Merge branch 'chore/license-mapping-audit' — license mapping + audit script + DGUV + /staerken marketing page
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Benjamin Admin
2026-05-22 00:54:49 +02:00
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# Lizenzregeln der Control-Pipeline
> **Stand:** 2026-05-21 — Mapping festgezurrt nach DB-Inspektion und IACE-Audit.
>
> Die Pipeline klassifiziert jede Regulation (und damit jedes daraus extrahierte
> Chunk und jeden atomic_control) in eine von **drei Lizenzregeln**. Die Regel
> entscheidet, ob der Volltext aufbewahrt werden darf und welche Attribution im
> Ausgabe-Renderer Pflicht ist.
## Die drei Regeln
| Regel | Bedeutung | Volltext speichern? | Attribution Pflicht? | Beispiele |
|-------|-----------|---------------------|----------------------|-----------|
| **1** | Wörtlich — Hoheitsrecht / Public Domain | ✓ | nein (empfohlen für Audit) | EU-Recht (EUR-Lex), Bundesrecht, Satzungsrecht (DGUV UVV), TRBS, TRGS, ASR, US Federal Code (OSHA), NIST SP, EU-Leitfäden |
| **2** | Wörtlich mit Attribution — freie Lizenzen | ✓ | **ja** | OWASP (CC-BY-SA-4.0), OECD AI Principles (OECD_PUBLIC), ENISA-Dokumente (CC-BY-4.0), Apache-2.0 Werke |
| **3** | Nur zitieren — proprietäre Standards | ✗ | nicht anwendbar (kein Volltext) | DIN, EN, ISO, ANSI, UL, IEC, IEEE, DGUV Regeln/Informationen/Grundsätze, Bitkom-Leitfäden, BSI-Bausteine (urheberrechtlich) |
**Wichtige Klarstellung:** Regel 3 = "nur Identifier/Abschnitt zitieren", **nicht** "umformulieren". Die ursprüngliche Bezeichnung "neu formulieren" war irreführend. Korrekt: Bei Regel-3-Quellen darf die Pipeline den Volltext nicht speichern; sie bewahrt nur die Quellenreferenz (regulation_id + article/paragraph), und der Output-Renderer zeigt diese Referenz im Frontend/PDF.
## Mapping `license_type` → `license_rule`
| license_type | license_rule | Erklärung |
|---|---|---|
| `EU_LAW`, `EU_PUBLIC` | 1 | EU-Verordnungen, Richtlinien, OJ-Veröffentlichungen, EU-Leitfäden |
| `DE_LAW`, `DE_PUBLIC` | 1 | Bundesgesetze, TRBS, TRGS, ASR, DGUV-UVV (Satzungsrecht) |
| `AT_LAW`, `CH_LAW`, `FR_LAW`, `IT_LAW`, `ES_LAW`, `NL_LAW`, `HU_LAW` | 1 | Andere EU-Mitgliedsstaaten-Recht |
| `US_GOV_PUBLIC`, `NIST_PUBLIC_DOMAIN`, `OSHA_PUBLIC` | 1 | US Federal Code (17 U.S.C. §105 Public Domain) |
| `CC-BY-4.0`, `CC-BY-SA-4.0`, `CC-BY-3.0`, `CC-BY-SA-3.0` | 2 | Creative-Commons mit Attribution-Pflicht |
| `Apache-2.0`, `MIT` | 2 | Permissive OSS-Lizenzen, NOTICE-Pflicht |
| `OECD_PUBLIC`, `ENISA_CC_BY_4.0` | 2 | Behörden-Publikationen mit Attribution-Auflage |
| `DIN_COPYRIGHT`, `ISO_COPYRIGHT`, `ANSI_COPYRIGHT`, `UL_COPYRIGHT`, `IEC_COPYRIGHT` | 3 | Normungsorganisationen — nur Identifier-Zitat |
| `DGUV_COPYRIGHT` | 3 | DGUV Regeln/Informationen/Grundsätze (nicht UVV) |
| `BITKOM_COPYRIGHT`, `BSI_COPYRIGHT`, `VDMA_COPYRIGHT` | 3 | Verbands-/Behörden-Publikationen mit eigenständigem Urheberrecht |
| `OWN_WORK` | 3 | BreakPilot-Eigentexte (Templates, eigene Patterns) — kein externes Lizenzrisiko, aber auch kein Public-Domain-Status |
**Sonderfall DGUV:** Die Klasse trennt sich nach Publikationstyp:
- DGUV **Vorschriften / UVV**`DE_LAW` → Regel 1
- DGUV **Regeln, Informationen, Grundsätze**`DGUV_COPYRIGHT` → Regel 3
## Auswirkung pro Pipeline-Stage
| Stage | Verhalten bei Regel 1 | Regel 2 | Regel 3 |
|---|---|---|---|
| Stage 6 ControlCompose (`pipeline_adapter.py:147`) | speichert `chunk_text` | speichert `chunk_text` | speichert `chunk_text = None` |
| Atomic-Control-Bildung | Volltext als Quelle | Volltext + Attribution-Vermerk | nur regulation_id + article |
| Output-Renderer (Frontend/PDF) | optionaler Quellen-Hinweis | **Pflicht-Attribution in Footer + Inline** | nur Identifier rendern |
| Tech-File-Anhang | Quelle nennen | Quelle + Lizenz-URL | Identifier-Liste |
## Quellen ohne Klassifikation
Aktuell sind in `regulation_registry` **232 Regulationen** klassifiziert (Stand 2026-05-21). Die folgenden müssen noch ergänzt werden (Task #20 deckt den DGUV-Ingest):
| Quelle | Regel | Begründung |
|---|---|---|
| TRBS-Familie (24 PDFs im RAG) | 1 | Technische Regeln Betriebssicherheit — BAuA Bundesarbeitsblatt |
| TRGS-Familie (alle Volltext-Chunks) | 1 | Technische Regeln Gefahrstoffe — BAuA |
| ASR-Familie (17 PDFs) | 1 | Arbeitsstättenregeln — BAuA |
| OSHA 29 CFR 1910 Subpart O + Technical Manual | 1 | US Federal Public Domain (17 U.S.C. §105) |
| DGUV Vorschrift 1 + UVV-Familie (sobald ingest) | 1 | Satzungsrecht der BG |
| DGUV Regel 100-500 + Information 209-072/074/073 | 3 | DGUV-Copyright, nur Identifier |
| DIN-Identifier-Tabelle (ohne Volltext) | 3 | DIN-Beuth-Copyright |
| ANSI B11.0 + RIA R15.06 + UL 508A Identifier | 3 | ANSI/UL-Copyright |
| ISO 12100/13849/13857 Identifier | 3 | ISO-Copyright |
## Audit-Pflicht
Vor jedem Ingest neuer Quellen:
1. Lizenz prüfen (publikationen.dguv.de, EUR-Lex, etc.)
2. license_type aus obiger Tabelle wählen — wenn nicht vorhanden, hier ergänzen
3. license_rule wird daraus deterministisch abgeleitet
4. Attribution-Text bei Regel 2 ist Pflichtfeld
Vor jedem Output:
- Wenn ein atomic_control aus einer Regel-3-Quelle stammt: prüfen dass NUR Identifier gezeigt wird, niemals Volltext
- Wenn aus Regel-2-Quelle: Attribution muss im PDF-Footer und im Frontend-Tooltip vorhanden sein
- Wenn aus Regel-1-Quelle: empfohlen Quelle nennen für Auditierbarkeit
## Verweise
- Schema: `migrations/002_regulation_registry.sql`
- Code: `services/regulation_registry.py`, `services/pipeline_adapter.py`
- Seed-Script: `scripts/f1_migrate_regulation_registry.py`
- Tests: `tests/test_regulation_registry.py` (assert: rule IN (1,2,3))
@@ -0,0 +1,256 @@
#!/usr/bin/env python3
"""Audit script for license classification gaps in the control pipeline.
Reports:
1. **regulation_registry coverage** — how many regulations are classified, by
rule and license_type.
2. **atomic_controls without license_rule** — how many controls reference a
regulation_id that has no entry (or no license_rule) in the registry.
3. **Qdrant payload consistency** — for each indexed collection, how many
chunks carry both ``license`` and ``license_rule`` payload fields.
The goal is to surface every record where the engine could in principle
extract or emit content but the license rule is unknown — those records are
the highest-risk material in a license audit.
Usage::
python3 scripts/audit_license_classification.py --db-host 100.80.114.48
Add ``--check-qdrant`` to also probe ``http://<host>:6333`` collections.
"""
from __future__ import annotations
import argparse
import json
import sys
from collections import Counter
from pathlib import Path
from typing import Optional
from urllib import request as urllib_request
sys.path.insert(0, str(Path(__file__).resolve().parent.parent))
DEFAULT_HOST = "100.80.114.48"
DEFAULT_PORT = 5432
DEFAULT_USER = "breakpilot"
DEFAULT_DB = "breakpilot_db"
def parse_args() -> argparse.Namespace:
p = argparse.ArgumentParser(description=__doc__)
p.add_argument("--db-host", default=DEFAULT_HOST)
p.add_argument("--db-port", type=int, default=DEFAULT_PORT)
p.add_argument("--db-user", default=DEFAULT_USER)
p.add_argument("--db-name", default=DEFAULT_DB)
p.add_argument("--db-password", default="")
p.add_argument("--check-qdrant", action="store_true")
p.add_argument("--qdrant-host", default="100.80.114.48")
p.add_argument("--qdrant-port", type=int, default=6333)
p.add_argument("--json", action="store_true", help="Emit JSON result on stdout")
return p.parse_args()
def audit_registry(conn) -> dict:
"""Coverage of regulation_registry."""
cur = conn.cursor()
cur.execute(
"SET search_path TO compliance, public; "
"SELECT license_rule, license_type, COUNT(*) "
"FROM regulation_registry GROUP BY license_rule, license_type "
"ORDER BY license_rule, license_type;"
)
by_rule_and_type: list[tuple] = []
by_rule: Counter = Counter()
for rule, ltype, count in cur.fetchall():
by_rule_and_type.append((rule, ltype or "(empty)", count))
by_rule[rule] += count
cur.execute(
"SELECT COUNT(*) FROM regulation_registry "
"WHERE license_type IS NULL OR license_type = '';"
)
missing_type = cur.fetchone()[0]
cur.execute("SELECT COUNT(*) FROM regulation_registry;")
total = cur.fetchone()[0]
return {
"total": total,
"by_rule": dict(by_rule),
"by_rule_and_type": by_rule_and_type,
"missing_license_type": missing_type,
}
def audit_atomic_controls(conn) -> dict:
"""Controls whose source regulation has no license rule.
