Compare commits

...

3 Commits

Author SHA1 Message Date
Benjamin Admin 2b1fe3713a feat(dsms): tech-file DSMS archive now logs CID into IACE audit trail
Before: archiveTechFile called dsms.Archive() and discarded the result. The
file was archived to IPFS but no audit-trail entry was written, so there
was no way to later prove "this CE-Akte export went to DSMS with CID X".

After:
- archiveTechFile is now a method on IACEHandler with access to store + gin
  context, and captures the CID from dsms.Archive().
- Writes an AuditAction "tech_file_export" audit entry whose new_values
  JSON carries {cid, filename, size}, mirroring the Python evidence-upload
  pattern.
- Applies to PDF, XLSX, DOCX, and Markdown exports.

Plus dsms package gets 3 unit tests pinning the contract: success-CID
extraction, gateway-unreachable returns nil, 500-response returns nil.

This closes DSMS Stufe 2 (evidence side was already wired; tech-file side
was missing the audit hook). Stufe 3 next: version chains + delta view.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-22 10:02:18 +02:00
Benjamin Admin e2be51b0aa feat(audit): P106 MC-Audit-Type + P83 BUILD_SHA in Dockerfiles + P80 v2 full
CI / secret-scan (push) Has been skipped
CI / dep-audit (push) Has been skipped
CI / sbom-scan (push) Has been skipped
CI / validate-canonical-controls (push) Successful in 16s
CI / detect-changes (push) Successful in 11s
CI / branch-name (push) Has been skipped
CI / guardrail-integrity (push) Has been skipped
CI / loc-budget (push) Failing after 16s
CI / go-lint (push) Has been skipped
CI / python-lint (push) Has been skipped
CI / nodejs-lint (push) Has been skipped
CI / nodejs-build (push) Successful in 2m42s
CI / test-go (push) Has been skipped
CI / iace-gt-coverage (push) Has been skipped
CI / test-python-backend (push) Successful in 41s
CI / test-python-document-crawler (push) Has been skipped
CI / test-python-dsms-gateway (push) Has been skipped
P106 — mc_audit_type.py: zentrales Quality-Thema.
Klassifiziert pro MC: verifiable / process_internal / doc_internal /
ambiguous. Pattern-Match auf check_question + title + fail_criteria
(Schulung, AVV abgeschlossen, TOM umgesetzt, DSFA durchgefuehrt,
Ausnahmen dokumentieren, kostenfrei zur Verfuegung, opt-out
intern ermoeglichen, …).

Interne MCs werden in der MC-Auswertung NICHT mehr als FAIL gewertet,
sondern als CHECK markiert (audit_status='check'). Sie zaehlen im
build_scorecard als skipped (nicht failed) damit der Score realistisch
ist. build_internal_checks_block_html() rendert sie als separaten
blauen Block 'Pruefungen die wir von aussen NICHT durchfuehren koennen'
nach dem MC-Scorecard.

Erwartete Wirkung: bei VW 95 FAILs → wahrscheinlich 30-40 echte
verifiable_fails + 50-60 internal_checks. GF-Mail wird drastisch
realistischer (statt 'Sie haben 95 Verstoesse' → 'Sie haben 35
extern sichtbare Themen + 60 interne Checks, bitte mit DSB klaeren').

P83 — BUILD_SHA in backend/admin/consent-tester Dockerfiles als
ARG + ENV. check-rebuild-needed.sh kann jetzt deployed vs local SHA
vergleichen + REBUILD REQUIRED melden.

P80 v2 — check_replay.py macht jetzt vollstaendigen Replay aller
post-fetch Quality-Generatoren: vendor_normalizer (Dedup),
audit_quality_checks, cookie_compliance_audit, tcf_vendor_authority,
cookie_value_entropy, cookie_network_tracer. Snapshots aus alter Zeit
zeigen jetzt im Replay den aktuellen Audit-Stand.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-22 08:57:02 +02:00
Benjamin Admin bd65b6f318 feat(audit): Phase 2+3 — P54 + P68 + P69 + P6/P53/P55 + P31 + P80v2
CI / guardrail-integrity (push) Has been skipped
CI / secret-scan (push) Has been skipped
CI / dep-audit (push) Has been skipped
CI / sbom-scan (push) Has been skipped
CI / go-lint (push) Has been skipped
CI / python-lint (push) Has been skipped
CI / nodejs-lint (push) Has been skipped
CI / nodejs-build (push) Has been skipped
CI / test-go (push) Failing after 59s
CI / detect-changes (push) Successful in 10s
CI / branch-name (push) Has been skipped
CI / validate-canonical-controls (push) Successful in 15s
CI / loc-budget (push) Failing after 19s
CI / iace-gt-coverage (push) Successful in 27s
CI / test-python-backend (push) Successful in 42s
CI / test-python-document-crawler (push) Has been skipped
CI / test-python-dsms-gateway (push) Has been skipped
P54 — consent_diff_for_user.py: USP-Feature fuer wiederkehrende Besucher.
compute_user_facing_diff() vergleicht aktuellen Snapshot mit letztem fuer
gleiche site_domain → added_vendors / removed_vendors / requires_reconsent
wenn neue Marketing-Vendors hinzugekommen. build_diff_banner_snippet()
liefert HTML zum Einbau in eigenen Banner via consent-sdk.

P68 — reverse_audit.py: Self-Audit unserer Template-Bibliothek.
run_reverse_audit() laedt alle MCs aus doc_check_controls + alle Templates
aus doc_templates, prueft per pass_criteria-Match welche MCs durch
mindestens 1 Template abgedeckt sind. Liefert coverage_pct, uncovered_mcs
(Top HIGH zuerst), unused_templates, by_doctype-Breakdown.

P69 — data/ecall_regulation.json: eCall-VO (EU) 2015/758 als 7 Chunks
fuer RAG-Ingest (Art. 3/6/7 + compliance_implications fuer Automotive-OEMs).
Standortdaten ausserhalb Notfall = unzulaessig; Mehrwertdienste brauchen
separate Einwilligung; Daten sofort loeschen nach Notruf.

P6+P53+P55 — industry_library.py: Branchen-Profile (automotive/ecommerce/
saas/banking/healthcare) mit mandatory_regulations + typical_cookie_vendors
+ vvt_required_processes + special_findings_to_watch. load_site_profile()
liest Site-Historie aus snapshots (common_provider, avg_vendors,
historical_runs). build_industry_context_block_html() rendert Block am
Mail-Anfang: 'Was wir in dieser Branche bei VW pruefen' + 'Wir haben
diese Site bereits 3× analysiert'.

P31 — llm_cascade.py: Tiered LLM-Cascade Qwen → OVH 120B → Anthropic
Claude Haiku mit Confidence-Heuristik (JSON parsed, items count vs
input size). Valkey-Cache (redis://) mit 7-Tage-TTL plus In-Process-
Fallback. Wenn Tier-1 unter Confidence-Threshold → Tier-2, dann Tier-3.
Reduziert Lauf-Zeit drastisch bei Re-Runs.

P80 v2 — check_replay.py: replay nutzt jetzt audit_quality_checks
mit den Snapshot-Daten. Auch alte Snapshots zeigen jetzt im Replay
ob banner_detected fehlt / vendor_extract thin ist.

Bonus — P90 BMW-Final markiert completed: alle B1-B4 Bugs gefixt
(cmp_payloads keep, cookies_detailed wiring, multi-doc-fail visibility,
VVT-Tabelle).

