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>
The "Maßnahmen" page in the Bremsscheibe project showed a flat list with
heavy redundancy — e.g. "Sicherheitszeichen nach ISO 7010" appeared on 21
separate rows, one per linked hazard. Same for "Gefahrenpiktogramme",
"Flucht- und Rettungswege" etc. The signal got lost in the noise.
This is a presentation-only regrouping. Each Hazard×Mitigation pair stays
a separate DB row with its own status, notes and edit history (option B
from the discussion: instances remain independently editable). The page
now collapses rows that share the same `m.title` into one group row.
Group row shows:
- title + ISO 12100 sub-category (if encoded in description)
- count of linked hazards on the right
- compact status distribution "P · I · V" (Planned/Implemented/Verified)
- shared checkbox that selects all instances in the group
Click expands the group and reveals the individual hazard×measure rows,
each with its own StatusBadge and detail-expand for MitigationHints.
State additions:
- expandedGroup: Set<string> with keys `${type}:${title}` so the same
title across different reduction stages stays independently togglable
- groupByTitle() helper trims the title, falls back to "(ohne Titel)"
- statusCounts() helper for the P·I·V breakdown
Pagination semantics swapped from 50 instances/page to 50 groups/page —
makes the list far easier to scan at the ~80-instance scale this project
exhibits.
LOC: 267 → 346 (well under the 500 hard cap).
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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.
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).
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.
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).
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
Two bugs observed in BMW BMW test run:
1. Generic JSON heuristic captured /de-de/login/bmw/api/flyout/data (4KB,
user login fly-out data) and reconstruct_generic produced 56 words of
noise. The CMP-prefer logic then 'replaced' the 185-word imprint DOM
extraction with those 56 words because self_wc(185) < 300 — even
though cmp_wc(56) < self_wc(185).
2. The strict prefilter list was too short. Login/auth/cart endpoints
often have category-shaped JSON without being cookie policies.
Fixes:
- dsi_discovery: replace DOM with CMP only when cmp_wc > self_wc AND
meets one of the existing conditions. Tiny captures can no longer
silently destroy a bigger DOM extraction.
- cmp_extractor: skip non-cookie URLs (/login, /auth, /user, /session,
/cart, /checkout, /search, /flyout, /menu, /nav, /translation, /i18n,
/locale, /feature-flag).
- cmp_extractor: require ≥5KB payload size — real CMP policies are
always larger (BMW ePaaS is ~393KB). Tiny matches drop out before
reconstruction.
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.
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.
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.
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.
[guardrail-change]
Phase 18 adds an EU Cyber Resilience Act compliance track to IACE:
the engine now fires patterns that surface the manufacturer-side CRA
obligations whenever a project's components carry digital elements.
Patterns (HP1910-HP1918, hazard_patterns_cra.go):
HP1910 Missing SBOM
HP1911 Unsigned firmware/software updates
HP1912 Factory-default credentials still active
HP1913 No coordinated vulnerability disclosure (CVD) policy
HP1914 No documented security patch SLA
HP1915 Missing user-facing hardening guide
HP1916 No incident-notification process to ENISA / CSIRT
HP1917 No security assessment prior to placing on market
HP1918 AI component without cybersecurity risk assessment
Each pattern carries ClarificationQuestionsDE so the operator gets
auditor-grade questions to take back to the Anlagenbauer instead of
the engine inventing prose. PatternMatch carries DefaultAvoidability
(P=1 for all CRA patterns), feeding the PLr graph from Phase 17.
Measures (M540-M548, measures_library_cra.go):
M540 SBOM (SPDX or CycloneDX) with each machine release
M541 Signed updates with rollback protection
M542 Forced default-password change at first boot
M543 Published CVD policy (security.txt / PSIRT)
M544 Documented patch SLA with CVSS-tier response times
M545 User-facing hardening guide in the machine docs
M546 ENISA incident-notification process (24h/72h/14d)
M547 Authenticated update channel + integrity check
M548 Pre-market security assessment / pen-test
The library is urheberrechtlich neutral: identifiers only
(Verordnung (EU) 2024/2847, DIN EN 40000-1-2 Entwurf, IEC 62443,
ETSI EN 303 645, ISO/IEC 5962, ISO/IEC 29147). No normative text
is reproduced — DIN/Beuth proprietary content is referenced by
section number only.
Category-compatibility:
cyber_resilience pattern category accepts measures with
HazardCategory cyber_resilience, cyber_network, or
software_control. Updated in both the runtime helper
(iace_handler_init_helpers.go) and its test-mirror
(pattern_coverage_test.go) — both must move in lockstep.
