{
  "schema_version": 1,
  "builder_plan": {
    "scenario": "An agent reads external documents or tool responses that may contain malicious instructions.",
    "change": "Replay attacks and legitimate lookalikes in an isolated copy of your agent workflow.",
    "baseline": "Your existing checks with the same tasks, permissions, and tool responses.",
    "steps": [
      "Locate the paper's implementation and check its license, model support, data needs, and hardware requirements. Stop here if you cannot obtain the required artifacts.",
      "Save a small set of representative product tasks and expected outcomes. Keep evaluation tasks out of any training or tuning, and choose quality and cost limits before running.",
      "Run the baseline and the proposed change on identical inputs. Keep other settings fixed and repeat paired runs to expose variation.",
      "Save per-task outputs, failures, timings, and all usage costs. Review regressions before expanding the test."
    ],
    "measure": "Successful attacks missed, legitimate actions blocked, detection delay, and review cost.",
    "decision": "Keep the change only if it meets your preselected quality and latency limits and improves the metric you care about after setup and operating costs. Otherwise retain the baseline. This is an exploration plan, not a validated recommendation."
  },
  "builder_review": null,
  "arxiv_id": "2609.15293",
  "title": "Why LLM Agents Collapse Without Oversight: The Enforcement Gap as the Mechanism Behind Emergence World Failures",
  "summary": "Replaces reflexion-style self-critique that detects dangerous plan steps but never acts on them, by adding a conditional enforcement check (fewer than 20 lines) between the auditor's verdict and the controller's action. Costs are minimal for the check itself, but handling unparseable auditor verdicts requires a GRPO-trained enforcement controller, which adds training cost and a model dependency. Can fail through unreliable auditors, ambiguous or malformed verdicts, and any enforcement path that is bypassed outside the gated call site.",
  "rationale": "The core fix is a cheap, framework-agnostic conditional check with a reported fourfold attack-success reduction, making it directly adoptable on constrained infrastructure, while only the GRPO controller component merits smaller-scale testing.",
  "technique": "Audit enforcement gate for LLM agents",
  "family": "seguranca_e_guardrails",
  "recommendation": "adotar",
  "published": "2026-09-14",
  "as_of": "2026-10-18",
  "editorial_status": "indexed",
  "source_url": "https://arxiv.org/abs/2609.15293",
  "independent_implementations": 0,
  "total_implementations": 1,
  "stars": 0,
  "citations": 0,
  "claims": [
    {
      "claim_id": "claim-01",
      "statement": "Replaces reflexion-style self-critique that detects dangerous plan steps but never acts on them, by adding a conditional enforcement check (fewer than 20 lines) between the auditor's verdict and the controller's action. Costs are minimal for the check itself, but handling unparseable auditor verdicts requires a GRPO-trained enforcement controller, which adds training cost and a model dependency. Can fail through unreliable auditors, ambiguous or malformed verdicts, and any enforcement path that is bypassed outside the gated call site.",
      "basis": "inferred",
      "result": "",
      "baseline": "",
      "conditions": "",
      "source_url": "https://arxiv.org/abs/2609.15293",
      "source_page": null,
      "source_excerpt": ""
    },
    {
      "claim_id": "claim-02",
      "statement": "Reduces attack success by more than fourfold across frontier models and five agent frameworks in large-scale experiments.",
      "basis": "inferred",
      "result": "",
      "baseline": "",
      "conditions": "",
      "source_url": "https://arxiv.org/abs/2609.15293",
      "source_page": null,
      "source_excerpt": ""
    }
  ],
  "exposure_map": [
    {
      "dimension": "quality",
      "basis": "not_evaluated",
      "finding": "",
      "interpretation": "",
      "limitation": "",
      "next_check": "",
      "source_url": "",