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-22 08:38:08 +02:00
14 changed files with 1318 additions and 8 deletions
+4
View File
@@ -55,5 +55,9 @@ EXPOSE 3000
# Set hostname
ENV HOSTNAME="0.0.0.0"
# P83 — Build-SHA fuer check-rebuild-needed.sh
ARG BUILD_SHA="unknown"
ENV BUILD_SHA=${BUILD_SHA}
# Start the application
CMD ["node", "server.js"]
@@ -1,6 +1,7 @@
package handlers
import (
"encoding/json"
"fmt"
"net/http"
"strings"
@@ -412,7 +413,7 @@ func (h *IACEHandler) ExportTechFile(c *gin.Context) {
c.JSON(http.StatusInternalServerError, gin.H{"error": fmt.Sprintf("PDF export failed: %v", err)})
return
}
archiveTechFile(data, fmt.Sprintf("CE-Akte-%s.pdf", safeName), projectID.String())
h.archiveTechFile(c, data, fmt.Sprintf("CE-Akte-%s.pdf", safeName), projectID)
c.Header("Content-Disposition", fmt.Sprintf(`attachment; filename="CE-Akte-%s.pdf"`, safeName))
c.Data(http.StatusOK, "application/pdf", data)
@@ -422,7 +423,7 @@ func (h *IACEHandler) ExportTechFile(c *gin.Context) {
c.JSON(http.StatusInternalServerError, gin.H{"error": fmt.Sprintf("Excel export failed: %v", err)})
return
}
archiveTechFile(data, fmt.Sprintf("CE-Akte-%s.xlsx", safeName), projectID.String())
h.archiveTechFile(c, data, fmt.Sprintf("CE-Akte-%s.xlsx", safeName), projectID)
c.Header("Content-Disposition", fmt.Sprintf(`attachment; filename="CE-Akte-%s.xlsx"`, safeName))
c.Data(http.StatusOK, "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet", data)
@@ -432,7 +433,7 @@ func (h *IACEHandler) ExportTechFile(c *gin.Context) {
c.JSON(http.StatusInternalServerError, gin.H{"error": fmt.Sprintf("DOCX export failed: %v", err)})
return
}
archiveTechFile(data, fmt.Sprintf("CE-Akte-%s.docx", safeName), projectID.String())
h.archiveTechFile(c, data, fmt.Sprintf("CE-Akte-%s.docx", safeName), projectID)
c.Header("Content-Disposition", fmt.Sprintf(`attachment; filename="CE-Akte-%s.docx"`, safeName))
c.Data(http.StatusOK, "application/vnd.openxmlformats-officedocument.wordprocessingml.document", data)
@@ -442,7 +443,7 @@ func (h *IACEHandler) ExportTechFile(c *gin.Context) {
c.JSON(http.StatusInternalServerError, gin.H{"error": fmt.Sprintf("Markdown export failed: %v", err)})
return
}
archiveTechFile(data, fmt.Sprintf("CE-Akte-%s.md", safeName), projectID.String())
h.archiveTechFile(c, data, fmt.Sprintf("CE-Akte-%s.md", safeName), projectID)
c.Header("Content-Disposition", fmt.Sprintf(`attachment; filename="CE-Akte-%s.md"`, safeName))
c.Data(http.StatusOK, "text/markdown", data)
@@ -468,7 +469,30 @@ func (h *IACEHandler) ExportTechFile(c *gin.Context) {
}
}
// archiveTechFile stores a tech-file export to DSMS (best-effort, non-blocking).
func archiveTechFile(data []byte, filename, projectID string) {
dsms.Archive(data, filename, "ce_techfile", projectID, "1")
// archiveTechFile stores a tech-file export to DSMS (best-effort, non-blocking)
// AND records the resulting CID in the IACE audit trail so the export is
// traceable. The "new_values" JSON carries the CID + filename so the audit
// timeline can later resolve the CID against the DSMS gateway for verify.
func (h *IACEHandler) archiveTechFile(c *gin.Context, data []byte, filename string, projectID uuid.UUID) {
result := dsms.Archive(data, filename, "ce_techfile", projectID.String(), "1")
if result == nil || result.CID == "" {
return
}
payload := map[string]string{
"cid": result.CID,
"filename": filename,
"size": fmt.Sprintf("%d", result.Size),
}
newValues, _ := json.Marshal(payload)
userID := rbac.GetUserID(c)
_ = h.store.AddAuditEntry(
c.Request.Context(),
projectID,
"tech_file_export",
projectID,
iace.AuditActionCreate,
userID.String(),
nil,
newValues,
)
}
@@ -0,0 +1,74 @@
package dsms
import (
"encoding/json"
"io"
"net/http"
"net/http/httptest"
"strings"
"testing"
)
func TestArchive_Success_ReturnsCID(t *testing.T) {
server := httptest.NewServer(http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) {
if r.Method != "POST" || r.URL.Path != "/api/v1/documents" {
http.Error(w, "wrong route", http.StatusNotFound)
return
}
if !strings.HasPrefix(r.Header.Get("Content-Type"), "multipart/form-data") {
http.Error(w, "wrong content-type", http.StatusBadRequest)
return
}
if r.Header.Get("Authorization") == "" {
http.Error(w, "missing auth", http.StatusUnauthorized)
return
}
io.ReadAll(r.Body)
w.Header().Set("Content-Type", "application/json")
_ = json.NewEncoder(w).Encode(ArchiveResult{
CID: "bafytest123",
Size: 42,
GatewayURL: "/ipfs/bafytest123",
})
}))
defer server.Close()
old := gatewayURL
defer func() { gatewayURL = old }()
gatewayURL = server.URL
got := Archive([]byte("hello"), "test.pdf", "ce_techfile", "proj-1", "1")
if got == nil {
t.Fatal("expected non-nil result on 200 OK")
}
if got.CID != "bafytest123" {
t.Errorf("expected CID bafytest123, got %q", got.CID)
}
if got.Size != 42 {
t.Errorf("expected Size 42, got %d", got.Size)
}
}
func TestArchive_GatewayDown_ReturnsNil(t *testing.T) {
old := gatewayURL
defer func() { gatewayURL = old }()
gatewayURL = "http://127.0.0.1:1" // unreachable
got := Archive([]byte("hello"), "test.pdf", "ce_techfile", "proj-1", "1")
if got != nil {
t.Errorf("expected nil when gateway unreachable, got %+v", got)
}
}
func TestArchive_GatewayReturnsError_ReturnsNil(t *testing.T) {
server := httptest.NewServer(http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) {
http.Error(w, "internal error", http.StatusInternalServerError)
}))
defer server.Close()
old := gatewayURL
defer func() { gatewayURL = old }()
gatewayURL = server.URL
got := Archive([]byte("hello"), "test.pdf", "ce_techfile", "proj-1", "1")
if got != nil {
t.Errorf("expected nil on 500 response, got %+v", got)
}
}
+4
View File
@@ -60,5 +60,9 @@ EXPOSE 8002
HEALTHCHECK --interval=30s --timeout=3s --start-period=5s --retries=3 \
CMD curl -f http://127.0.0.1:8002/health || exit 1
# P83 — Build-SHA fuer check-rebuild-needed.sh
ARG BUILD_SHA="unknown"
ENV BUILD_SHA=${BUILD_SHA}
# Run the application
CMD ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "8002"]
@@ -1184,6 +1184,22 @@ async def _run_compliance_check(check_id: str, req: ComplianceCheckRequest):
if (not c.passed and not c.skipped
and (c.severity or "").upper() in ("CRITICAL", "HIGH")):
fails_by_doc.setdefault(r.doc_type, []).append(rec)
# P106 — Audit-Type-Klassifizierung pro MC. Interne Prozess-/
# Doku-Checks werden NICHT als FAIL gewertet sondern als CHECK
# (manuelle Pruefung beim DSB notwendig).
try:
from compliance.services.mc_audit_type import (
annotate_mc_results, split_by_audit_type,
)
annotate_mc_results(all_mc_checks)
mc_split = split_by_audit_type(all_mc_checks)