Frontend (clarifications page):
When at least one clarification references "2024/2847" or
"40000-1-2" in its norm_references, a blue info-banner is
rendered at the top of the page:
"Cyber Resilience Act (CRA) — Hinweis zur Geltung
Diese Klärungsliste enthält Fragen zur Verordnung (EU)
2024/2847 (CRA). Die CRA gilt für Produkte mit digitalen
Elementen, die ab dem 11.12.2027 auf dem EU-Markt bereit-
gestellt werden. ..."
Reminds the user that the CRA pflichten are forward-looking
while still allowing the manufacturer to bake them in now.
LOC exceptions:
Added three pre-existing files to .claude/rules/loc-exceptions.txt
(manufacturer_safety_features.go, iace_handler_clarifications.go,
routes.go). All three grew across Phases 16-17 and are tagged as
Phase 5+ refactor backlog. [guardrail-change] marker required.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Phase 17 of the risk-assessment polish. Two pieces:
A) PLr per EN ISO 13849-1 Anhang A (Risikograph)
- HazardPattern.DefaultAvoidability (1 = P1, 2 = P2). Optional;
defaults to P1 if unset (conservative — operator can raise after
review).
- ComputePLr(s,f,p) implements the canonical 8-leaf binary tree
(S1F1P1 -> a, ..., S2F2P2 -> e). Pinned by 8 table-driven tests.
- SeverityToS / ExposureToF map the existing 1-5 fields to the
binary S/F at the documented threshold (3).
- At project initialise, every hazard's Description is appended
with "Risikograph EN ISO 13849-1 (Anhang A): S2 · F1 · P1 -> PLr c"
so the audit value is visible without leaving the hazard view.
- PatternMatch carries DefaultAvoidability so the init handler can
pick it up without a second pattern lookup.
B) Methoden-Kopf am Bericht
- GET /clarifications.html now opens with a standardised methodology
block: ISO 12100 Anhang B (hazard ID) + ISO 13849-1 Anhang A
(PLr graph) + ISO 12100 6.2/6.3/6.4 (reduction hierarchy). Same
wording on every export, ready for the Anlagenbauer-Uebergabe.
- Only norm identifiers — no norm text reproduced.
C) ISO12100Section in Hazard Description
- When a pattern is labeled with ISO12100Section, the hazard
description gets a "Klassifikation: EN ISO 12100 Anhang B,
Abschnitt 6.3.5.4" suffix. Provenance for the auditor.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Phase 16 of the Klaerungen / risk-assessment polish. Sources from
EN ISO 12100 Anhang B Tabelle B.1 are now first-class:
A) HazardPattern.ISO12100Section identifier (string), persisted only as
the section number (e.g. "6.3.5.5") — not the norm text. Keeps the
library urheberrechtlich neutral (DIN/Beuth license). 57 patterns
labeled today; rest will follow on touch.
B) Category split per ISO 12100 Nr. 4 vs Nr. 5:
- 16 patterns reclassified noise_vibration -> noise_hazard
- 7 patterns reclassified noise_vibration -> vibration_hazard
- 1 pattern (HP228 UV-/Laermexposition) kept multi-cat
acceptableMeasureCategories now accepts both new aliases plus the
legacy noise_vibration. Coverage test recognises both as valid.
C) 5 new ISO-12100-Annex-B gap patterns (HP1900-HP1904):
- HP1900 Vakuum-Verletzung (6.3.5.5)
- HP1901 Federenergie / elastische Elemente (6.2.10)
- HP1902 Rutschen/Stolpern auf rauer Oberflaeche (6.3.5.6)
- HP1903 Hochdruckinjektion (6.3.5.4) — includes clarifying
"no hand-locating of leaks" question
- HP1904 Ersticken durch Brustkorbquetschung (6.3.5.2)
The library now mirrors the ISO 12100 Annex B structure for the gaps
the Bremse benchmark surfaced.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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
[migration-approved]
Three pieces complete the Klaerungen lifecycle:
1. Migration 028: iace_clarifications + iace_clarification_comments +
iace_clarification_history. Deterministic clarification_key
(UNIQUE per project) so engine re-inits don't lose answers.
History table logs every status/answer transition. The previous
JSONB-in-metadata storage is kept as read-only fallback for
pre-migration projects until a one-shot upcopy script runs.
2. Multi-User-Workflow:
- assigned_to field on every clarification (free-text user kuerzel
for now; an FK to users can be added in a follow-up).
- Comment thread per clarification (POST .../comment, GET
.../detail returns the thread).