Important: the schema differs between core (bp-core) and customer
deployments. We probe a handful of likely column names and skip if
none are found.
"""
cur = conn.cursor()
# Detect controls table
cur.execute(
"SELECT table_name FROM information_schema.tables "
"WHERE table_schema='compliance' AND table_name IN "
"('atomic_controls','atomic_controls_dedup','canonical_controls');"
)
tables = [r[0] for r in cur.fetchall()]
if not tables:
return {"skipped": True, "reason": "no controls table found"}
result: dict = {"tables": {}}
for tbl in tables:
cur.execute(
f"SELECT column_name FROM information_schema.columns "
f"WHERE table_schema='compliance' AND table_name='{tbl}';"
)
cols = {r[0] for r in cur.fetchall()}
if "license_rule" not in cols:
result["tables"][tbl] = {"skipped": True, "reason": "no license_rule column"}
continue
cur.execute(f"SELECT COUNT(*) FROM compliance.{tbl};")
total = cur.fetchone()[0]
cur.execute(
f"SELECT license_rule, COUNT(*) FROM compliance.{tbl} "
f"GROUP BY license_rule ORDER BY license_rule;"
)
by_rule = {str(r[0]): r[1] for r in cur.fetchall()}
cur.execute(
f"SELECT COUNT(*) FROM compliance.{tbl} WHERE license_rule IS NULL;"
)
missing = cur.fetchone()[0]
result["tables"][tbl] = {
"total": total,
"by_rule": by_rule,
"missing_license_rule": missing,
}
return result
def audit_qdrant(host: str, port: int) -> dict:
"""Probe Qdrant collections for license + license_rule payload coverage.
Samples 500 points per collection and reports how many have neither
field populated.
"""
out: dict = {"collections": {}}
base = f"http://{host}:{port}"
try:
with urllib_request.urlopen(f"{base}/collections", timeout=10) as r:
colls = json.loads(r.read()).get("result", {}).get("collections", [])
except Exception as e:
return {"error": str(e)}
for c in colls:
name = c["name"]
if "compliance" not in name and "atomic_controls" not in name:
continue
payload = {"limit": 500, "with_payload": True, "with_vector": False}
req = urllib_request.Request(
f"{base}/collections/{name}/points/scroll",
data=json.dumps(payload).encode(),
headers={"Content-Type": "application/json"},
)
try:
with urllib_request.urlopen(req, timeout=15) as r:
points = json.loads(r.read()).get("result", {}).get("points", [])
except Exception as e:
out["collections"][name] = {"error": str(e)}
continue
sampled = len(points)
both_set = 0
only_license = 0
only_rule = 0
neither = 0
for p in points:
pl = p.get("payload", {}) or {}
has_lic = bool(pl.get("license"))
has_rule = pl.get("license_rule") is not None
if has_lic and has_rule:
both_set += 1
elif has_lic:
only_license += 1
elif has_rule:
only_rule += 1
else:
neither += 1
out["collections"][name] = {
"sampled": sampled,
"both_set": both_set,
"only_license_field": only_license,
"only_license_rule_field": only_rule,
"neither_set": neither,
"neither_pct": round(neither / sampled * 100, 1) if sampled else 0,
}
return out
def main() -> int:
args = parse_args()
try:
import psycopg2
except ImportError:
print("error: psycopg2 not installed (pip install psycopg2-binary)", file=sys.stderr)
return 2
conn = psycopg2.connect(
host=args.db_host,
port=args.db_port,
user=args.db_user,
dbname=args.db_name,
password=args.db_password or None,
)
try:
registry = audit_registry(conn)
controls = audit_atomic_controls(conn)
finally:
conn.close()
qdrant: Optional[dict] = None
if args.check_qdrant:
qdrant = audit_qdrant(args.qdrant_host, args.qdrant_port)
result = {"registry": registry, "atomic_controls": controls, "qdrant": qdrant}
if args.json:
print(json.dumps(result, indent=2, default=str))
return 0
print("=" * 60)
print(" Audit — License Classification")
print("=" * 60)
print()
print(f"## regulation_registry ({registry['total']} rows)")
print(f" By rule: {registry['by_rule']}")
print(f" Missing license_type: {registry['missing_license_type']}")
print()
print("## atomic_controls")
for tbl, info in controls.get("tables", {}).items():
if info.get("skipped"):
print(f" {tbl}: SKIPPED ({info['reason']})")
continue
print(f" {tbl}: {info['total']} rows")
print(f" by_rule={info['by_rule']}")
print(f" missing_license_rule={info['missing_license_rule']}")
print()
if qdrant:
print("## qdrant")
for name, info in qdrant.get("collections", {}).items():
if "error" in info:
print(f" {name}: ERROR {info['error']}")
continue
print(
f" {name:30} sampled={info['sampled']:4} "
f"both={info['both_set']:4} "
f"neither={info['neither_set']:4} ({info['neither_pct']}%)"
)
return 0
if __name__ == "__main__":
raise SystemExit(main())
@@ -0,0 +1,184 @@
#!/usr/bin/env python3
"""Backfill license_rule on canonical_controls by inheriting from parent.