# Fails-by-doc neu aufbauen: nur noch echte verifiable Fails
fails_by_doc = {}
for r in mc_split.get("verifiable_fails") or []:
fails_by_doc.setdefault("dse", []).append(r)
except Exception as e:
logger.warning("P106 mc_audit_type skipped: %s", e)
mc_split = {"internal_checks": [], "verifiable_fails": all_mc_checks}
scorecard = build_scorecard(all_mc_checks) if all_mc_checks else {}
# Trend: load previous scorecard for the same tenant + domain so the
# email can show delta indicators (A6).
@@ -1486,6 +1502,39 @@ async def _run_compliance_check(check_id: str, req: ComplianceCheckRequest):
except Exception as e:
logger.warning("P71 jc_avv_decision skipped: %s", e)
# P6/P53/P55 — Branchen-Kontext + Site-History
industry_ctx_html = ""
try:
from compliance.services.industry_library import (
build_industry_context_block_html, load_site_profile,
)
from database import SessionLocal as _SLib
_ind_db = _SLib()
try:
ind = (req.scan_context or {}).get("industry") if req.scan_context else None
site_prof = load_site_profile(_ind_db, domain_for_exec or "")
industry_ctx_html = build_industry_context_block_html(ind, site_prof)
finally:
_ind_db.close()
except Exception as e:
logger.warning("industry context skipped: %s", e)
# P106 — Internal-Checks-Block (interne Prozesse / Doku-Pflichten)
internal_checks_html = ""
try:
from compliance.services.mc_audit_type import (
build_internal_checks_block_html,
)
ic = (mc_split or {}).get("internal_checks") or []
if ic:
internal_checks_html = build_internal_checks_block_html(ic)
logger.info(
"P106: %d interne Checks (statt FAIL) im Block",
len(ic),
)
except Exception as e:
logger.warning("P106 internal_checks_html skipped: %s", e)
# P85 — Banner-Screenshot fuer visuellen Beweis (zwischen
# GF-1-Pager und Detail-Bloecken)
banner_shot_html = ""
@@ -1595,7 +1644,8 @@ async def _run_compliance_check(check_id: str, req: ComplianceCheckRequest):
+ bench_html + diff_html
+ critical_html + scope_disclaimer_html + exec_summary_html
+ cookie_arch_html + summary_html + scanned_html + profile_html
+ scorecard_html + redundancy_html
+ scorecard_html + internal_checks_html + redundancy_html
+ industry_ctx_html
+ banner_shot_html
+ providers_html + banner_deep_html
+ cookie_audit_html
@@ -0,0 +1,50 @@
{
"source": "Verordnung (EU) 2015/758 - eCall",
"official_url": "https://eur-lex.europa.eu/legal-content/DE/TXT/?uri=CELEX%3A32015R0758",
"ingest_for": "RAG-Korpus (Compliance fuer Automotive-OEMs)",
"chunks": [
{
"id": "ecall-art-3-1",
"title": "Art. 3 (1) — bordeigenes eCall-System",
"text": "Hersteller stellen sicher, dass alle neuen Typen von Personenkraftwagen und leichten Nutzfahrzeugen mit einem auf 112 basierten bordeigenen eCall-System ausgestattet sind, das den in dieser Verordnung festgelegten Anforderungen und harmonisierten Normen entspricht."
},
{
"id": "ecall-art-6-1",
"title": "Art. 6 (1) — Datenschutz",
"text": "Bei der Verarbeitung personenbezogener Daten ueber das auf 112 basierte bordeigene eCall-System gewaehrleisten Hersteller die Einhaltung der Richtlinie 95/46/EG und der RL 2002/58/EG. Insbesondere muessen Fahrzeughalter darueber informiert werden, dass das System dauerhaft im Standby-Modus ist und im Falle eines schweren Unfalls automatisch ausgeloest wird."
},
{
"id": "ecall-art-6-2",
"title": "Art. 6 (2) — Datenverarbeitung",
"text": "Die Verarbeitung personenbezogener Daten ueber das auf 112 basierte bordeigene eCall-System darf nur zum Zwecke der Bearbeitung von Notrufen erfolgen. Diese Daten sind unmittelbar nach Bearbeitung des Notrufs ohne automatisierte Speicherung zu loeschen, soweit nicht anders gesetzlich vorgesehen."
},
{
"id": "ecall-art-6-3",
"title": "Art. 6 (3) — Standortdaten",
"text": "Die Standortdaten des Fahrzeugs werden zur Behandlung des Notrufes uebermittelt. Eine permanente Standortueberwachung ausserhalb von Notfaellen ist nicht zulaessig."
},
{
"id": "ecall-art-6-4",
"title": "Art. 6 (4) — Informationspflicht",
"text": "Hersteller stellen sicher, dass in der technischen Dokumentation des Fahrzeugs klare und vollstaendige Informationen ueber die Verarbeitung personenbezogener Daten gegeben werden, einschliesslich des Rechts der betroffenen Person auf Auskunft und gegebenenfalls Berichtigung sowie Sperrung der sie betreffenden personenbezogenen Daten."
},
{
"id": "ecall-art-6-5",
"title": "Art. 6 (5) — Mehrwertdienste",
"text": "Mehrwertdienste (z.B. private Pannenruf-Apps) duerfen nur mit ausdruecklicher Einwilligung des Fahrzeughalters in Anspruch genommen werden. Das auf 112 basierte bordeigene eCall-System darf nicht von diesen Mehrwertdiensten beeintraechtigt werden und muss kostenlos und fuer alle Fahrzeughalter verfuegbar sein."
},
{
"id": "ecall-art-7",
"title": "Art. 7 — Datenfluss",
"text": "Der Mindestdatensatz (MSD) umfasst Fahrzeug-ID (VIN), Ausloesungsart, Zeitstempel, Standort, Fahrtrichtung, Antriebsenergie, Anzahl angeschnallter Insassen. Diese Daten gehen an die naechste oeffentliche Notrufabfragestelle (PSAP)."
}
],
"compliance_implications": {
"automotive_oem": [
"Hersteller MUSS in der DSE den eCall-Datenfluss erklaeren (Art. 6 (4)).",
"Standortdaten ausserhalb von Notfaellen sind UNZULAESSIG (Art. 6 (3)).",
"Mehrwertdienste brauchen separate ausdrueckliche Einwilligung (Art. 6 (5)).",
"Daten nach Notruf-Bearbeitung SOFORT zu loeschen (Art. 6 (2))."
]
}
}
@@ -85,6 +85,82 @@ def replay_from_snapshot(
section_sizes: dict[str, int] = {}
parts: list[str] = []
# P80 v2 — Quality-Checks aus dem aktuellen Code auf Snapshot-Daten
# anwenden. Vollstaendiger Replay aller post-fetch Findings-Generatoren.
cookie_t = doc_texts.get("cookie") or doc_texts.get("dse") or ""
# Vendor-Normalize (Dedup + Garbage-Filter)
try:
from compliance.services.vendor_normalizer import normalize_vendors
cmp_vendors = normalize_vendors(list(cmp_vendors))
except Exception as e:
logger.warning("Replay v2: normalizer failed: %s", e)
# Audit-Quality
try:
from compliance.services.audit_quality_checks import (
run_all as run_aq, build_audit_quality_block_html,
)
aq = run_aq(banner_result, cookie_t, cmp_vendors, doc_entries)
if aq:
aq_html = build_audit_quality_block_html(aq)
parts.append(aq_html)
section_sizes["audit_quality_v2"] = len(aq_html)
except Exception as e:
logger.warning("Replay v2: audit_quality failed: %s", e)
# Cookie-Compliance-Audit
try:
from compliance.services.cookie_compliance_audit import (
audit_cookie_compliance, build_cookie_audit_block_html,
)
ca = audit_cookie_compliance(db, cookie_t, banner_result)
if ca and (ca.get("declared_count") or ca.get("browser_count")):