- Status-history log written by UpsertClarification when the
status or answer actually changes.
- Frontend Modal: Zugewiesen-an + Bearbeiter fields, comment
thread with inline post, collapsible history section.
3. PDF-Export via print-friendly HTML:
- GET /clarifications.html returns a standalone A4-styled
document with status badges, norm references, affected hazards
and a signature row at the bottom. The Bediener opens the link
and uses Strg-P / Cmd-P to save as PDF. No server-side PDF
dependency added.
- Frontend "PDF / Druck" button next to CSV export.
Backend:
- internal/iace/store_clarifications.go: UpsertClarification,
ListClarificationsForProject, GetClarificationByKey,
AddClarificationComment, ListClarificationComments,
ListClarificationHistory.
- internal/api/handlers/iace_handler_clarifications.go:
- AnswerClarification now writes the SQL row, falls back to legacy
JSONB read on list.
- PostClarificationComment, ListClarificationDetail,
ExportClarificationsHTML added.
Migration must be applied manually on Mac Mini and prod via
psql -f /migrations/028_iace_clarifications.sql — pattern as in
scripts/apply_*_migration.sh.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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.
Three pieces complete the Klaerungen UX:
1. Sidebar-Counter: layout.tsx polls /clarifications and shows a
colored open-count badge on the "Klaerungen" nav item. Refreshes
whenever the user changes route.
2. CSV-Export: new backend endpoint
GET /sdk/v1/iace/projects/:id/clarifications.csv produces a UTF-8-
BOM-prefixed semicolon-separated CSV (Excel-friendly) with ID,
Quelle, Kategorie, Frage, Status, Antwort, Begruendung, Bearbeiter,
answered_at, anzahl Gefaehrdungen, Gefaehrdungs-Namen, Norm-Refs.
Frontend Klaerungen-Seite bekommt einen "CSV-Export"-Button.
3. Hazard-Banner statt Fragentext im Benchmark-Detail: the previous
bulleted clarification list was duplicated across 48 hazards for a
single FANUC question. Phase 2 replaces it with a compact status
badge — "N offene Klaerung(en) — Klaerungen-Seite oeffnen" (orange)
or "Alle N Klaerungen beantwortet" (green) with a direct link.
Backend cleanup: iace_handler_init.go no longer appends the "Mit
Anlagenbauer zu klaeren" block to Hazard.Description. The description
stays focused on the scenario; clarifications live in the dedicated
endpoint and answers persist across re-inits via project.metadata.
The aggregated "Referenzierte Normen" line on the hazard is kept.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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.
New page "Klaerungen" between Massnahmen and Verifikation.
Backend:
- internal/iace/clarifications.go: Clarification struct + ClarificationAnswer +
BuildProjectClarifications() — aggregates pattern-level + manufacturer-
level questions from collectAllPatterns + GetManufacturerSafetyFeatures.
Deterministic IDs ("pattern:HP1640:0", "manuf:fanuc:dual-check-safety-dcs:1")
so persisted answers survive every re-init.
- internal/api/handlers/iace_handler_clarifications.go:
- GET /projects/:id/clarifications returns aggregated list with affected
hazard names + persisted answer state, sorted (open first).
- POST /projects/:id/clarifications/:cid/answer writes status/answer/
reasoning/answered_by/answered_at to project.metadata.clarification_-
answers — no DB schema change.
Frontend:
- admin-compliance/app/sdk/iace/layout.tsx: new "Klaerungen" nav item.
- app/sdk/iace/[projectId]/clarifications/page.tsx: table grouped by
source (FANUC / Pattern HP1640 / …), Filter Offen/Beantwortet/Alle,
search field, Antwort-Modal with status/answer/Begruendung/Bearbeiter.
A clarification answered once applies to ALL referenced hazards — the
operator no longer has to answer the same FANUC DCS question on 48
mechanical hazards individually.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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.
The Go init handler appends two annotated blocks to Hazard.Description
("Mit Anlagenbauer zu klaeren: ..." and "Referenzierte Normen: ...")
without changing the DB schema. The benchmark detail view only rendered
hazard.scenario || hazard.description, so the appended blocks were
silently hidden because scenario is always populated.
