integrity_scanner_fuer_stat.../scanner/baseline.py

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"""
Snapshot and baseline management.
Snapshots are timestamped crawl results. The baseline is a manually
approved reference state. Compromised content must never flow into the
baseline automatically every update requires an explicit `approve` call.
"""
import hashlib
import json
import logging
from datetime import datetime, timezone
from pathlib import Path
from typing import Optional
logger = logging.getLogger(__name__)
def url_key(url: str) -> str:
"""Stable filename-safe key for a URL (first 16 hex chars of SHA-256)."""
return hashlib.sha256(url.encode("utf-8")).hexdigest()[:16]
class BaselineManager:
def __init__(self, data_dir: str | Path):
self.data_dir = Path(data_dir)
self.baseline_dir = self.data_dir / "baseline"
self.pages_dir = self.baseline_dir / "pages"
self.snapshots_dir = self.data_dir / "snapshots"
# ------------------------------------------------------------------
# Snapshot operations
# ------------------------------------------------------------------
def save_snapshot(self, pages: list[dict], errors: list[dict] | None = None) -> Path:
"""
Persist a crawl+extraction result as a timestamped snapshot.
Crawl errors (network failures) are recorded in the manifest so they
survive into the comparison/report stage.
Returns the snapshot directory path.
"""
ts = _utc_stamp()
snap_dir = self.snapshots_dir / ts
snap_pages_dir = snap_dir / "pages"
snap_pages_dir.mkdir(parents=True, exist_ok=True)
manifest = {
"timestamp": ts,
"page_count": len(pages),
"urls": [p["url"] for p in pages],
"errors": errors or [],
}
(snap_dir / "manifest.json").write_text(
json.dumps(manifest, indent=2, ensure_ascii=False), encoding="utf-8"
)
for page in pages:
fname = url_key(page["url"]) + ".json"
(snap_pages_dir / fname).write_text(
json.dumps(page, indent=2, ensure_ascii=False), encoding="utf-8"
)
logger.info("Snapshot saved: %s (%d pages)", snap_dir, len(pages))
return snap_dir
def latest_snapshot_dir(self) -> Optional[Path]:
"""Return the most recent snapshot directory, or None."""
if not self.snapshots_dir.exists():
return None
dirs = sorted(
(d for d in self.snapshots_dir.iterdir() if d.is_dir()),
key=lambda d: d.name,
)
return dirs[-1] if dirs else None
def load_snapshot(self, snap_dir: Optional[Path] = None) -> dict:
"""
Load a snapshot (default: latest).
Returns {manifest, pages: {url: page_dict}, errors: list, dir: Path}.
"""
if snap_dir is None:
snap_dir = self.latest_snapshot_dir()
if snap_dir is None or not snap_dir.exists():
return {}
manifest = json.loads((snap_dir / "manifest.json").read_text(encoding="utf-8"))
pages: dict[str, dict] = {}
pages_dir = snap_dir / "pages"
for f in pages_dir.glob("*.json"):
page = json.loads(f.read_text(encoding="utf-8"))
pages[page["url"]] = page
return {
"manifest": manifest,
"pages": pages,
"errors": manifest.get("errors", []),
"dir": snap_dir,
}
# ------------------------------------------------------------------
# Baseline operations
# ------------------------------------------------------------------
def baseline_exists(self) -> bool:
return (self.baseline_dir / "manifest.json").exists()
def load_baseline(self) -> dict:
"""
Load the current approved baseline.
Returns {manifest, pages: {url: page_dict}}.
"""
if not self.baseline_exists():
return {"manifest": {}, "pages": {}}
manifest = json.loads(
(self.baseline_dir / "manifest.json").read_text(encoding="utf-8")
)
pages: dict[str, dict] = {}
if self.pages_dir.exists():
for f in self.pages_dir.glob("*.json"):
page = json.loads(f.read_text(encoding="utf-8"))
pages[page["url"]] = page
return {"manifest": manifest, "pages": pages}
# ------------------------------------------------------------------
# Approve operations (the only way baseline content is ever updated)
# ------------------------------------------------------------------
def approve_all(
self,
snap_dir: Optional[Path] = None,
note: str = "",
approved_by: str = "cli",
) -> list[str]:
"""
Approve every page in the snapshot as the new baseline.
Existing baseline pages NOT present in snapshot are kept unless
--rebuild is requested (caller responsibility to wipe baseline_dir first).