Background
==========
Audit (audit_license_classification.py) showed that 279,384 of 314,811 rows
in compliance.canonical_controls have NULL license_rule. Drilling in:
- 261,980 of those (94%) have a parent_control_uuid whose parent already
carries a non-NULL license_rule. The pass0b decomposition pipeline did
not propagate the rule to its child controls — this is a clear inheritance
bug, fixable without any classification decisions.
- 16,617 have a parent that itself has no license_rule (transitive case).
Inheriting iteratively converges to either rule-set or root-orphan.
- 787 have no parent at all (decomposition roots). These need cluster-based
manual classification (see Strategy Notes at the bottom of this file).
This script runs the inheritance fix in three idempotent stages and
prints per-stage counts before any write happens.
Usage::
# Always dry-run first:
python3 scripts/backfill_license_rule.py --db-host 100.80.114.48 \\
--db-password breakpilot123 --dry-run
# If counts look right:
python3 scripts/backfill_license_rule.py --db-host 100.80.114.48 \\
--db-password breakpilot123 --apply
The script is safe to rerun — it only touches rows where license_rule
IS NULL.
"""
from __future__ import annotations
import argparse
import sys
def parse_args() -> argparse.Namespace:
p = argparse.ArgumentParser(description=__doc__)
p.add_argument("--db-host", default="100.80.114.48")
p.add_argument("--db-port", type=int, default=5432)
p.add_argument("--db-user", default="breakpilot")
p.add_argument("--db-name", default="breakpilot_db")
p.add_argument("--db-password", required=True)
g = p.add_mutually_exclusive_group(required=True)
g.add_argument("--dry-run", action="store_true")
g.add_argument("--apply", action="store_true")
p.add_argument("--max-iterations", type=int, default=5,
help="Cap on inheritance iterations to avoid loops")
return p.parse_args()
# Stage 1: direct parent has license_rule — single UPDATE.
# Stage 2: iterative — parent did not have it, but a grandparent does.
# We loop until no more rows can be filled or max-iterations.
# Stage 3: residual rows with no resolvable parent. Report them clustered
# by category/pattern_id so the user can classify by family.
SQL_REPORT_NULLS = """
SET search_path TO compliance, public;
SELECT
CASE WHEN cc.parent_control_uuid IS NULL THEN 'no_parent'
WHEN p.license_rule IS NULL THEN 'parent_null'
ELSE 'parent_set' END AS bucket,
COUNT(*) AS n
FROM canonical_controls cc
LEFT JOIN canonical_controls p ON cc.parent_control_uuid = p.id
WHERE cc.license_rule IS NULL
GROUP BY 1 ORDER BY 2 DESC;
"""
SQL_INHERIT_FROM_PARENT = """
SET search_path TO compliance, public;
UPDATE canonical_controls cc
SET license_rule = p.license_rule, updated_at = NOW()
FROM canonical_controls p
WHERE cc.parent_control_uuid = p.id
AND cc.license_rule IS NULL
AND p.license_rule IS NOT NULL;
"""
SQL_REPORT_ORPHAN_CLUSTERS = """
SET search_path TO compliance, public;
SELECT
COALESCE(category, '(null)') AS category,
COALESCE(pattern_id, '(null)') AS pattern_id,
COALESCE(generation_strategy, '(null)') AS gen,
COUNT(*) AS n
FROM canonical_controls
WHERE license_rule IS NULL AND parent_control_uuid IS NULL
GROUP BY 1, 2, 3 ORDER BY n DESC LIMIT 25;
"""
def print_bucket(rows, label: str) -> None:
print(f"\n## {label}")
total = 0
for bucket, n in rows:
print(f" {bucket:12} {n:>8}")
total += n
print(f" {'TOTAL':12} {total:>8}")
def main() -> int:
args = parse_args()
try:
import psycopg2
except ImportError:
print("error: psycopg2 not installed", file=sys.stderr)
return 2
conn = psycopg2.connect(
host=args.db_host, port=args.db_port, user=args.db_user,
dbname=args.db_name, password=args.db_password,
)
conn.autocommit = False
cur = conn.cursor()
print("=" * 60)
print(" Backfill — license_rule via parent inheritance")
print(f" Mode: {'DRY-RUN' if args.dry_run else 'APPLY'}")
print("=" * 60)
# Initial bucket report
cur.execute(SQL_REPORT_NULLS)
rows = cur.fetchall()
print_bucket(rows, "Initial NULL distribution")
if args.dry_run:
# Print what the FIRST inherit pass would resolve (without writing)
cur.execute(
"SET search_path TO compliance, public; "
"SELECT p.license_rule, COUNT(*) "
"FROM canonical_controls cc "
"JOIN canonical_controls p ON cc.parent_control_uuid = p.id "
"WHERE cc.license_rule IS NULL AND p.license_rule IS NOT NULL "
"GROUP BY 1 ORDER BY 1;"
)
print("\n## First inherit-pass would fill:")
for rule, n in cur.fetchall():
print(f" rule={rule} {n:>8} rows")
# Show orphan clusters that would remain
cur.execute(SQL_REPORT_ORPHAN_CLUSTERS)
print("\n## Orphan clusters (no parent + no rule, top 25):")
for cat, pid, gen, n in cur.fetchall():
print(f" cat={cat[:20]:20} pat={pid[:20]:20} gen={gen[:20]:20} n={n}")
print("\nNo writes performed. Use --apply to execute.")