Split the description into three structured pieces:
1. extractScenario() — pure scenario text, stripped of trailing blocks
2. extractClarifications() — bullet list of "Mit Anlagenbauer zu klaeren"
3. extractEngineNorms() — pipe-separated norm references
Each piece is rendered as its own DetailRow. The FANUC DCS clarification
that already lives in the DB (48/115 hazards on the Bremse project) is
now visible in the Engine column.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
cmp_discovery_log.py:
- sqlite log at /data/cmp_discoveries.db: every LLM-discovered CMP
pattern recorded with domain, strategy, value, sample text
- Auto-promote (user-chosen 'voll automatisch' mode): when LLM returns
strategy=url AND extracted text >= 800 words, write a new module
/data/auto_cmp/auto_<slug>.py with derived regex matcher + reconstruct
- record_discovery() called from dsi_discovery._try_llm_cascade on success
cmp_library/_registry.py:
- Loads both hand-written modules from services/cmp_library/ AND
auto-promoted modules from /data/auto_cmp/ (CMP_AUTO_DIR env)
- Auto modules use importlib.util.spec_from_file_location, no package
install needed; restart consent-tester to pick up new ones
dsi_discovery.py:
- _try_llm_cascade now calls record_discovery() on every successful
LLM analysis (cached AND fresh)
main.py:
- GET /cmp-discoveries — admin endpoint listing all logged discoveries
- DELETE /cmp-discoveries/{id} — rollback (unlinks auto_*.py)
This closes the self-improving loop: first encounter with a new CMP fires
the LLM (cost) → discovery is auto-promoted → all future runs against the
same vendor pattern hit Phase B (Named CMP) at <50ms with no LLM call.
New module consent-tester/services/cmp_llm_fallback.py:
- LLMCookieExtractor: single-endpoint adapter (Ollama OR OpenAI-compat)
- LLMCascade: tries Qwen (local Mac Mini Ollama) first; falls through to
OVH (managed 120B) when Qwen returns no usable strategy
- LLMCascade.from_env(): reads OLLAMA_URL/CMP_LLM_MODEL + OVH_LLM_URL/
OVH_LLM_KEY/OVH_LLM_MODEL from environment
- LLM returns JSON {strategy: url|selector|text, value: ...}
- Valkey-backed cache per netloc (cmp:hint:<netloc>, 7-day TTL) — next run
against the same domain skips the LLM entirely
dsi_discovery.py:
- Wired network_log collector (URL/status/content-type/size of every JSON
response on the page) — passed to LLM prompt as observation
- After Named CMP (Phase B) + Heuristic (Phase A) both fail AND DOM
< 300 words: invoke LLMCascade.analyze(...)
- _apply_llm_hint executes the LLM's strategy: refetch URL via Playwright
request context, query DOM selector, or use text directly
- Cache HIT path: apply cached hint, only fall back to LLM if cache is stale
docker-compose.yml:
- consent-tester gets env vars + cmp-data volume (for Phase E)
- All LLM endpoints configurable via env, sensible defaults
consent-tester/requirements.txt:
- redis>=5.0 (asyncio client, Valkey-compatible)
- httpx>=0.27
Adds a curated database of safety-relevant features for the major
manufacturers across mechanical/plant engineering, written entirely in
own words with norm anchors. No verbatim manufacturer texts — therefore
no copyright issue:
- Markennennung (§ 23 MarkenG nominative use) is permitted.
- Fakten ueber Produkt-Sicherheitsfunktionen are not protected by § 2
UrhG (only Werke, not facts).
- NormReferences contain only the identifiers (e.g. "EN ISO 13849-1
PLd Kat.3"), never the norm text itself.
Coverage (52 entries across 12 categories):
Industrieroboter (10): FANUC DCS, KUKA SafeOperation, ABB SafeMove,
Yaskawa FSU, Staeubli CS9, Kawasaki Cubic-S, Mitsubishi MELFA,
Universal Robots PolyScope, Doosan PRS, Comau SafeNet
CNC/WZM (8): DMG MORI, Mazak, TRUMPF, Okuma, Hermle, Heidenhain
SPLC, GROB, Heller
Pneumatik (4): Festo, SMC, AVENTICS, Parker
Hydraulik (3): Bosch Rexroth, HAWE, HYDAC
Safety-PLC / Sicherheitstechnik (8): PILZ, SICK, Schmersal, Euchner,
Leuze, Phoenix Contact, Banner, Wieland
Standard-PLC (5): Siemens, Beckhoff, Rockwell, Schneider, B&R
Pressen (3): Schuler, Bruderer, AIDA
Spritzguss (3): Arburg, KraussMaffei, ENGEL
Verpackung (2): Krones, Bosch Packaging/Syntegon
Laser/Schweissen (3): Bystronic, Amada, Fronius
Foerdertechnik (2): Interroll, SEW EURODRIVE
Engine integration:
- LookupManufacturerFeaturesInText() scans the project narrative for
any of the manufacturer aliases (case-insensitive, umlaut-tolerant).