ca_html = build_cookie_audit_block_html(ca)
parts.append(ca_html)
section_sizes["cookie_audit_v2"] = len(ca_html)
except Exception as e:
logger.warning("Replay v2: cookie_audit failed: %s", e)
# TCF Authority
try:
from compliance.services.tcf_vendor_authority import (
cross_reference_with_tcf, build_tcf_authority_block_html,
)
tcf = cross_reference_with_tcf(db, cmp_vendors)
if tcf:
tcf_html = build_tcf_authority_block_html(tcf)
parts.append(tcf_html)
section_sizes["tcf_v2"] = len(tcf_html)
except Exception as e:
logger.warning("Replay v2: tcf failed: %s", e)
# Entropy + Network-Trace
try:
from compliance.services.cookie_value_entropy import (
check_cookies_for_entropy_mismatch, build_entropy_block_html,
)
from compliance.services.cookie_network_tracer import (
trace_cookie_network, build_network_trace_block_html,
)
cd = (banner_result or {}).get("cookies_detailed") or []
e1 = check_cookies_for_entropy_mismatch(cd)
if e1:
ent_html = build_entropy_block_html(e1)
parts.append(ent_html)
section_sizes["entropy_v2"] = len(ent_html)
site_url = ""
for entry in (doc_entries or []):
if entry.get("url"):
site_url = entry["url"]; break
net = trace_cookie_network(cd, site_url)
if net:
net_html = build_network_trace_block_html(net)
parts.append(net_html)
section_sizes["network_trace_v2"] = len(net_html)
except Exception as e:
logger.warning("Replay v2: entropy/network failed: %s", e)
# P82: GF-1-Pager zuerst (5-Bullet-Summary)
try:
from compliance.services.gf_one_pager import build_gf_one_pager_html
@@ -0,0 +1,125 @@
"""
P54 Diff-Banner fuer End-User (USP-Feature).
USP-Idee: bei wiederkehrenden Besuchern zeigt das Banner NICHT die
Standard-Frage, sondern eine Diff-Mitteilung:
"Seit deiner letzten Zustimmung haben wir hinzugefuegt:
* Microsoft Bing (Werbung)
* TikTok Pixel (Marketing)
Bitte erneut zustimmen oder anpassen."
Backend-Seite (hier): liefert pro Snapshot eine 'diff_for_user'-Struktur
die zum Embedden in eigenen Banner / Hinweistext genutzt werden kann.
Frontend-Banner-Lib (separate consent-sdk) konsumiert das.
Vergleicht Vendor-Listen zwischen aktuellem Snapshot und dem letzten
Snapshot mit gleicher site_domain.
"""
from __future__ import annotations
import logging
from typing import Iterable
from sqlalchemy import text as sa_text
from sqlalchemy.orm import Session
logger = logging.getLogger(__name__)
def _norm_vendor_set(vendors: Iterable) -> set[str]:
out: set[str] = set()
for v in (vendors or []):
if isinstance(v, dict):
n = (v.get("name") or "").strip()
elif isinstance(v, str):
n = v.strip()
else:
continue
if n:
out.add(n)
return out
def compute_user_facing_diff(
db: Session,
site_domain: str,
current_check_id: str,
current_cmp_vendors: list,
) -> dict | None:
"""Vergleicht aktuelle vs letzte cmp_vendors-Liste fuer die gleiche
site_domain. Liefert {prev_at, added_vendors, removed_vendors,
new_high_risk_categories} oder None wenn kein vorheriger Lauf."""
if not site_domain:
return None
try:
row = db.execute(sa_text(
"""
SELECT cmp_vendors, created_at
FROM compliance.compliance_check_snapshots
WHERE site_domain = :dom AND check_id != :ex
ORDER BY created_at DESC LIMIT 1
"""
), {"dom": site_domain, "ex": current_check_id}).fetchone()
except Exception as e:
logger.warning("diff lookup failed: %s", e)
return None
if not row:
return None
prev_vendors = row[0] or []
prev_at = row[1]
curr_set = _norm_vendor_set(current_cmp_vendors)
prev_set = _norm_vendor_set(prev_vendors)
added = sorted(curr_set - prev_set)
removed = sorted(prev_set - curr_set)
if not added and not removed:
return None
# High-risk Kategorien aus added Vendors: Marketing / Tracking
new_marketing: list[str] = []
for v in current_cmp_vendors:
if not isinstance(v, dict):
continue
n = (v.get("name") or "").strip()
cat = (v.get("category") or "").lower()
if n in added and cat in ("marketing", "tracking", "advertising"):
new_marketing.append(n)
return {
"prev_at": prev_at.isoformat() if prev_at else None,
"added_vendors": added,
"removed_vendors": removed,
"new_marketing_vendors": new_marketing,
"requires_reconsent": bool(new_marketing),
}
def build_diff_banner_snippet(diff: dict) -> str:
"""Liefert HTML-Snippet das der Site-Betreiber in seinen eigenen
Cookie-Banner einbauen kann (z.B. via consent-sdk)."""
if not diff or not diff.get("added_vendors"):
return ""
added = diff.get("added_vendors", [])
n_marketing = len(diff.get("new_marketing_vendors") or [])
items = "".join(f"<li>{v}</li>" for v in added[:8])
reconsent_note = ""
if diff.get("requires_reconsent"):
reconsent_note = (
f'<p style="margin:6px 0 0;color:#991b1b;font-size:12px">'
f'<strong>{n_marketing} neue{"r" if n_marketing == 1 else ""} '
f'Marketing-Anbieter</strong> seit Ihrer letzten Zustimmung — '
'bitte erneut bestaetigen.'
'</p>'
)
return (
'<div class="breakpilot-consent-diff" '
'style="font-family:-apple-system,sans-serif;font-size:12px;'
'padding:8px 12px;background:#fef3c7;border:1px solid #fde68a;'
'border-radius:6px;margin-bottom:8px">'
'<strong>Seit Ihrer letzten Zustimmung haben wir hinzugefuegt:</strong>'
f'<ul style="margin:4px 0 0 18px;padding:0">{items}</ul>'
+ reconsent_note +
'</div>'
)
@@ -0,0 +1,222 @@
"""
P6 + P53 + P55 OEM-Cross-Industry-Library mit Autonomes Profiling.
Vereinheitlicht 3 verwandte Themen:
* P6 Branchen-Knowledge-Base: was ist branchen-spezifisch (Automotive
hat eCall, eHealth hat Patientendaten, Finance hat MaRisk).
* P53 OEM-Site-Profile-Library: bekannte Pattern pro OEM-Site
(Mercedes hat cmm-cookie-banner, BMW hat ePaaS, VW hat
cookiemgmt, Audi blocked Akamai 503).
* P55 Autonomes Profiling: bei jedem Lauf lernen wir Pattern dazu
und persistieren sie in der Library.
Backend-Service: Lookup-API + Auto-Lern-Hook bei jedem Snapshot-Save.
"""
from __future__ import annotations
import json
import logging
import os
from typing import Iterable
from sqlalchemy import text as sa_text
from sqlalchemy.orm import Session
logger = logging.getLogger(__name__)
# Branchen-spezifische zusaetzliche Compliance-Themen
_INDUSTRY_PROFILES: dict[str, dict] = {
"automotive": {
"mandatory_regulations": [
"DSGVO", "TDDDG",
"VO 2015/758 (eCall)",
"VO 2018/858 (Typgenehmigung)",
"VO 2019/2144 (Allgemeine Sicherheit)",
"Cyber Security UN-R 155",
"Software Update UN-R 156",
],
"typical_cookie_vendors": [
"Adobe Analytics", "Adobe Target", "Salesforce LiveAgent",
"AdForm", "The Trade Desk", "Google Marketing Platform",
"Inbenta", "Datadog RUM",
],
"vvt_required_processes": [
"Probefahrten-Buchung", "Haendler-Suche", "eCall-System",
"We Connect / Connected Drive Services", "Konfigurator-Daten",
],
"special_findings_to_watch": [
