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    "section": "safety-security",
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    "headline": "The Breach Became a Time-Series Event",
    "slug": "the-breach-became-a-time-series-event",
    "dek": "EventTime fused market history with breach metadata to estimate short-term abnormal losses after disclosures.",
    "summary": "EventTime fused market history with breach metadata to estimate short-term abnormal losses after disclosures.",
    "body_text": "EventTime combines long-horizon market context, immediate pre-event behavior and event metadata, with contrastive learning designed for sparse, heterogeneous shocks. The accompanying SECURE dataset aligns cybersecurity incidents with stock-market series and structured plus model-derived features. Across the authors’ tests it outperformed time-series and event-aware baselines, but it estimates associations in historical data rather than guaranteeing a tradable forecast or causal loss figure.",
    "why_it_matters": "EventTime fused market history with breach metadata to estimate short-term abnormal losses after disclosures.",
    "limitations": [],
    "importance": 8,
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    "modified_at": "2026-08-21T09:00:00.000-04:00",
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    "tags": [
      "cybersecurity",
      "time series",
      "market impact"
    ],
    "image_url": null,
    "corrections": []
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  "sources": [
    {
      "source_id": "source-2026-08-21-006",
      "title": "arXiv preprint 2608.19447",
      "publisher": "arXiv",
      "url": "https://arxiv.org/abs/2608.19447",
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      "published_at": "2026-08-18T20:00:00.000-04:00",
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  "publisher": {
    "name": "The Machine Press",
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    "description": "A daily newspaper for the age of artificial intelligence."
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  "cite_this_report": {
    "title": "The Breach Became a Time-Series Event",
    "publisher": "The Machine Press",
    "published_at": "2026-08-21T09:00:00.000-04:00",
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