- Init-Handler appends matched feature clarifications to the relevant
hazard's "Mit Anlagenbauer zu klaeren:" block — for the right
HazardCategory only (e.g. FANUC DCS only on mechanical_hazard).
- For a Bremse project narrative mentioning "Fanuc Robodrill", the
engine now adds clarification questions like "Ist DCS am Roboter
konfiguriert?" to relevant mechanical hazards automatically.
Tests: 7 new pin tests — manufacturer count, norm prefixes, FANUC/KUKA
detection in narrative, umlaut robustness (Staeubli vs Staubli).
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
cmp_extractor.py refactored to thin coordinator (123 LOC, was 223).
Discovers all CMP modules via cmp_library/_registry.py:load_all() at
import time. Restart consent-tester to pick up new modules.
New cmp_library/ folder:
- _registry.py: auto-discovers all modules with MATCHER + reconstruct()
- epaas.py: BMW Group ePaaS (extracted from cmp_extractor)
- onetrust.py: cdn.cookielaw.org Groups/Cookies schema
- cookiebot.py: consent.cookiebot.com Categories schema
- usercentrics.py: api.usercentrics.eu services schema
- didomi.py: sdk.privacy-center.org notice + vendors + purposes
- trustarc.py: consent.trustarc.com categories + vendors
Each module:
- MATCHER: re.Pattern matching the CMP JSON endpoint URL
- reconstruct(d: dict) -> str: builds German Markdown cookie-policy text
Phase E (self-improving) will write auto_*.py files into the same folder;
_registry already picks those up via pkgutil.iter_modules.
GT 1.8 fordert konkret den 'sicher begrenzten Bewegungsbereich (Dual
Check Safety)'. HP1654 hatte nur M061 'Feste trennende Schutzeinrich-
tung' als Mitigation. Ergaenzt um M494 (Safe Limited Position/Space mit
DCS-Erlaeuterung), M501 (Schutzzaun-Lastbemessung) und M502 (Greifer-
Fail-Safe). Klaerungsfragen verweisen explizit auf DCS bei FANUC,
SafeMove bei ABB, SafeOperation bei KUKA und die EN ISO 13849-1 PLd/
Kat.3-Validierung.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
New module cmp_heuristic.py with:
- looks_like_cookie_policy(data): shape-based classifier (top-level keys
cookies/categories/providers/vendors/purposes/cookieList/etc. + at
least 2 name+description objects, or IAB TCF v2 vendors[]+purposes[])
- reconstruct_generic(data): walks JSON, extracts name + description
fields + standalone prologue/dataController/persistence fields,
emits flat German Markdown text (max 5000 words, dedup)
cmp_extractor.py wired so that AFTER named CMP matchers (epaas,
onetrust) fail, every JSON response on the page is tested for the
heuristic. If matched, payload is captured as '_heuristic' kind and
reconstructed via the generic walker.
This is Phase A of the 4-stage cascade (B-D follow). Unknown CMPs that
return JSON now work without hand-coding each one.
Pre-filter: skips response paths /api/config, /beacon, /track,
/analytics, /fonts/, /log/, /heartbeat/, /.well-known/ to avoid
spamming the heuristic on every Playwright load.
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.
Library measures carry NormReferences (EN/IEC/ISO/DIN/TRBS/TRGS Ziff./Kap./
Pos.) but they were dropped on persist: CreateMitigationRequest only
wrote Name + Description. The Fachmann benchmark file lists Normen for
34 of 60 hazards — the engine had this data already but lost it on the
way to the UI.
Fix without DB schema change:
- Mitigation.Description gets a "Normen: EN 60204-1 Ziff. 6.2 | EN 61140"
line appended when the measure has NormReferences. Pipe separator keeps
the inline panel short and grep-friendly.
- After all mitigations land, the aggregated dedup'd norm list for the
hazard is appended to Hazard.Description as a single "Referenzierte
Normen: ..." line so the UI can show one panel per hazard without
scanning every mitigation.