conn.rollback()
return 0
# Apply mode — iterative inheritance
total_updated = 0
for i in range(1, args.max_iterations + 1):
cur.execute(SQL_INHERIT_FROM_PARENT)
updated = cur.rowcount
total_updated += updated
print(f"\n iteration {i}: {updated} rows updated")
if updated == 0:
break
conn.commit()
print(f"\n✓ Total rows backfilled: {total_updated}")
# Final bucket report
cur.execute(SQL_REPORT_NULLS)
print_bucket(cur.fetchall(), "Remaining NULL distribution")
cur.execute(SQL_REPORT_ORPHAN_CLUSTERS)
rows = cur.fetchall()
if rows:
print("\n## Orphan clusters still need classification:")
for cat, pid, gen, n in rows:
print(f" cat={cat[:20]:20} pat={pid[:20]:20} gen={gen[:20]:20} n={n}")
return 0
if __name__ == "__main__":
raise SystemExit(main())
@@ -0,0 +1,203 @@
#!/usr/bin/env python3
"""Backfill ``license_rule`` payload field into Qdrant atomic_controls_dedup
and related compliance collections, sourced from canonical_controls in Postgres.
The audit (audit_license_classification.py) surfaced that Qdrant collections
holding canonical-control vectors (notably ``atomic_controls_dedup``) carry no
license_rule payload at all, even though the underlying Postgres table is now
fully classified. This script joins the two via ``control_uuid`` and patches the
Qdrant payload in batches.
Usage::
python3 scripts/backfill_qdrant_license_payload.py \\
--pg-host 100.80.114.48 --pg-password breakpilot123 \\
--qdrant http://100.80.114.48:6333 \\
--collection atomic_controls_dedup \\
--dry-run
# apply
python3 scripts/backfill_qdrant_license_payload.py ... --apply
Notes
-----
- ``control_uuid`` lives in the payload of atomic_controls_dedup. For other
collections that key the canonical control by a different field, override with
``--uuid-field``.
- Qdrant ``set_payload`` is keyed by point id, not payload field. We resolve
UUID → point id by a paginated scroll-and-filter pass, then issue grouped
set_payload requests per license_rule (3 batches per collection).
"""
from __future__ import annotations
import argparse
import json
import sys
import time
from typing import Iterator
from urllib import request as urllib_request
def parse_args() -> argparse.Namespace:
p = argparse.ArgumentParser(description=__doc__)
p.add_argument("--pg-host", default="100.80.114.48")
p.add_argument("--pg-port", type=int, default=5432)
p.add_argument("--pg-user", default="breakpilot")
p.add_argument("--pg-name", default="breakpilot_db")
p.add_argument("--pg-password", required=True)
p.add_argument("--qdrant", default="http://100.80.114.48:6333")
p.add_argument("--qdrant-api-key", default="",
help="API key for managed Qdrant (Production)")
p.add_argument("--collection", default="atomic_controls_dedup")
p.add_argument("--uuid-field", default="control_uuid",
help="Payload field used for lookup (control_uuid or regulation_id)")
p.add_argument("--lookup", choices=["canonical_controls", "regulation_registry"],
default="canonical_controls",
help="Postgres table to resolve the lookup against")
p.add_argument("--batch-size", type=int, default=500)
g = p.add_mutually_exclusive_group(required=True)
g.add_argument("--dry-run", action="store_true")
g.add_argument("--apply", action="store_true")
return p.parse_args()
def fetch_rule_by_uuid(args) -> dict[str, int]:
"""Pull lookup-key → license_rule mapping from Postgres.
Source table is chosen by ``--lookup``:
- canonical_controls: id (UUID) → license_rule, for atomic_controls_dedup
- regulation_registry: regulation_id → license_rule, for document chunks
"""
import psycopg2
conn = psycopg2.connect(
host=args.pg_host, port=args.pg_port, user=args.pg_user,
dbname=args.pg_name, password=args.pg_password,
)
cur = conn.cursor()
cur.execute("SET search_path TO compliance, public;")
if args.lookup == "regulation_registry":
cur.execute(
"SELECT regulation_id, license_rule FROM regulation_registry "
"WHERE license_rule IS NOT NULL"
)
else:
cur.execute(
"SELECT id::text, license_rule FROM canonical_controls "
"WHERE license_rule IS NOT NULL"
)
mapping = {row[0]: int(row[1]) for row in cur.fetchall()}
conn.close()
return mapping
def _headers(api_key: str = "") -> dict:
h = {"Content-Type": "application/json"}
if api_key:
h["api-key"] = api_key
return h
def scroll_collection(qdrant: str, collection: str, uuid_field: str, api_key: str = "") -> Iterator[dict]:
"""Yield (point_id, uuid_value, has_rule_already) tuples."""
next_offset = None
while True:
body = {"limit": 1000, "with_payload": True, "with_vector": False}
if next_offset is not None:
body["offset"] = next_offset
req = urllib_request.Request(
f"{qdrant}/collections/{collection}/points/scroll",
data=json.dumps(body).encode(),
headers=_headers(api_key),
)
with urllib_request.urlopen(req, timeout=60) as r:
payload = json.loads(r.read())
result = payload.get("result", {})
for pt in result.get("points", []):
pl = pt.get("payload", {}) or {}
yield {
"id": pt["id"],
"uuid": pl.get(uuid_field),
"has_rule": "license_rule" in pl,
}
next_offset = result.get("next_page_offset")
if next_offset is None:
break
def set_payload_batch(qdrant: str, collection: str, point_ids: list, rule: int, api_key: str = "") -> int:
"""POST set_payload for a batch of point IDs with a single license_rule."""