"eCall ohne Hinweis in DSE = Verstoss VO 2015/758 Art. 6(4)",
"Connected-Car-Telemetrie ohne Einwilligung",
"Haendler-Weitergabe nicht erwaehnt (Art. 13(1)(e))",
],
},
"ecommerce": {
"mandatory_regulations": [
"DSGVO", "TDDDG", "Fernabsatzgesetz",
"Verbraucherrechterichtlinie (EU 2011/83)",
"Geo-Blocking-Verordnung (EU 2018/302)",
],
"typical_cookie_vendors": [
"Google Analytics", "Google Ads", "Meta Pixel",
"Pinterest", "TikTok", "Criteo", "AppNexus",
"Klaviyo", "Hotjar",
],
"vvt_required_processes": [
"Bestellung", "Zahlung", "Versand", "Retoure",
"Newsletter", "Account-Verwaltung",
],
"special_findings_to_watch": [
"Widerrufsbelehrung muss 14-Tage-Frist + Wertersatz nennen",
"Muster-Widerrufsformular als Anlage Pflicht",
"Kundenkonto-Loeschung muss in DSR-Prozess sein",
],
},
"saas": {
"mandatory_regulations": [
"DSGVO", "TDDDG", "AI Act (wenn KI-Features)",
"NIS-2 (wenn kritische Infrastruktur)",
],
"typical_cookie_vendors": [
"Segment", "Amplitude", "Mixpanel", "Hotjar",
"Intercom", "HubSpot", "Salesforce", "Stripe",
],
"vvt_required_processes": [
"Login / Auth", "Trial-Signup", "Abrechnung",
"Support-Tickets", "Telemetry / Usage-Analytics",
],
"special_findings_to_watch": [
"B2B-AVV (Art. 28) statt Endkunden-DSE",
"Sub-Prozessor-Liste muss vollstaendig sein",
"Drittland (USA-Hosting) erfordert SCC + TIA",
],
},
"banking": {
"mandatory_regulations": [
"DSGVO", "TDDDG", "PSD2 (Payment Services Directive)",
"MaRisk", "BAIT (BaFin)", "KWG", "GwG",
],
"typical_cookie_vendors": [
"Adobe Analytics", "Glassbox", "ContentSquare",
"Decibel", "Qualtrics",
],
"vvt_required_processes": [
"Kontoeroeffnung", "Zahlungsverkehr", "Kreditpruefung",
"Geldwaesche-Pruefung (GwG)", "Schufa-Anfrage",
],
"special_findings_to_watch": [
"PSD2 Strong-Customer-Authentication Pflicht",
"Bankgeheimnis = zusaetzlicher Schutz",
"GwG-Pflicht-Identifikation erfordert spezielle DSE-Klausel",
],
},
"healthcare": {
"mandatory_regulations": [
"DSGVO Art. 9 (Gesundheitsdaten)",
"Medizinprodukteverordnung (MDR)",
"Patientendaten-Schutzgesetz (PDSG)",
"DiGAV (Digitale-Gesundheitsanwendungen-Verordnung)",
],
"typical_cookie_vendors": [
"Sehr restriktiv — i.d.R. nur essential",
],
"vvt_required_processes": [
"Termin-Vereinbarung", "Anamnese-Bogen",
"Befund-Versand", "ePA-Anbindung",
],
"special_findings_to_watch": [
"Art. 9 DSGVO erfordert ausdrueckliche Einwilligung",
"Schweigepflicht §203 StGB",
"Drittland-Transfer fast immer unzulaessig",
],
},
}
def lookup_industry_profile(industry: str | None) -> dict | None:
"""Liefert das Branchenprofil oder None."""
if not industry:
return None
return _INDUSTRY_PROFILES.get(industry.lower())
# Site-Profile (gelernt aus vorherigen Snapshots)
def load_site_profile(db: Session, site_domain: str) -> dict | None:
"""Liefert gespeichertes Profil fuer eine Site (CMP-Provider,
bekannte Quirks etc.) oder None."""
if not site_domain:
return None
try:
row = db.execute(sa_text(
"""
SELECT banner_provider,
jsonb_array_length(coalesce(cmp_vendors, jsonb_build_array())) AS n_vendors,
created_at
FROM compliance.compliance_check_snapshots
WHERE site_domain = :dom
ORDER BY created_at DESC LIMIT 5
"""
), {"dom": site_domain}).fetchall()
except Exception:
return None
if not row:
return None
providers = [r[0] for r in row if r[0]]
vendor_counts = [r[1] for r in row if r[1] is not None]
if not providers:
return None
# Most common provider
from collections import Counter
common_provider = Counter(providers).most_common(1)[0][0]
avg_vendors = sum(vendor_counts) // max(1, len(vendor_counts))
return {
"site_domain": site_domain,
"common_provider": common_provider,
"avg_vendor_count": avg_vendors,
"historical_runs": len(row),
"last_run": row[0][2].isoformat() if row[0][2] else None,
}
def build_industry_context_block_html(
industry: str | None,
site_profile: dict | None,
) -> str:
"""Eingangsblock in der Mail: 'Was wir in dieser Branche pruefen
sollten' + 'Was wir ueber diese Site schon wissen'."""
parts: list[str] = []
profile = lookup_industry_profile(industry)
if profile:
regs = ", ".join(profile.get("mandatory_regulations", [])[:6])
watches = profile.get("special_findings_to_watch", [])[:3]
watch_html = "".join(
f'<li style="font-size:11px;color:#475569">{w}</li>'
for w in watches
)
parts.append(
'<div style="background:#eff6ff;border:1px solid #bfdbfe;'
'border-radius:6px;padding:10px 14px;margin-bottom:8px">'
f'<div style="font-size:11px;color:#1e40af;font-weight:600;'
f'text-transform:uppercase;letter-spacing:1px">'
f'Branchen-Kontext: {industry}</div>'
f'<p style="font-size:11px;color:#475569;margin:4px 0">'
f'<strong>Geltende Spezial-Regulierungen:</strong> {regs}'
f'</p>'
f'<div style="font-size:11px;color:#475569"><strong>Worauf '
f'wir bei dieser Branche besonders schauen:</strong></div>'
f'<ul style="margin:4px 0 0 18px;padding:0">{watch_html}</ul>'
'</div>'
)
if site_profile and site_profile.get("historical_runs", 0) > 1:
parts.append(
'<div style="background:#f5f3ff;border:1px solid #ddd6fe;'
'border-radius:6px;padding:8px 12px;margin-bottom:8px;'
'font-size:11px;color:#5b21b6">'
f'Wir haben diese Site bereits {site_profile["historical_runs"]}× '
f'analysiert. Bekannter CMP-Provider: '
f'<strong>{site_profile["common_provider"]}</strong>, '
f'historische Vendor-Zahl: ~{site_profile["avg_vendor_count"]}.'
'</div>'
)
return "".join(parts)
@@ -0,0 +1,229 @@
"""
P31 Tiered LLM-Cascade mit Confidence + Valkey-Cache.
Bisherige LLM-Calls (vendor_llm_extractor, mc_solution_generator):
* gehen direkt an Qwen lokal bei kompliziertem Input lange Latenz
* fallen bei Fail manuell auf OVH 120B zurueck
* Kein Cache gleiche Eingabe kostet x-mal Zeit
Diese Modul vereinheitlicht:
1. Cache-Lookup (md5(prompt) cached response, TTL 7d)
2. Qwen-Aufruf mit kurzem Timeout (90s)
3. Wenn fail/leer ODER confidence < threshold OVH 120B (45s)
4. Wenn auch fail Anthropic Claude (last resort)
5. Response wird gecached
confidence-Heuristik:
* parsed JSON erfolgreich + non-empty 0.8
* JSON-Parse failed 0.0
* JSON ok aber nur 1 Item bei >5000 chars input 0.3
Backend-API: await call_with_cascade(prompt, system_prompt, expected_min_items)
"""
from __future__ import annotations
import hashlib
import json
import logging
import os
from typing import Any
import httpx
logger = logging.getLogger(__name__)
# In-process Cache wenn kein Valkey verfuegbar
_LOCAL_CACHE: dict[str, dict] = {}
_LOCAL_CACHE_MAX = 200
def _cache_key(system: str, user: str, model_hint: str = "") -> str:
blob = f"{system}\n---\n{user}\n---\n{model_hint}"
return "llm:" + hashlib.md5(blob.encode()).hexdigest()[:24]
def _cache_get(key: str) -> dict | None:
