
2026-05-11 12:15:07 +02:00
Benjamin Admin 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>
2026-05-11 11:44:20 +02:00
Benjamin Admin 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>
2026-05-10 23:26:21 +02:00
Benjamin Admin 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>
2026-05-10 23:12:20 +02:00