{
  "id": 10591,
  "url": "https://arxiv.org/abs/2607.13716v1",
  "title": "CAVA: Canonical Action Verification and Attestation for Runtime Governance of Agentic AI Systems",
  "summary": "Agentic AI systems increasingly act through heterogeneous runtimes: local coding hooks, SDK tools, browser automation, managed-agent traces, API gateways, and workflow engines. A single operational act such as publishing code, changing identity state, moving money, or exporting data may therefore be represented by many incompatible runtime records. This makes a basic governance question difficult to answer: what action was actually approved, what evidence binds the approval to execution, and can",
  "authors": "Zexun Wang",
  "category": "research",
  "topics": "regulation,jobs-economy,agents-autonomy",
  "orgs": null,
  "regions": null,
  "published_at": "2026-07-15T11:34:34.000Z",
  "fetched_at": "2026-07-16T05:10:56.605Z",
  "source_slug": "arxiv-ethics",
  "source_name": "arXiv",
  "source_homepage": "https://arxiv.org",
  "ethics_ai_record_url": "https://ethics.ai/record/10591",
  "original_url": "https://arxiv.org/abs/2607.13716v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}