try:
import redis # noqa: WPS433
url = os.getenv("VALKEY_URL", "redis://bp-core-valkey:6379")
r = redis.Redis.from_url(url, socket_timeout=2.0,
decode_responses=True)
v = r.get(key)
if v:
return json.loads(v)
except Exception:
pass
return _LOCAL_CACHE.get(key)
def _cache_put(key: str, value: dict, ttl: int = 604800) -> None:
try:
import redis # noqa: WPS433
url = os.getenv("VALKEY_URL", "redis://bp-core-valkey:6379")
r = redis.Redis.from_url(url, socket_timeout=2.0,
decode_responses=True)
r.setex(key, ttl, json.dumps(value)[:200000])
return
except Exception:
pass
if len(_LOCAL_CACHE) >= _LOCAL_CACHE_MAX:
for k in list(_LOCAL_CACHE.keys())[:50]:
_LOCAL_CACHE.pop(k, None)
_LOCAL_CACHE[key] = value
def _heuristic_confidence(response_text: str, input_len: int) -> float:
if not response_text:
return 0.0
try:
obj = json.loads(response_text)
except Exception:
# Try to extract JSON block
a, b = response_text.find("{"), response_text.rfind("}")
if 0 <= a < b:
try:
obj = json.loads(response_text[a:b + 1])
except Exception:
return 0.1
else:
return 0.1
n_items = 0
if isinstance(obj, dict):
for v in obj.values():
if isinstance(v, list):
n_items += len(v)
elif isinstance(v, dict):
n_items += 1
if input_len > 5000 and n_items <= 1:
return 0.3
if n_items >= 5:
return 0.9
return 0.7
async def _call_ollama(system: str, user: str,
max_tokens: int = 6000,
timeout: float = 90.0) -> str:
base = os.getenv("OLLAMA_URL", "http://host.docker.internal:11434")
model = os.getenv("CMP_LLM_MODEL", "qwen3:30b-a3b")
payload = {
"model": model, "stream": False, "format": "json",
"messages": [{"role": "system", "content": system},
{"role": "user", "content": user}],
"options": {"temperature": 0.05, "num_predict": max_tokens},
}
try:
async with httpx.AsyncClient(timeout=timeout) as c:
r = await c.post(f"{base.rstrip('/')}/api/chat", json=payload)
r.raise_for_status()
return (r.json().get("message") or {}).get("content", "") or ""
except Exception as e:
logger.warning("ollama cascade tier 1 failed: %s", e)
return ""
async def _call_ovh(system: str, user: str, max_tokens: int = 6000) -> str:
base = os.getenv("OVH_LLM_URL", "").strip()
key = os.getenv("OVH_LLM_KEY", "").strip()
model = os.getenv("OVH_LLM_MODEL", "").strip()
if not base or not model:
return ""
headers = {"Content-Type": "application/json"}
if key:
headers["Authorization"] = f"Bearer {key}"
payload = {
"model": model, "temperature": 0.05, "max_tokens": max_tokens,
"messages": [{"role": "system", "content": system},
{"role": "user", "content": user}],
"response_format": {"type": "json_object"},
}
try:
async with httpx.AsyncClient(timeout=45.0) as c:
r = await c.post(f"{base.rstrip('/')}/v1/chat/completions",
json=payload, headers=headers)
r.raise_for_status()
choice = (r.json().get("choices") or [{}])[0]
return (choice.get("message") or {}).get("content", "") or ""
except Exception as e:
logger.warning("ovh cascade tier 2 failed: %s", e)
return ""
async def _call_anthropic(system: str, user: str,
max_tokens: int = 4000) -> str:
key = os.getenv("ANTHROPIC_API_KEY", "").strip()
if not key:
return ""
headers = {
"Content-Type": "application/json",
"x-api-key": key,
"anthropic-version": "2023-06-01",
}
payload = {
"model": "claude-haiku-4-5-20251001",
"max_tokens": max_tokens, "temperature": 0.05,
"system": system,
"messages": [{"role": "user", "content": user}],
}
try:
async with httpx.AsyncClient(timeout=30.0) as c:
r = await c.post("https://api.anthropic.com/v1/messages",
json=payload, headers=headers)
r.raise_for_status()
blocks = r.json().get("content") or []
return "".join(b.get("text", "") for b in blocks if isinstance(b, dict))
except Exception as e:
logger.warning("anthropic cascade tier 3 failed: %s", e)
return ""
async def call_with_cascade(
system: str,
user: str,
min_confidence: float = 0.6,
max_tokens: int = 6000,
) -> dict:
"""Returns {'text': str, 'confidence': float, 'source': str,
'cached': bool}."""
key = _cache_key(system, user)
cached = _cache_get(key)
if cached:
cached["cached"] = True
return cached
input_len = len(user)
# Tier 1: Qwen lokal
text = await _call_ollama(system, user, max_tokens=max_tokens)
conf = _heuristic_confidence(text, input_len)
if text and conf >= min_confidence:
out = {"text": text, "confidence": conf,
"source": "qwen", "cached": False}
_cache_put(key, out)
return out
# Tier 2: OVH 120B
text2 = await _call_ovh(system, user, max_tokens=max_tokens)
conf2 = _heuristic_confidence(text2, input_len)
if text2 and conf2 >= min_confidence:
out = {"text": text2, "confidence": conf2,
"source": "ovh_120b", "cached": False}
_cache_put(key, out)
return out
# Tier 3: Anthropic Claude (Notnagel)
text3 = await _call_anthropic(system, user, max_tokens=max_tokens // 2)
conf3 = _heuristic_confidence(text3, input_len)
if text3 and conf3 >= min_confidence:
out = {"text": text3, "confidence": conf3,
"source": "anthropic_claude", "cached": False}
_cache_put(key, out)
return out
# Nichts hat geliefert — beste Variante wenigstens zurueckgeben
best_text = text or text2 or text3 or ""
best_conf = max(conf, conf2, conf3)
best_source = "qwen" if text else ("ovh_120b" if text2 else "anthropic")
return {"text": best_text, "confidence": best_conf,
"source": best_source, "cached": False,
"below_threshold": True}
@@ -0,0 +1,269 @@
"""
P106 MC-Audit-Type-Klassifizierung.
Zentrales Problem: viele Master-Controls pruefen Sachverhalte, die wir
von Aussen GAR NICHT pruefen koennen z.B. ob das Unternehmen einen
internen Loeschkonzept-Prozess hat oder Schulungen durchgefuehrt wurden.
Bisher: alle MCs deren Pattern im Text nicht matched FAIL.
Folge: GF-Mail mit 95 FAILs, davon ~60-70 in Wirklichkeit nur 'unknown'.
Loesung: pro MC klassifizieren:
* verifiable Pattern muss im sichtbaren Dokument stehen (Audit moeglich)
* process_internal interner Prozess des Kunden (Schulung, AVV-Vertrag, )
* doc_internal interne Dokumentation (VVT-Eintrag, DSFA-File, )
* ambiguous koennte beides sein
In der MC-Auswertung:
* verifiable + Pattern fehlt echtes FAIL
* process_internal CHECK (Hinweis 'Bitte intern pruefen')
* doc_internal CHECK (Hinweis 'Im VVT/DSFA dokumentiert?')
* ambiguous CHECK mit Warnung
"""
from __future__ import annotations
import logging
import re
logger = logging.getLogger(__name__)
# Patterns die auf interne Prozesse hindeuten (NICHT von aussen pruefbar)
_PROCESS_INTERNAL_PATTERNS = [
# Schulung / Mitarbeiter
r"\bmitarbeiter\b.*schul",
r"\bschulung(en)?\b",
r"\bawareness\b",
r"\bsensibilisier",
# Vertraege intern
r"\bauftragsverarbeitungsvertrag\b",
r"\bAVV\b\s+abgeschlossen",
r"\bvertrag.*abgeschlossen",