"""
snap = self.load_snapshot(snap_dir)
if not snap:
raise RuntimeError("No snapshot found to approve.")
self.pages_dir.mkdir(parents=True, exist_ok=True)
approved: list[str] = []
for url, page in snap["pages"].items():
fname = url_key(url) + ".json"
(self.pages_dir / fname).write_text(
json.dumps(page, indent=2, ensure_ascii=False), encoding="utf-8"
)
approved.append(url)
self._write_manifest(approved, note, approved_by, snap.get("dir"))
logger.info("Approved %d URLs into baseline.", len(approved))
return approved
def approve_url(
self,
url: str,
snap_dir: Optional[Path] = None,
note: str = "",
approved_by: str = "cli",
) -> bool:
"""Approve a single URL from snapshot into the baseline."""
snap = self.load_snapshot(snap_dir)
if url not in snap.get("pages", {}):
logger.error("URL not found in snapshot: %s", url)
return False
self.pages_dir.mkdir(parents=True, exist_ok=True)
fname = url_key(url) + ".json"
(self.pages_dir / fname).write_text(
json.dumps(snap["pages"][url], indent=2, ensure_ascii=False),
encoding="utf-8",
)
# Update manifest incrementally
if self.baseline_exists():
manifest = json.loads(
(self.baseline_dir / "manifest.json").read_text(encoding="utf-8")
)
else:
manifest = {"urls": []}
if url not in manifest.get("urls", []):
manifest.setdefault("urls", []).append(url)
manifest["last_updated"] = datetime.now(timezone.utc).isoformat()
manifest["last_note"] = note
manifest["last_approved_by"] = approved_by
(self.baseline_dir / "manifest.json").write_text(
json.dumps(manifest, indent=2, ensure_ascii=False), encoding="utf-8"
)
logger.info("Approved single URL into baseline: %s", url)
return True
def rebuild_baseline(
self,
snap_dir: Optional[Path] = None,
note: str = "",
approved_by: str = "cli",
) -> list[str]:
"""
Wipe the entire baseline and replace it with the given snapshot.
Use when a major legitimate redesign has taken place.
"""
import shutil
if self.baseline_dir.exists():
shutil.rmtree(self.baseline_dir)
self.pages_dir.mkdir(parents=True, exist_ok=True)
return self.approve_all(snap_dir=snap_dir, note=note, approved_by=approved_by)
# ------------------------------------------------------------------
# Asset hash baseline
# ------------------------------------------------------------------
@property
def _asset_hashes_path(self) -> Path:
return self.baseline_dir / "asset_hashes.json"
def load_asset_hashes(self) -> dict:
"""Load approved asset hashes. Returns {} if none approved yet."""
if not self._asset_hashes_path.exists():
return {}
return json.loads(self._asset_hashes_path.read_text(encoding="utf-8"))
def save_asset_hashes(self, hashes: dict) -> None:
"""Persist asset hashes as the new approved state."""
self.baseline_dir.mkdir(parents=True, exist_ok=True)
self._asset_hashes_path.write_text(
json.dumps(hashes, indent=2, ensure_ascii=False), encoding="utf-8"
)
logger.info("Asset hashes saved: %d entries", len(hashes))
feat: KI-gestützte Inhaltsanalyse via OpenRouter (hash-gegated) Optionale semantische Prüfung von Text und Bildern (inkl. OCR) auf problematische Inhalte ohne Link-Signal: Pornografie, Propaganda, diffamierende/strafbare Texte, versteckter Spam, themenfremde Werbung, widersprüchliche Aussagen. Bewertet die thematische Passung zum deklarierten site_context — eingestreute Heimat-Begriffe täuschen die Erkennung nicht. Kern: - scanner/ai_analyzer.py: run_ai_analysis + score_ai_findings. Hash-Gate über data/ai_ledger.json → unveränderte Inhalte = Cache- Treffer = kein API-Call. Nur neue/geänderte Inhalte kosten etwas. - Modell-Kette mit zweifacher Eskalation (Stufe 1+2 free, Stufe 3 günstig bezahlt); eskaliert bei Fehler ODER Timeout (attempt_timeout). Erfolgreiches Modell wird im Ledger vermerkt. - KI-Funde sind auf GELB gedeckelt — ROT bleibt harten Integritäts- Signalen vorbehalten. Graceful degradation: ohne Key/bei Fehler wird übersprungen, Scan läuft unverändert weiter. Integration: - baseline.py: load/save_ai_ledger, dismiss_ai_entries. - config.py: ai_analysis-Block + ai_* Scoring-Schlüssel. - __main__.py: Einhängung in cmd_scan/cmd_check, ai-dismiss-Subcommand, approve quittiert zugehörige Funde, status-Anzeige, diff-only + report. - alerter.py + __main__.py: beanstandete Dateien erscheinen mit URL, Begründung und Quittier-Fingerprint in E-Mail UND Markdown-Report. - plain.py: laienverständliche KI-Sätze. API-Key nur aus Umgebungsvariable (OPENROUTER_API_KEY). Audio/Video als abschaltbare Hooks vorbereitet (default aus). Modelle live gegen OpenRouter verifiziert; Demo auf bredelar.info zeigte korrekte Erkennung (echter Inhalt clean, eingeschleuster Casino-Spam mit Heimat-Begriffen als hidden_spam erkannt). Tests: 227 grün (+26 für ai_analyzer, +1 für E-Mail-KI-Abschnitt). Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