body = {
"payload": {"license_rule": rule},
"points": point_ids,
}
req = urllib_request.Request(
f"{qdrant}/collections/{collection}/points/payload?wait=true",
data=json.dumps(body).encode(),
headers=_headers(api_key),
method="POST",
)
with urllib_request.urlopen(req, timeout=120) as r:
resp = json.loads(r.read())
if resp.get("status") != "ok":
raise RuntimeError(f"set_payload failed: {resp}")
return len(point_ids)
def main() -> int:
args = parse_args()
print("Loading canonical_controls → license_rule mapping…")
rule_by_uuid = fetch_rule_by_uuid(args)
print(f" Postgres returned {len(rule_by_uuid)} classified controls")
print(f"Scrolling Qdrant collection {args.collection!r}")
by_rule: dict[int, list] = {1: [], 2: [], 3: []}
points_total = 0
points_with_uuid = 0
points_already_set = 0
points_no_match = 0
for pt in scroll_collection(args.qdrant, args.collection, args.uuid_field, args.qdrant_api_key):
points_total += 1
uuid = pt["uuid"]
if not uuid:
continue
points_with_uuid += 1
if pt["has_rule"]:
points_already_set += 1
continue
rule = rule_by_uuid.get(uuid)
if rule is None:
points_no_match += 1
continue
if rule not in by_rule:
continue
by_rule[rule].append(pt["id"])
print(f" total points scanned: {points_total}")
print(f" with {args.uuid_field}: {points_with_uuid}")
print(f" already had license_rule: {points_already_set}")
print(f" uuid not found in Postgres: {points_no_match}")
print(f" to set per rule: rule1={len(by_rule[1])} rule2={len(by_rule[2])} rule3={len(by_rule[3])}")
if args.dry_run:
print("\nDRY-RUN: no writes performed. Use --apply to execute.")
return 0
total_written = 0
for rule, ids in by_rule.items():
if not ids:
continue
print(f"\nWriting license_rule={rule} to {len(ids)} points (batch {args.batch_size})…")
for i in range(0, len(ids), args.batch_size):
chunk = ids[i:i + args.batch_size]
n = set_payload_batch(args.qdrant, args.collection, chunk, rule, args.qdrant_api_key)
total_written += n
print(f" batch {i // args.batch_size + 1}: {n} points (cumulative {total_written})")
time.sleep(0.05)
print(f"\nWrote license_rule on {total_written} Qdrant points in {args.collection}")
return 0
if __name__ == "__main__":
raise SystemExit(main())
+21
View File
@@ -34,6 +34,27 @@ export default function ImpressumPage() {
Unsere E-Mail-Adresse finden Sie oben im Impressum.
</p>
</div>
<div>
<h2 className="text-lg font-semibold text-white mb-2">Quellen und Lizenzen der Compliance-Inhalte</h2>
<p>
Die BreakPilot Compliance-Plattform stuetzt sich auf rund 315.000 klassifizierte
Controls aus oeffentlichen Quellen: EU-Recht (EUR-Lex), deutsches und oesterreichisches
Bundesrecht, US Federal Code (OSHA, NIST), Behoerden-Leitfaeden (ENISA, EDPB, BAuA),
freie Sicherheits-Frameworks unter CC-BY-SA (OWASP-Familie, OECD AI Principles) und
eigene Texte. Jeder Control traegt eine deterministische Lizenzregel (R1 woertlich, R2
mit Attribution, R3 nur Identifier-Verweis), die das Render-Verhalten in Berichten,
PDF-Exports und Frontend steuert. Die vollstaendige Quellenliste mit Aufschluesselung
pro Lizenzklasse ist im SDK unter <code className="text-white/80">/sdk/licenses</code>
eingesehen. Pflicht-Attributionen fuer R2-Quellen erscheinen automatisch im
Quellen-Footer jedes generierten Berichts.
</p>
<p className="mt-2 text-xs">
Hinweis: Dieser Pauschalvermerk ersetzt nicht die werknahe Attribution. Jede
Berichts- oder Frontend-Ausgabe nennt die konkret verwendeten Quellen direkt am
Werk (Auto-Footer in PDFs, Inline-Citation im Frontend).
</p>
</div>
</div>
</div>
</div>
+177
View File
@@ -0,0 +1,177 @@
import Navbar from '@/components/layout/Navbar'
import Footer from '@/components/layout/Footer'
import ChatFAB from '@/components/layout/ChatFAB'
// Stärken / USP-Seite — sieben Verkaufsargumente aus der IACE-Strategie
// (Memory: project_marketing_website_3014_themes.md). Aufgebaut als
// Long-Form-Page mit Anker-Sprungmarken — eine Nummerierte Differenzierung
// pro Sektion, damit Sales-Calls über tiefe Links arbeiten können.