r"\bdpa\s+(geschlossen|abgeschlossen|vorhanden)",
r"\bSCC\s+(geschlossen|abgeschlossen|implementiert)",
# Technisch-organisatorische Massnahmen (intern)
r"\btechnisch[-\s]*organisatorische\s+ma(ß|ss)nahmen?\b",
r"\bTOM\s+(umgesetzt|dokumentiert|implementiert)",
r"\bverschluesselung\s+(implementiert|aktiv)",
r"\bpseudonymisierung\s+(implementiert|aktiv)",
r"\bbackup[s]?\s+(eingerichtet|vorhanden)",
r"\bzugriffskontrolle",
r"\b(rollen|berechtigungs)konzept",
# Risikobewertung / DSFA (intern)
r"\bdsfa\s+(durchgefuehrt|erstellt|dokumentiert)",
r"\brisikobewertung\s+(durchgefuehrt|dokumentiert)",
r"\brisikoanalyse",
# Loeschkonzept / Aufbewahrung
r"\bloeschkonzept\s+(umgesetzt|implementiert)",
r"\baufbewahrungsfrist(en)?\s+(eingehalten|definiert)",
r"\bloeschroutinen?\s+(aktiv|implementiert)",
# Meldewege / Vorfallmanagement
r"\bmeldepflicht\s+(eingehalten|umgesetzt)",
r"\bvorfallmanagement",
r"\bincident[\s-]?response",
r"\b72[\s-]?stunden[\s-]?meldung",
# Generische Prozess-Indikatoren
r"\bdokumentiert\s+werden",
r"\bbitte\s+(intern\s+)?dokumentieren",
r"\bin\s+der\s+verfahrens",
r"\bnach\s+innen\s+geh",
r"\bausnahmen\s+(dokumentieren|protokollieren)",
r"\bkostenfrei\s+(zur\s+verfuegung|gewaehren|ermoegli)",
r"\bunentgeltlich\s+(zur\s+verfuegung)",
# Vertragsleistung / Service-Level (intern)
r"\bservice[\s-]?level",
r"\breaktionszeit",
# Auditierung / Aufsicht
r"\binterne(s)?\s+audit",
r"\baufsichtsbehoerde\s+gemeldet",
r"\bbeauftragter\s+(intern|benannt)",
# eCall + Branchen-spezifische interne Pflichten
r"\babschaltung\s+der\s+\w+\s+kostenfrei",
r"\bopt[\s-]?out\s+(intern|im\s+kundenportal)\s+ermoeglichen",
]
# Patterns die auf interne Dokumentation hindeuten (VVT, DSFA-Datei, …)
_DOC_INTERNAL_PATTERNS = [
r"\bverzeichnis\s+der\s+verarbeitungstaetigkeiten\b",
r"\bvvt(\s+|\b)",
r"\bdsfa[\s-]?dokument",
r"\bauftragsverarbeitungsverzeichnis",
r"\bsub[\s-]?prozessor[\s-]?liste",
r"\bverarbeitungs[\s-]?register",
r"\binternes\s+register",
r"\baufbewahrungs[\s-]?konzept\b",
]
# Patterns die auf externe Sichtbarkeit hindeuten → DEFINITIV verifiable
_VERIFIABLE_PATTERNS = [
r"\bin\s+der\s+(datenschutzerklaerung|dse|cookie[\s-]?richtlinie|impressum|agb)\b",
r"\bauf\s+der\s+website\s+(genannt|sichtbar|angegeben)",
r"\bim\s+banner\s+(genannt|sichtbar)",
r"\bim\s+cookie[\s-]?banner",
r"\bauf\s+der\s+startseite",
r"\bim\s+footer",
]
def _matches_any(text: str, patterns: list[str]) -> bool:
tl = text.lower()
for pat in patterns:
try:
if re.search(pat, tl):
return True
except re.error:
continue
return False
def classify_mc_audit_type(
title: str | None,
check_question: str | None = None,
fail_criteria: dict | None = None,
) -> str:
"""Returns 'verifiable', 'process_internal', 'doc_internal',
or 'ambiguous'."""
blob = " ".join([title or "", check_question or "",
str(fail_criteria or "")])
if not blob.strip():
return "ambiguous"
is_verifiable_hint = _matches_any(blob, _VERIFIABLE_PATTERNS)
is_process = _matches_any(blob, _PROCESS_INTERNAL_PATTERNS)
is_doc = _matches_any(blob, _DOC_INTERNAL_PATTERNS)
# Wenn explicit Verifiable-Indikator + kein Process → verifiable
if is_verifiable_hint and not (is_process or is_doc):
return "verifiable"
# Wenn Process oder Doc UND nicht Verifiable → intern
if is_process and not is_verifiable_hint:
return "process_internal"
if is_doc and not is_verifiable_hint:
return "doc_internal"
# Beides → ambiguous, im Zweifel CHECK markieren
if is_process or is_doc:
return "ambiguous"
return "verifiable"
def annotate_mc_results(check_results: list[dict]) -> list[dict]:
"""In-place: setzt mc_audit_type auf jeden MC-Check und ersetzt
Status 'failed' durch 'check' wenn audit_type != verifiable."""
if not check_results:
return check_results
n_reclassified = 0
for r in check_results:
if not isinstance(r, dict):
continue
if not (r.get("id") or "").startswith("mc-"):
continue
if "mc_audit_type" not in r:
r["mc_audit_type"] = classify_mc_audit_type(
r.get("label"), r.get("hint"), r.get("fail_criteria"),
)
# Wenn FAIL aber audit_type != verifiable → "check" (manuell)
if (not r.get("passed")
and not r.get("skipped")
and r["mc_audit_type"] in (
"process_internal", "doc_internal", "ambiguous",
)):
r["audit_status"] = "check" # NICHT failed
n_reclassified += 1
elif r.get("passed"):
r["audit_status"] = "pass"
elif r.get("skipped"):
r["audit_status"] = "skip"
else:
r["audit_status"] = "fail"
if n_reclassified:
logger.info(
"MC-Audit-Type: %d/%d MCs reklassifiziert von FAIL → CHECK "
"(interne Pruefung erforderlich)",
n_reclassified, len(check_results),
)
return check_results
def split_by_audit_type(check_results: list[dict]) -> dict[str, list[dict]]:
"""Liefert {verifiable_fails, internal_checks, passes, skips}."""
out = {"verifiable_fails": [], "internal_checks": [],
"passes": [], "skips": []}
for r in (check_results or []):
if not isinstance(r, dict):
continue
if not (r.get("id") or "").startswith("mc-"):
continue
status = r.get("audit_status")
if status == "pass":
out["passes"].append(r)
elif status == "skip":
out["skips"].append(r)
elif status == "check":
out["internal_checks"].append(r)
elif status == "fail" or (not r.get("passed") and not r.get("skipped")):
out["verifiable_fails"].append(r)
return out
def build_internal_checks_block_html(
internal_checks: list[dict],
limit: int = 30,
) -> str:
if not internal_checks:
return ""
by_type: dict[str, list[dict]] = {}
for c in internal_checks:
t = c.get("mc_audit_type", "ambiguous")
by_type.setdefault(t, []).append(c)
sections: list[str] = []
labels = {
"process_internal": ("Interne Prozesse — bitte beim DSB pruefen",
"#1e40af"),
"doc_internal": ("Interne Dokumentation — bitte im VVT/DSFA pruefen",
"#5b21b6"),
"ambiguous": ("Unklar ob Audit-Befund oder interne Pruefung",
"#92400e"),
}
for atype, (heading, color) in labels.items():
items = by_type.get(atype) or []
if not items:
continue
rows = "".join(
f'<li style="margin-bottom:4px;font-size:11px;line-height:1.45">'
f'<strong>{(c.get("label") or "")[:160]}</strong>'
+ (f' <span style="color:#94a3b8">({c.get("regulation") or ""})</span>'
if c.get("regulation") else '') +
f'</li>'
for c in items[:limit]
)
sections.append(
f'<div style="margin-bottom:10px">'
f'<div style="font-size:11px;color:{color};text-transform:uppercase;'
f'letter-spacing:1px;font-weight:600;margin-bottom:4px">'
f'{heading} ({len(items)})</div>'
f'<ul style="margin:0 0 0 18px;padding:0">{rows}</ul>'
f'</div>'
)
return (
'<div style="font-family:-apple-system,BlinkMacSystemFont,sans-serif;'
'max-width:760px;margin:0 auto 16px;padding:12px 16px;'
'background:#f0f9ff;border:1px solid #bfdbfe;border-radius:8px">'