2026-06-13 00:04:33 +02:00
# ------------------------------------------------------------------
# AI verdict ledger (cache keyed by content fingerprint)
# ------------------------------------------------------------------
#
# Unlike the baseline, the ledger is a *cache*: it records the AI verdict
# for every fingerprint already analysed — including "clean" ones — so that
# unchanged content is never re-sent to the API. It lives in data_dir
# (not baseline_dir): it is operational state, not an approved reference.
@property
def _ai_ledger_path(self) -> Path:
return self.data_dir / "ai_ledger.json"
def load_ai_ledger(self) -> dict:
"""Load the AI verdict ledger. Returns {'entries': {}} if none/corrupt."""
if not self._ai_ledger_path.exists():
return {"entries": {}}
try:
data = json.loads(self._ai_ledger_path.read_text(encoding="utf-8"))
except (json.JSONDecodeError, ValueError):
return {"entries": {}}
data.setdefault("entries", {})
return data
def save_ai_ledger(self, ledger: dict) -> None:
"""Persist the AI verdict ledger."""
self.data_dir.mkdir(parents=True, exist_ok=True)
self._ai_ledger_path.write_text(
json.dumps(ledger, indent=2, ensure_ascii=False), encoding="utf-8"
)
# ------------------------------------------------------------------
# AI model-router state (circuit-breaker telemetry + /models catalog)
# ------------------------------------------------------------------
@property
def _ai_router_state_path(self) -> Path:
return self.data_dir / "ai_router_state.json"
def load_ai_router_state(self) -> dict:
"""Load the model-router state. Returns a safe default if none/corrupt."""
default = {"models": {}, "catalog": {"slugs": [], "fetched_at": None}}
if not self._ai_router_state_path.exists():
return default
try:
data = json.loads(self._ai_router_state_path.read_text(encoding="utf-8"))
except (json.JSONDecodeError, ValueError):
return default
data.setdefault("models", {})
data.setdefault("catalog", {"slugs": [], "fetched_at": None})
return data
def save_ai_router_state(self, state: dict) -> None:
"""Persist the model-router state."""
self.data_dir.mkdir(parents=True, exist_ok=True)
self._ai_router_state_path.write_text(
json.dumps(state, indent=2, ensure_ascii=False), encoding="utf-8"
)
def invalidate_ai_url_hashes(self, urls: list[str]) -> int:
"""Entfernt URLs aus der url_hashes-Erinnerung. Folge: Die KI lädt diese Bilder
beim nächsten Lauf erneut und bewertet sie inhaltlich neu (geänderte Bytes
neuer Hash Cache-Miss Analyse). Wird von der Datei-Prüfung (check-assets)
für geänderte Bild-Assets aufgerufen. Returns Anzahl entfernter Einträge."""