Audit of library coverage (per-pattern) showed GT-Bremse Normen are
generally present and richer:
- HP1640 covers GT 2.2 (EN 60204-1 Ziff. 6.2, Ziff. 8.2.3, EN 61140 +)
- HP1641 covers GT 2.4 (EN 60204-1 Ziff. 8.2.6 +)
- HP1605 covers GT 1.7 (ISO 10218-1 Ziff. 5.6.2, 5.8.3 — Ziff. 5.7.3 fehlt)
- HP1671 covers GT 1.30 (EN 12417 — Pos. detail fehlt)
Followup: 2 fine-grained sub-paragraph references (5.7.3, Pos. 1.1.4)
can be added later as measure-text updates.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
ZoneDE 'Pneumatikkomponenten der Anlage' kollidiert nach normalizeZoneKey
mit HP1630 'Pneumatikschlaeuche der Automation' im 3-signifikante-Wort-
Vergleich. Neue Zone 'Berstgefaehrdete Druckwandungen Pneumatik (Leitungs-
wand, Dichtung, Verschraubung)' hat semantisch eigenstaendige Schluessel-
woerter — Dedup mergt nicht mehr in HP1630.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Drei nachhaltige Verbesserungen, getrieben durch die Bremse-Benchmark-
Faelle GT 1.4, GT 1.30 und GT 7.4. Die Engine erfindet weiterhin
keine Fachmann-Kommentare — Kommentare bleiben aus, weil sie ein
Verstaendnis der konkreten Anlage erfordern, das die Engine nicht
hat. Statt dessen liefert die Engine norm-basierte Klaerungsfragen
und ein praeziseres Pattern-Vokabular.
A) HazardPattern.ClarificationQuestionsDE — neues optionales Feld:
- Pattern hinterlegt prueffaehige Fragen, die der Bediener mit dem
Anlagenbauer abklaert. Beispiele:
- HP1640: "Liegt ein Pruefprotokoll nach EN 60204-1 vor?"
- HP1666: "Ist die WZM als CE-konformes Subsystem integriert?"
- HP1604: "Ist DCS am Roboter konfiguriert und validiert?"
- Init-Handler haengt die Fragen an Hazard.Description an mit dem
Marker "Mit Anlagenbauer zu klaeren:". Kein DB-Schema-Aenderungs-
bedarf.
- 11 Patterns mit Klaerungsfragen versehen (HP1602, HP1604, HP1611,
HP1612, HP1620, HP1622, HP1637, HP1640, HP1641, HP1666, HP1685).
B) HP1632 "Bersten druckbeaufschlagter Pneumatik-Komponente" — neues
Pattern, semantisch DISTINKT zu HP1630 "Abspringen":
- Bersten = Material-/Druckversagen der Komponente, Mediumaustritt
- Abspringen = Verbindung loest sich, Peitscheneffekt
Bremse-Benchmark GT 1.4 sprach von Bersten, HP1630 nur von
Abspringen — ein 66%-Frontend-Match war eine Sackgasse. Mit
HP1632 feuert die Engine ein eigenes Hazard, das auf GT 1.4
einen sauberen Volltreffer liefert.
C) HP1637 "Einatmen von KSS-Aerosolen" — Massnahmen vervollstaendigt:
Vorher nur M141 (Sicherheitszeichen), neu zusaetzlich M405 (KSS-
Aerosolabsaugung), M418 (AGW-Ueberwachung), M526 (WZM-Tueren
geschlossen waehrend Bearbeitung), M408 (Hautschutzplan).
Klaerungsfrage: "Wurde die Aerosolkonzentration nach Bearbeitungs-
ende messtechnisch ermittelt und mit dem AGW verglichen?"
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
HP1671 "Druckluft-Verletzung in Bearbeitungszelle" matched zwar das
GT-1.30 Szenario "Einstich, Augenverletzung in Bearbeitungszelle" exakt
nach Name und Scenario, hatte aber nur eine einzige Massnahme M061
"Feste trennende Schutzeinrichtung". Die drei spezifischen Massnahmen
des Fachmanns (Reinigungsduese in Zelle integriert / Druckluft bei
Tueroeffnung aus / Einhausung-Lastbemessung) blieben unsichtbar, weil
mein neuer GT-Bremse-Pattern HP1712 zwar diese Massnahmen kennt, aber
durch RequiredEnergyTags=["pneumatic"] in diesem Projekt nicht feuert.
Fix: HP1671 SuggestedMeasureIDs ["M061"] -> ["M504", "M505", "M501",
"M061", "M141"]. EN 12417 Kap. 5.2 / Pos. 1.1.4 ist jetzt durch
M504/M505 abgedeckt. HP1712 bleibt als Backup-Pattern fuer Projekte
mit explizitem pneumatic-Tag bestehen.
Followup: HP1671 und HP1712 sind semantisch redundant — Konsolidierung
ist Teil der naechsten Pattern-Hygiene-Iteration.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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.
