data/sample_preview.json

{
  "run_id": "netflow-0d773ed5964dc52e",
  "status": "ready",
  "status_label": "Windows ready for review \u00b7 Live parse, schema map, robust baseline, Isolation Forest, small autoencoder, optional tree",
  "kpis": {
    "n_raw": 27277,
    "n_valid": 27277,
    "n_dropped": 0,
    "n_windows": 10361,
    "n_security_review": 16,
    "n_context": 14,
    "n_incomplete": 0,
    "parse_coverage": 1.0,
    "event_recall": 1.0,
    "pr_auc": 0.5094,
    "false_alarms_per_1k": 0.0,
    "false_alarms_per_hour": 0.0,
    "mean_detect_delay_min": 0.0,
    "backup_as_security": 0,
    "seconds": 15.444,
    "threshold": 3.0,
    "model_names": "robust+iforest+pytorch+lightgbm",
    "exporter": "canonical"
  },
  "kpi_html": "<div class='kpi-grid'><article class='kpi-card'><p class='kpi-label'>Needs security review</p><p class='kpi-value'>16</p><p class='kpi-sub'>14 context windows</p></article><article class='kpi-card'><p class='kpi-label'>Parse coverage</p><p class='kpi-value'>100%</p><p class='kpi-sub'>27277/27277</p></article><article class='kpi-card'><p class='kpi-label'>Incomplete rows</p><p class='kpi-value'>0</p><p class='kpi-sub'>missing time/source</p></article><article class='kpi-card'><p class='kpi-label'>Test event recall</p><p class='kpi-value'>100%</p><p class='kpi-sub'>volume-z baseline: 0.3333</p></article><article class='kpi-card'><p class='kpi-label'>False alarms / hour</p><p class='kpi-value'>0.00</p><p class='kpi-sub'>windows without a review label</p></article><article class='kpi-card'><p class='kpi-label'>Analyze time</p><p class='kpi-value'>15.4s</p><p class='kpi-sub'>T=3.0</p></article></div>",
  "validation_ok": true,
  "precomputed": true
}