'<div style="font-size:11px;color:#1e40af;text-transform:uppercase;'
'letter-spacing:1.2px;margin-bottom:4px;font-weight:600">'
'Pruefungen die wir von aussen NICHT durchfuehren koennen</div>'
f'<h3 style="margin:0 0 6px;font-size:14px;color:#1e293b">'
f'{len(internal_checks)} Pruefpunkt'
f'{"e" if len(internal_checks) != 1 else ""} sind '
'NUR intern beim Kunden zu pruefen</h3>'
'<p style="margin:0 0 10px;font-size:11px;color:#475569;'
'line-height:1.5">'
'Diese Anforderungen koennen wir per externem Website-Audit nicht '
'als erfuellt oder nicht-erfuellt bewerten — sie betreffen interne '
'Prozesse (Schulungen, AVV-Vertraege, TOM-Doku) oder interne '
'Dokumentation (VVT, DSFA, Loeschkonzept). Sie sind also <strong>kein '
'Verstoss</strong>, sondern Hinweis-Checks fuer Ihren DSB.</p>'
+ "".join(sections) +
'</div>'
)
@@ -61,6 +61,12 @@ def build_scorecard(check_results: list[dict]) -> dict:
b["skipped"] += 1
elif r.get("passed"):
b["passed"] += 1
# P106 — interner Check ist KEIN Fail (zaehlt als skipped fuer
# die Score-Berechnung damit der Score realistisch ist).
elif r.get("audit_status") == "check":
b["skipped"] += 1
b.setdefault("internal_checks", 0)
b["internal_checks"] += 1
else:
b["failed"] += 1
sev = (r.get("severity") or "MEDIUM").upper()
@@ -0,0 +1,173 @@
"""
P68 Reverse-Audit: eigene Templates gegen alle MCs pruefen.
Statt 'gegeben einen Kunden-Text → welche MCs fail' machen wir den
umgekehrten Test: 'gegeben unseren BreakPilot-Standard-Template-Pool
(95 Templates) welche MCs werden NICHT abgedeckt? Wo sind Luecken?'
Liefert einen Coverage-Report:
- Total MCs in DB: ~1800
- MCs abgedeckt durch min. 1 unserer Templates: X
- MCs ohne Coverage: Y (Liste)
- Templates ohne MC-Wirkung: Z (Liste)
Zweck: Audit unserer eigenen Code-Base. Wenn ein Customer einen Lauf
macht und 50 Findings produziert sind, sollten 90%+ davon durch unsere
Template-Bibliothek korrigierbar sein. Wenn nicht Templates fehlen.
"""
from __future__ import annotations
import logging
import re
from sqlalchemy import text as sa_text
from sqlalchemy.orm import Session
logger = logging.getLogger(__name__)
def run_reverse_audit(db: Session) -> dict:
"""Hauptfunktion. Returns coverage-report dict."""
# 1) Alle MCs aus doc_check_controls laden
mc_rows = db.execute(sa_text(
"""
SELECT id::text, control_id, doc_type, title, check_question,
pass_criteria, severity
FROM compliance.doc_check_controls
ORDER BY doc_type, severity DESC
"""
)).fetchall()
# 2) Templates aus DB (doc_templates oder legal_templates oder analog)
try:
tpl_rows = db.execute(sa_text(
"""
SELECT id::text, doc_type, title, body
FROM compliance.doc_templates
WHERE active = TRUE
"""
)).fetchall()
except Exception:
# Fallback auf evtl. andere Template-Tabelle
try:
tpl_rows = db.execute(sa_text(
"""
SELECT id::text, doc_type, name AS title, content AS body
FROM compliance.legal_templates
"""
)).fetchall()
except Exception as e:
logger.warning("template table not found: %s", e)
tpl_rows = []
# 3) Coverage-Matrix: pro MC, ob ein Template sie abdeckt
templates_by_doctype: dict[str, list[dict]] = {}
for tid, dt, title, body in tpl_rows:
templates_by_doctype.setdefault(dt or "other", []).append({
"id": tid, "title": title, "body": (body or "")[:50000],
})
covered_mc_ids: set[str] = set()
uncovered: list[dict] = []
for mc_id, ctrl_id, dt, title, q, pc, sev in mc_rows:
tpls = templates_by_doctype.get(dt or "other") or []
if not tpls:
uncovered.append({
"mc_id": ctrl_id, "doc_type": dt, "title": title,
"severity": sev, "reason": "no_template_for_doctype",
})
continue
# Heuristik: pass_criteria sind Pattern. Wenn IRGENDEIN Template
# die Pattern enthaelt → covered.
criteria = _extract_patterns_from_pc(pc)
if not criteria:
# ohne klare Pattern: per Title-Keywords pruefen
criteria = _title_keywords(title or "")
ok = False
for tpl in tpls:
body = tpl["body"].lower()
hits = sum(1 for p in criteria if p and p.lower() in body)
if hits >= max(1, len(criteria) // 2):
ok = True
break
if ok:
covered_mc_ids.add(mc_id)
else:
uncovered.append({
"mc_id": ctrl_id, "doc_type": dt, "title": title,
"severity": sev, "reason": "no_template_match",
"criteria_sample": criteria[:5],
})
# 4) Templates ohne MC-Wirkung
used_template_ids: set[str] = set()
for mc_id, ctrl_id, dt, title, q, pc, sev in mc_rows:
if mc_id not in covered_mc_ids:
continue
tpls = templates_by_doctype.get(dt or "other") or []
criteria = _extract_patterns_from_pc(pc) or _title_keywords(title or "")
for tpl in tpls:
body = tpl["body"].lower()
hits = sum(1 for p in criteria if p and p.lower() in body)
if hits >= max(1, len(criteria) // 2):
used_template_ids.add(tpl["id"])
break
all_template_ids = {t["id"] for tpls in templates_by_doctype.values()
for t in tpls}
unused_templates = all_template_ids - used_template_ids
return {
"total_mcs": len(mc_rows),
"total_templates": len(all_template_ids),
"covered_mcs": len(covered_mc_ids),
"uncovered_mcs": len(uncovered),
"coverage_pct": round(len(covered_mc_ids) / max(1, len(mc_rows)) * 100, 1),
"unused_templates": sorted(unused_templates),
"top_uncovered_high": [u for u in uncovered if u.get("severity") == "HIGH"][:30],
"by_doctype": _summarize_by_doctype(mc_rows, covered_mc_ids),
}
def _extract_patterns_from_pc(pc) -> list[str]:
"""pc ist jsonb mit z.B. {required_phrases: [...]}, {keywords: [...]}"""
if not pc:
return []
if isinstance(pc, str):
try:
import json as _j
pc = _j.loads(pc)
except Exception:
return [pc[:50]]
if isinstance(pc, dict):
out: list[str] = []
for k in ("required_phrases", "keywords", "must_contain",
"patterns", "phrases"):
v = pc.get(k)
if isinstance(v, list):
out.extend([str(x)[:80] for x in v if x])
return out
if isinstance(pc, list):
return [str(x)[:80] for x in pc if x]
return []
def _title_keywords(title: str) -> list[str]:
"""Fallback wenn pass_criteria leer: extrahiere Substantive aus Title."""
if not title:
return []
# primitive: alle Worte > 4 Buchstaben
return [w for w in re.findall(r"\b\w{5,}\b", title)][:5]
def _summarize_by_doctype(mc_rows, covered_mc_ids: set[str]) -> dict:
out: dict[str, dict] = {}
for mc_id, ctrl_id, dt, title, q, pc, sev in mc_rows:
dt = dt or "other"
d = out.setdefault(dt, {"total": 0, "covered": 0})
d["total"] += 1
if mc_id in covered_mc_ids:
d["covered"] += 1
for dt, d in out.items():
d["pct"] = round(d["covered"] / max(1, d["total"]) * 100, 1)
return out
+4
View File
@@ -28,4 +28,8 @@ USER appuser
EXPOSE 8094
# P83 — Build-SHA fuer check-rebuild-needed.sh
ARG BUILD_SHA="unknown"
ENV BUILD_SHA=${BUILD_SHA}
CMD ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "8094"]