Background: hazard_patterns_extended.go (HP045-074) and _extended2.go
(HP074-102) shared their entire ID range with the semantically-different
patterns in hazard_patterns_cobot.go, hazard_patterns_press.go,
hazard_patterns_operational.go and hazard_patterns_extended_dguv.go.
The collision had lived unnoticed because TestGetBuiltinHazardPatterns_-
UniqueIDs only checks the 44 builtin patterns (HP001-HP044).
Examples of the collision:
- HP059 = "Kollision Mensch-Roboter" (cobot.go) vs "Kupplung — mechanisch" (extended.go)
- HP060 = "Quetschen durch Werkzeug am Cobot" (cobot.go) vs "Diagnosemodul — Software" (extended.go)
- HP073 = "Wartung ohne LOTO" (operational.go) vs "Hydraulikventil — hydraulisch" (extended.go)
At runtime collectAllPatterns() returned both patterns under the same ID
which made downstream lookups (e.g. hazardPatternMeasures map keyed by
pattern_id) non-deterministic — last-loaded wins, dropping the other
pattern's mitigation set silently.
Rename strategy (no deletes — both patterns are real and earn their
SuggestedMeasureIDs after the category-filter work):
extended.go HP045..HP073 -> HP1800..HP1828 (29 IDs)
extended2.go HP074..HP102 -> HP1830..HP1858 (29 IDs)
cobot/press/operational/extended_dguv keep their original IDs because:
- compliance_triggers.go references HP059/HP060 with the cobot meaning
- pattern_engine_test.go references HP073 with the LOTO/maintenance meaning
- phase3_4_test.go references HP073 the same way
New regression test:
- TestAllPatterns_UniqueIDs runs over collectAllPatterns() and fails if
ANY pattern in the runtime set duplicates an ID. The old
TestGetBuiltinHazardPatterns_UniqueIDs stays for the builtin subset.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Two-part nachhaltiger fix replacing the previous "fill to 5 mitigations
no matter what" behavior that the GT-Bremse benchmark proved
unfaithful (e.g. HP1625 "scharfe Kanten" returning M005 "Rotations-
bewegung vermeiden" via category fallback; HP1651 "Wiederanlauf
Roboter" returning M054 "Sichere thermische Auslegung" via
mismatched pattern reference).
PART A — Set-based category filter (handlers package):
- acceptableMeasureCategories: replaces 1:1 patternCatToMeasureCat
with a curated set per pattern category, so e.g.
safety_function_failure now accepts software_control measures
(watchdogs, plausibility checks) and emc_hazard accepts both
electrical and software_control measures
- isCategoryCompatible: gate every measure id against the accepted
set before creating a mitigation; mismatches log MEASURE-SKIP
- The old category fallback is REMOVED. A hazard whose pattern has
no category-compatible measure is now created with zero mitigations
and logged as COVERAGE-GAP — the operator must consult an expert.
No more silent invention of generic defaults.
PART B — 235 pattern author-error fixes across 26 files:
- HP040-HP044 (AI): M101/M102/M103 (Auffangwanne/Absauganlage) ->
M133 Anomalieerkennung + M214 Plausibilitaet + M213 Sensor-Redundanz
+ M044 Zweikanalige Steuerung + others
- HP011-HP015, HP104-HP109, HP1085-HP1095, HP1281-HP1334 (electrical):
M001-M005/M054/M061 placeholders -> M481/M482 Isolation +
M511-M522 PE/Schutzleiter/RCD/Hauptschalter
- HP110-HP1331 (material_environmental): M101-M103 -> M384-M395
Brandschutz/Laserschutz + M533/M408 SDB/PSA
- HP800-HP858, HP1178-HP1264 (software/sensor/hmi):
M101/M104 -> M105/M106/M107/M214 SPS/Watchdog/Plausibilitaet
- HP026, HP611-HP1690 (ergonomic): M001/M082 -> M353-M360 +
M530-M532 Hebehilfe/ergonomische Hoehe
- HP201-HP1697 (mechanical): M054/M051 -> M002/M008/M061/M141 +
M487/M488 Tueroeffnung-Stillsetzung/Wiederanlauf
- Plus EMF/Strahlung/Brand/Lärm/Vibration/Kommunikation/Cyber
Coverage shift (Pattern-Author-Fehler bei aktiviertem Set-Filter):
start: 237 patterns with zero category-compatible measures
after Stufe 1A: 5 (AI)
after Stufe 1B: 20 (mechanical Bestand)
after Stufe 1C: 35 (electrical Bestand)
after Stufe 1D: 29 (material_environmental)
after Stufe 1E: 29 (software/sensor/hmi)
after Stufe 1F: 20 (ergonomic)
after Stufe 1G: 80 (thermal/comm/radiation/fire/safety)
final: 0 (28 extended.go/extended2.go duplicates fixed)
New regression tests:
- TestEveryPattern_HasCategoryCompatibleMeasure: every pattern in
collectAllPatterns() must reference at least one category-compatible
measure; gaps must be explicitly listed in AllowlistKnownGaps
(currently empty). Fails CI for any new pattern that drifts.