const usps = [
{
id: 'engine',
no: '1',
title: 'Engine, nicht Checkliste',
sub: 'Wir leiten Gefährdungen ab. Wettbewerb fragt aus einer Liste.',
body:
'Marktstandard (DesignSafe, Pilz, Sick) ist Excel-aufgewertete Checkliste: der Engineer wählt aus einer Hazard-Bibliothek aus. ' +
'BreakPilot betreibt eine deterministische Pattern-Engine mit über 1.200 Hazard-Patterns. Aus der Maschinenbeschreibung leitet sie ' +
'die Gefährdungen ab — keine Auswahllisten, keine vergessenen Punkte.',
proof: 'Audit-Suite cmd/iace-audit erkennt eigene Lücken (Methode AE)',
},
{
id: 'multi-markt',
no: '2',
title: 'Eine Risikobeurteilung — alle Märkte',
sub: 'CE + OSHA + ANSI + GB + JIS aus einem Datenmodell.',
body:
'Die gleiche Pattern-Engine generiert pro Maschinenbeschreibung mehrere Compliance-Anhänge. Hersteller wählt seine Zielmärkte. ' +
'EU-Recht zitieren wir wörtlich (Rule 1). OWASP unter CC-BY-SA mit Pflicht-Attribution (Rule 2). DIN/EN nur per Identifier (Rule 3). ' +
'Norm-Cross-Reference-Bibliothek mappt ISO 12100 ↔ DIN EN ISO 12100 ↔ ANSI B11.0 ↔ GB/T 15706 ↔ JIS B 9700.',
proof: '252 Regulationen klassifiziert · 314.811 Controls audited',
},
{
id: 'folgegefahren',
no: '3',
title: 'Vom Bediener bis zum Endkunden',
sub: 'Folgegefahren-Modell mit Sekundärschadens-Kette.',
body:
'Klassische Risikobeurteilung schaut nur den Bediener an. Wir modellieren die Schadenskette weiter: Glasbruch in der Abfüllanlage ' +
'verletzt nicht nur den Bediener, sondern erreicht über Restsplitter den Endkunden. BreakPilot verbindet CE-Sicherheit mit ' +
'Produkthaftung nach ProdHaftG, Lebensmittelrecht nach VO 178/2002 und ISO 31000 Unternehmensrisiko in einem Datenmodell.',
proof: 'SecondaryHarm-Modell live für consumer_safety, product_liability, food_safety, environmental, reputation, financial',
},
{
id: 'public-domain',
no: '4',
title: 'Public Domain als Rechtsanker',
sub: 'Werte aus OSHA, NIST, EUR-Lex, BAuA — auditfähig zitiert.',
body:
'Mindestabstände der Maschinensicherheit kommen bei uns aus OSHA 29 CFR 1910 Subpart O — US Federal Public Domain, lizenzrechtlich ' +
'unbedenklich. Engineering-Rundung auf safe-side mm-Raster wird transparent dokumentiert. EU-Normen erscheinen nur als Identifier-Verweis ' +
'mit einer menschlich kuratierten "Strenger/Gleich/Weicher"-Annotation — kein Copyright-Risiko.',
proof: 'OSHA Table O-10 + §1910.217 PSDI-Formel verbatim · DIN nur Identifier · 6 DGUV-Publikationen referenziert',
},
{
id: 'audit-suite',
no: '5',
title: 'Audit findet Lücken, die der Fachmann übersieht',
sub: 'Fünf deterministische Audits ohne Ground Truth.',
body:
'Unsere Engine kennt ihre eigenen Lücken. Methode A bis E (Reachability, Consistency, Vocabulary, Echo, Hierarchy) finden Gaps ' +
'ohne Fachmann-Vergleich. Bei einem Test fanden wir 100 strukturell unerreichbare Patterns und 46 unvollständige Component-Tags — ' +
'Probleme, die ein menschlicher Auditor in einem Einzelfall nie gesehen hätte.',
proof: 'cmd/iace-audit · 1.213 Patterns transparent · 99,94% Recall verifiziert',
},
{
id: 'made-in-germany',
no: '6',
title: 'Made in Germany meets US Federal Public Domain',
sub: 'Deutscher Maschinenbau, der gleichzeitig US-Compliance liefert.',
body:
'Deutscher Exportweltmeister-Maschinenbau braucht UL/NRTL-Zulassung für die USA. Die gleichen Daten, die wir für CE generieren, ' +
'liefern dem US-Auditor 80 % der Vorarbeit. Risikobeurteilung in einer Sprache, Compliance in zwei Märkten — ohne Mehraufwand für den Hersteller.',
proof: 'OSHA-Anker im RAG · NRTL-fähige Compliance-Spur · DesignSafe-Marktstandard wird hier erweitert, nicht imitiert',
},
{
id: 'tooling',
no: '7',
title: 'LLM-Gap-Review als Co-Pilot, nicht als Roboter-Anwalt',
sub: 'Pattern-Engine als Audit-Spur, LLM als Lücken-Suchhund.',
body:
'Die deterministische Engine bleibt die auditfähige Quelle der Wahrheit. Ein nachgelagerter LLM-Gap-Review (Qwen / Claude) prüft, ' +
'was die Engine übersehen hat — mit klarer Quellen-Provenance (R3 LLM-Review) und Adopt/Reject-UX. Halluzinationen können nicht in ' +
'die finale Risikobeurteilung schlüpfen.',
proof: 'POST /projects/:id/llm-gap-review · Konfidenz-Stufen · Fallback auf statische Checkliste',
},
] as const
const competitors = [
{ feature: 'Pattern-Engine statt Checkliste', bp: '✓', ds: '—', pilz: '—', sick: '—', sphera: '—' },
{ feature: 'Multi-Markt CE / US / CN / JP', bp: '✓', ds: 'nur US', pilz: 'nur EU', sick: 'nur EU', sphera: 'enterprise' },
{ feature: 'Folgegefahren-Modell', bp: '✓', ds: '—', pilz: '—', sick: '—', sphera: 'Process' },
{ feature: 'Audit-Suite (Engine-Lücken-Erkennung)', bp: '✓', ds: '—', pilz: '—', sick: '—', sphera: '—' },
{ feature: 'OSHA-Anker (Public Domain Werte)', bp: '✓', ds: '✓', pilz: '—', sick: '—', sphera: '—' },
{ feature: 'LLM-Gap-Review (Co-Pilot)', bp: '✓', ds: '—', pilz: '—', sick: '—', sphera: '—' },
]
export default function StaerkenPage() {
return (
<>
<Navbar />
<main className="bg-enterprise-dark text-white pt-32 pb-24">
<div className="max-w-5xl mx-auto px-4">
<header className="mb-16">
<h1 className="text-5xl font-bold mb-4">Was uns differenziert</h1>
<p className="text-white/60 text-lg max-w-3xl">
Sieben konkrete Punkte, die BreakPilot von DesignSafe, Pilz, Sick, TÜV-Tools und Sphera trennen.
