{
  "id": "PRG-2026-0201",
  "kind": "program",
  "label": "AI Agent Publication Boundary and Security Closure (APBSC)",
  "created_at": "2026-09-21",
  "updated_at": "2026-10-13",
  "values": {
    "eml_status": "STABLE",
    "eml_evidence_level": "E2",
    "eml_object_version": "0.1",
    "eml_canonical_url": "https://evemisslab.com/ai/programs/PRG-2026-0201/",
    "eml_provenance": {
      "source": "EveMissLab research collection: AI Agent Publication Boundary and Security Closure (真本體論14)",
      "extracted_by": "Splice (Claude Code), reading the open-source release's own manifests, locks and pooled outputs, and the hashes of the internal drafts",
      "extracted_at": "2026-10-13",
      "generator": "tools/extract_all.py",
      "claim_boundary": "status, evidence level and result type follow the source artifact's own stated claim boundary; nothing is upgraded beyond what the report supports"
    },
    "eml_summary": "What do AI coding agents carry from a private workspace into public repositories, and how can that be measured without anyone reading other people's leaks? Phase I (ten papers, 2026-09-21) built the vocabulary — the five-state information chain, the green-light fallacy, agent context as an egress surface, recoverability, warning levels — and RBPM, a researcher-blind algorithm whose only observer of repository content is a sealed machine process. Phase II (2026-10) ran it on fresh public samples of companies, organizations and individuals and found agent-related publication-boundary signals in every population. The study stops there by decision: going further would mean reading what people did not mean to publish. Algorithm, protocols, released features and reports are open source.",
    "eml_summary_zh": "AI coding agent 會把什麼從私人工作環境帶進公開倉庫？又要怎樣量測它，而不讓任何人去讀別人的外洩？第一階段（十篇論文，2026-09-21）建立詞彙——五狀態資訊鏈、綠燈謬誤、agent 脈絡即出口面、可恢復性、警示等級——以及 RBPM：一個研究者盲測的演算法，倉庫內容唯一的觀察者是封閉的機器程序。第二階段（2026-10）在企業、組織與個人的新抽公開樣本上執行它，每個族群都出現了與 agent 相關的公開邊界訊號。研究依決定停在這裡：再往下就等於去讀人們不打算公開的東西。演算法、協定、釋出特徵與報告已開源。",
    "eml_label_zh": "AI Agent 公開邊界與安全閉包（APBSC）",
    "eml_primary_domain": "AI Safety",
    "eml_domains": [
      "Privacy",
      "Agent Systems",
      "Evaluation"
    ],
    "eml_goals": [
      "Separate passing checks from closing the publication boundary: AI may observe ≠ may persist ≠ may publish.",
      "Measure agent-context exposure on real public repositories with no human or AI ever reading them.",
      "Show whether the problem exists for individuals, organizations and companies — existence, not prevalence."
    ],
    "eml_milestones": [
      "2026-09-20: exploratory code-search pilot.",
      "2026-09-21: ten Phase I papers (v0.1, internal drafts).",
      "2026-09-22: RBPM v0.8.3 frozen instrument, 60-repository company panel and 3×3 surface matrix.",
      "2026-10-13: Phase II — rounds F1–F4 (236 repositories) and P1–P2 (400 individuals), each frozen before fetching, label-locked and independently audited.",
      "2026-10-13: measurement closed by decision; open-source release EveMissLab/apbsc-rbpm and the integrated public edition v1.0."
    ],
    "eml_open_questions": [
      "Prevalence of any disclosure class and its trend (not measured).",
      "Whether AI-assisted repositories disclose more than matched non-AI ones (hypothesis).",
      "How much of each result belongs to the instrument rather than to the repositories: no independently written instrument has been run on the same frame."
    ],
    "eml_repositories": [
      "https://github.com/EveMissLab/apbsc-rbpm"
    ],
    "eml_external_sites": [
      "https://privacy.evemisslab.com"
    ],
    "eml_license": "code MIT; text, protocols and released data CC BY 4.0",
    "eml_ai_collaborators": [
      "AI collaboration recorded for the series; the collaborator is not named in the drafts",
      "Splice (Claude Code, Anthropic) — Phase II protocols, runners, audits, reports and the integrated edition"
    ],
    "eml_authors": [
      "Neo.K (EveMissLab)"
    ]
  },
  "canonical_url": "https://evemisslab.com/ai/programs/PRG-2026-0201/",
  "json": "/ai/programs/PRG-2026-0201/index.json",
  "relations": [
    {
      "id": "REL-2026-0501",
      "predicate": "belongs_to",
      "source": "RES-2026-0201",
      "target": "PRG-2026-0201",
      "status": "ACTIVE"
    },
    {
      "id": "REL-2026-0502",
      "predicate": "belongs_to",
      "source": "RES-2026-0202",
      "target": "PRG-2026-0201",
      "status": "ACTIVE"
    },
    {
      "id": "REL-2026-0503",
      "predicate": "belongs_to",
      "source": "RES-2026-0203",
      "target": "PRG-2026-0201",
      "status": "ACTIVE"
    }
  ],
  "snapshot": {
    "snapshot_id": "AI-SNAPSHOT-v0.1-58e716495670",
    "created_at": "2026-10-13T14:55:22Z",
    "format_version": "0.1",
    "sedb_baseline": "v0.4B contract; static source content/ai/",
    "generator_version": "evemisslab-com ai_research 0.1",
    "object_count": 179,
    "relation_count": 624,
    "artifact_count": 88
  }
}