- TestAcceptableMeasureCategories: pins the set-mapping for the
7 most-bug-prone pattern categories.
- TestIsCategoryCompatible_EmptyMeasureCat: protects legacy entries.
A separate task #11 tracks 58 HP-ID duplicates between
extended.go/extended2.go and cobot.go/press.go/operational.go —
patterns are semantically different and TestGetBuiltinHazardPatterns_-
UniqueIDs misses them because it only checks HP001-HP044.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
BMW ePaaS URLs use 3 segments between /policypage/ and .epaas.json:
/epaas/prod/policypage/<tenant>/<config-hash>/<locale>.epaas.json
The old pattern only matched 2 segments. Switch to a tolerant pattern
that matches any path before .epaas.json (anchored at .epaas.json end).
Previous threshold (DOM < 300 words) missed the BMW case where Playwright
extracted 346 words of pure site navigation. The CMP JSON had 1673 words
of real policy content but was discarded.
New heuristic: prefer CMP when ANY of:
- DOM < 300 words (existing)
- CMP text >= 1000 words (authoritative at scale)
- CMP text >1.5x longer than DOM
BMW (and other big enterprise sites) do NOT render cookie policies as
static HTML. Their widget loads structured data from a JSON endpoint
(BMW: ePaaS at /epaas/prod/policypage/.../<locale>.epaas.json) and
renders it client-side after consent. Our DOM extraction therefore only
captured site navigation (603 words of header/footer chrome), not the
actual policy.
New module consent-tester/services/cmp_extractor.py:
- CMPCapture: response listener that catches policy JSON during navigation
- Reconstructors for ePaaS (BMW) + OneTrust placeholder
- Returns Cookie-Richtlinie text built from policyPageMetadata +
categories + providers (BMW: 1673 words reconstructed vs. 603 noise)
dsi_discovery.py:
- Attach CMPCapture before page.goto
- After self-extraction: if rendered DOM < 300 words AND CMP captured a
payload, prefer the CMP-reconstructed text. This bypasses the empty
'.cookie-policy' div problem entirely.
6 supplementary measures (M410-M420) were silently overwritten by
metalworking duplicates in measureByID lookups, so robot-cell electrical
patterns resolved to chip-extraction/cleaning fallbacks instead of
equipotential bonding, creepage, EMC, or hose-burst protection. Rename
supplementary IDs to M475-M480 and rewire 13 affected pattern references
in robot_cell + robot_cell_ext.
HP1640 (direct contact with live parts, GT 2.2): priority 98->99, drop
RequiredEnergyTags gate so it fires in robot cells without an electrical
tag, expand mitigations to 5 concrete TRBS 2131 / IEC 60204-1 / EN 61140
measures (basic protection, double insulation, earthing, insulation
monitoring, equipotential bonding) — was previously losing to HP1688
even though HP1688 describes a different scenario.
HP1688 (touch voltage from potential differences): priority 98->96 so it
no longer outranks HP1640 for the direct-contact case; mitigations
expanded from M410-only to 4 concrete electrical measures.
Add regression tests pinning HP1640 contact-protection resolution and
M475 = Potentialausgleich. Existing TestGetProtectiveMeasureLibrary_-
UniqueIDs now actually enforces uniqueness (previously masked by
last-wins map override).
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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>
KSS, EMV, ESD, DCS, PLR, SIL, HMI, SPS, RCD, LOTO, PSA are
abbreviations that should NOT trigger the relevance filter.
bersten, platzen, abspringen, spritzen, einatmen, ausrutschen,
herabfallen, durchschlaegen, wegschleudern are action words that
appear in many patterns and don't indicate a specific machine.
Fixes: HP1633-HP1675 (KSS patterns) were filtered out because
"kss" was not in the narrative but also not in genericSafetyTerms.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Robot cell patterns now fire BEFORE generic patterns (Priority 96-99
vs generic 85-95). This ensures pattern-specific SuggestedMeasureIDs
(M420 for KSS, M410 for Potentialausgleich) reach the hazard.
Removed debug fmt.Println statements.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
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