Jede Differenzierung ist im Produkt umgesetzt kein Marketing-Versprechen.
</p>
</header>
<ol className="space-y-12">
{usps.map((u) => (
<li id={u.id} key={u.id} className="border-l-2 border-accent-electric pl-6">
<div className="flex items-baseline gap-3 mb-2">
<span className="text-accent-electric font-mono text-3xl font-bold">#{u.no}</span>
<h2 className="text-2xl font-semibold">{u.title}</h2>
</div>
<p className="text-accent-electric/80 text-sm mb-3">{u.sub}</p>
<p className="text-white/70 leading-relaxed mb-3">{u.body}</p>
<p className="text-white/40 text-xs">
<span className="text-white/60">Belegt durch:</span> {u.proof}
</p>
</li>
))}
</ol>
<section className="mt-20">
<h2 className="text-3xl font-bold mb-4">Direktvergleich</h2>
<p className="text-white/60 mb-6 max-w-3xl">
Stand 2026. Marktangaben basieren auf öffentlicher Produktinformation der genannten Anbieter.
</p>
<div className="overflow-x-auto border border-white/10 rounded-lg">
<table className="w-full text-sm">
<thead className="bg-white/[0.04] border-b border-white/10">
<tr>
<th className="text-left p-3 font-medium">Feature</th>
<th className="text-left p-3 font-medium text-accent-electric">BreakPilot</th>
<th className="text-left p-3 font-medium text-white/60">DesignSafe</th>
<th className="text-left p-3 font-medium text-white/60">Pilz PASS</th>
<th className="text-left p-3 font-medium text-white/60">Sick SD</th>
<th className="text-left p-3 font-medium text-white/60">Sphera</th>
</tr>
</thead>
<tbody>
{competitors.map((c) => (
<tr key={c.feature} className="border-t border-white/[0.06]">
<td className="p-3 text-white/80">{c.feature}</td>
<td className="p-3 text-accent-electric font-medium">{c.bp}</td>
<td className="p-3 text-white/50">{c.ds}</td>
<td className="p-3 text-white/50">{c.pilz}</td>
<td className="p-3 text-white/50">{c.sick}</td>
<td className="p-3 text-white/50">{c.sphera}</td>
</tr>
))}
</tbody>
</table>
</div>
</section>
<section className="mt-20 border-t border-white/10 pt-12">
<h2 className="text-2xl font-bold mb-3">Quellen &amp; Lizenz-Architektur</h2>
<p className="text-white/60 leading-relaxed">
Die Plattform stützt sich auf öffentliche Quellen: EU-Recht (EUR-Lex), Bundesrecht (BetrSichV, ArbSchG),
US Federal Code (OSHA, NIST), Behörden-Leitfäden (ENISA, EDPB, BAuA), freie Sicherheits-Frameworks unter
CC-BY-SA (OWASP). Jeder Inhalt trägt eine deterministische Lizenzregel R1/R2/R3 und löst die
entsprechende Attribution im Ausgabe-PDF und im Frontend automatisch aus. Vollständige Quellenliste
im SDK unter <code className="bg-white/[0.06] px-1.5 py-0.5 rounded">/sdk/licenses</code>.
</p>
</section>
</div>
</main>
<Footer />
<ChatFAB />
</>
)
}
+1
View File
@@ -1,6 +1,7 @@
// Navbar links — route-based navigation
export const navLinks = [
{ href: '/plattform', labelDe: 'Plattform', labelEn: 'Platform' },
{ href: '/staerken', labelDe: 'Stärken', labelEn: 'Differentiators' },
{ href: '/ce-prozess', labelDe: 'CE-Prozess', labelEn: 'CE Process' },
{ href: '/product-compliance', labelDe: 'Product Compliance', labelEn: 'Product Compliance' },
{ href: '/architektur', labelDe: 'Architektur', labelEn: 'Architecture' },