if not urls:
return 0
ledger = self.load_ai_ledger()
uh = ledger.get("url_hashes", {})
removed = [u for u in urls if u in uh]
for u in removed:
del uh[u]
if removed:
self.save_ai_ledger(ledger)
return len(removed)
feat: KI-gestützte Inhaltsanalyse via OpenRouter (hash-gegated) Optionale semantische Prüfung von Text und Bildern (inkl. OCR) auf problematische Inhalte ohne Link-Signal: Pornografie, Propaganda, diffamierende/strafbare Texte, versteckter Spam, themenfremde Werbung, widersprüchliche Aussagen. Bewertet die thematische Passung zum deklarierten site_context — eingestreute Heimat-Begriffe täuschen die Erkennung nicht. Kern: - scanner/ai_analyzer.py: run_ai_analysis + score_ai_findings. Hash-Gate über data/ai_ledger.json → unveränderte Inhalte = Cache- Treffer = kein API-Call. Nur neue/geänderte Inhalte kosten etwas. - Modell-Kette mit zweifacher Eskalation (Stufe 1+2 free, Stufe 3 günstig bezahlt); eskaliert bei Fehler ODER Timeout (attempt_timeout). Erfolgreiches Modell wird im Ledger vermerkt. - KI-Funde sind auf GELB gedeckelt — ROT bleibt harten Integritäts- Signalen vorbehalten. Graceful degradation: ohne Key/bei Fehler wird übersprungen, Scan läuft unverändert weiter. Integration: - baseline.py: load/save_ai_ledger, dismiss_ai_entries. - config.py: ai_analysis-Block + ai_* Scoring-Schlüssel. - __main__.py: Einhängung in cmd_scan/cmd_check, ai-dismiss-Subcommand, approve quittiert zugehörige Funde, status-Anzeige, diff-only + report. - alerter.py + __main__.py: beanstandete Dateien erscheinen mit URL, Begründung und Quittier-Fingerprint in E-Mail UND Markdown-Report. - plain.py: laienverständliche KI-Sätze. API-Key nur aus Umgebungsvariable (OPENROUTER_API_KEY). Audio/Video als abschaltbare Hooks vorbereitet (default aus). Modelle live gegen OpenRouter verifiziert; Demo auf bredelar.info zeigte korrekte Erkennung (echter Inhalt clean, eingeschleuster Casino-Spam mit Heimat-Begriffen als hidden_spam erkannt). Tests: 227 grün (+26 für ai_analyzer, +1 für E-Mail-KI-Abschnitt). Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
2026-06-13 00:04:33 +02:00
def dismiss_ai_entries(self, fingerprints: list[str] | None = None) -> int:
"""
Mark ledger entries as dismissed (false-positive acknowledgement).
None = dismiss all currently flagged entries. Returns count dismissed.
"""
ledger = self.load_ai_ledger()
entries = ledger.get("entries", {})
count = 0
for fp, entry in entries.items():
if fingerprints is not None and fp not in fingerprints:
continue
if entry.get("category", "clean") != "clean" and not entry.get("dismissed"):
entry["dismissed"] = True
count += 1
if count:
self.save_ai_ledger(ledger)
return count
# ------------------------------------------------------------------
# Run-state (drives auto-scheduling of the weekly checks)
# ------------------------------------------------------------------
@property
def _state_path(self) -> Path:
return self.data_dir / "state.json"
def load_state(self) -> dict:
"""Load the run-state file. Returns {'last_runs': {}} if none exists."""
if not self._state_path.exists():
return {"last_runs": {}}
try:
data = json.loads(self._state_path.read_text(encoding="utf-8"))
except (json.JSONDecodeError, ValueError):
return {"last_runs": {}}
data.setdefault("last_runs", {})
return data
def save_state(self, state: dict) -> None:
"""Persist the run-state file."""
self.data_dir.mkdir(parents=True, exist_ok=True)
self._state_path.write_text(
json.dumps(state, indent=2, ensure_ascii=False), encoding="utf-8"
)
def is_check_due(self, name: str, interval_days: int) -> bool:
"""True if a periodic check has never run or last ran >= interval_days ago."""
last = self.load_state().get("last_runs", {}).get(name)
if not last:
return True
try:
last_dt = datetime.fromisoformat(last)
except ValueError:
return True
age = datetime.now(timezone.utc) - last_dt
return age.total_seconds() >= interval_days * 86400
def mark_check_run(self, name: str) -> None:
"""Record that a periodic check just ran (now, UTC)."""
state = self.load_state()
state["last_runs"][name] = datetime.now(timezone.utc).isoformat()
self.save_state(state)
# ------------------------------------------------------------------
# Internal helpers
# ------------------------------------------------------------------
def _write_manifest(
self,
urls: list[str],
note: str,
approved_by: str,
source_snap: Optional[Path],
) -> None:
self.baseline_dir.mkdir(parents=True, exist_ok=True)
manifest = {
"approved_at": datetime.now(timezone.utc).isoformat(),
"approved_by": approved_by,
"note": note,
"source_snapshot": str(source_snap) if source_snap else "",
"urls": urls,
}
(self.baseline_dir / "manifest.json").write_text(
json.dumps(manifest, indent=2, ensure_ascii=False), encoding="utf-8"
)
def _utc_stamp() -> str:
return datetime.now(timezone.utc).strftime("%Y%m%d_%H%M%S")