      "source_page": null,
      "source_excerpt": ""
    },
    {
      "dimension": "compute",
      "basis": "not_evaluated",
      "finding": "",
      "interpretation": "",
      "limitation": "",
      "next_check": "",
      "source_url": "",
      "source_page": null,
      "source_excerpt": ""
    },
    {
      "dimension": "latency",
      "basis": "not_evaluated",
      "finding": "",
      "interpretation": "",
      "limitation": "",
      "next_check": "",
      "source_url": "",
      "source_page": null,
      "source_excerpt": ""
    },
    {
      "dimension": "operations",
      "basis": "not_evaluated",
      "finding": "",
      "interpretation": "",
      "limitation": "",
      "next_check": "",
      "source_url": "",
      "source_page": null,
      "source_excerpt": ""
    },
    {
      "dimension": "compatibility",
      "basis": "not_evaluated",
      "finding": "",
      "interpretation": "",
      "limitation": "",
      "next_check": "",
      "source_url": "",
      "source_page": null,
      "source_excerpt": ""
    },
    {
      "dimension": "security",
      "basis": "not_evaluated",
      "finding": "",
      "interpretation": "",
      "limitation": "",
      "next_check": "",
      "source_url": "",
      "source_page": null,
      "source_excerpt": ""
    },
    {
      "dimension": "data_and_training",
      "basis": "not_evaluated",
      "finding": "",
      "interpretation": "",
      "limitation": "",
      "next_check": "",
      "source_url": "",
      "source_page": null,
      "source_excerpt": ""
    },
    {
      "dimension": "reproducibility",
      "basis": "not_evaluated",
      "finding": "",
      "interpretation": "",
      "limitation": "",
      "next_check": "",
      "source_url": "",
      "source_page": null,
      "source_excerpt": ""
    }
  ],
  "risks": [],
  "minimum_test": [],
  "open_questions": [],
  "independent_tests": [],
  "lab_reproductions": [],
  "report_available": false,
  "validation_tier": "unknown",
  "evidence_tier": "unknown",
  "infrastructure_basis": "unknown",
  "equations": [
    {
      "anchor": "S2.Ex1",
      "label": "",
      "section": "2 Background and Theory",
      "role": "baseline",
      "latex": "\\text{ASR}\\;\\geq\\;1-p_{d}\\cdot p_{e}\\;\\geq\\;1-p_{e}.",
      "mathml": "<math display=\"block\"><mrow><mrow><mtext>ASR</mtext><mo lspace=\"0.558em\">≥</mo><mrow><mn> 1</mn><mo>−</mo><mrow><msub><mi>p</mi><mi>d</mi></msub><mo lspace=\"0.222em\" rspace=\"0.222em\">⋅</mo><msub><mi>p</mi><mi>e</mi></msub></mrow></mrow><mo>≥</mo><mrow><mn> 1</mn><mo>−</mo><msub><mi>p</mi><mi>e</mi></msub></mrow></mrow><mo lspace=\"0em\">.</mo></mrow></math>",
      "context": "Let <math display=\"inline\"><mrow><msub><mi>p</mi><mi>d</mi></msub><mo>∈</mo><mrow><mo stretchy=\"false\">[</mo><mrow><mn>0</mn><mo>,</mo><mn>1</mn></mrow><mo stretchy=\"false\">]</mo></mrow></mrow></math> be the per-round detection rate and <math display=\"inline\"><mrow><msub><mi>p</mi><mi>e</mi></msub><mo>∈</mo><mrow><mo stretchy=\"false\">[</mo><mrow><mn>0</mn><mo>,</mo><mn>1</mn></mrow><mo stretchy=\"false\">]</mo></mrow></mrow></math> the probability the controller halts upon a detected flag. Under the advisory architecture with attacker persistence map <math display=\"inline\"><mi>σ</mi></math>:",
      "headline": "",
      "explanation": "",
      "objective": "",
      "symbols": {},
      "evidence": "",
      "evidence_url": "",
      "source_url": ""
    },
    {
      "anchor": "A1.Ex2",
      "label": "",
      "section": "Appendix A Proofs",
      "role": "proposed_method",
      "latex": "\\text{ASR}\\;\\geq\\;1-p_{d}\\cdot p_{e}",
      "mathml": "<math display=\"block\"><mrow><mtext>ASR</mtext><mo lspace=\"0.558em\">≥</mo><mrow><mn> 1</mn><mo>−</mo><mrow><msub><mi>p</mi><mi>d</mi></msub><mo lspace=\"0.222em\" rspace=\"0.222em\">⋅</mo><msub><mi>p</mi><mi>e</mi></msub></mrow></mrow></mrow></math>",
      "context": "The attack succeeds at round <math display=\"inline\"><mi>t</mi></math> iff <math display=\"inline\"><mrow><msup><mi>π</mi><mrow><mo stretchy=\"false\">(</mo><mi>t</mi><mo stretchy=\"false\">)</mo></mrow></msup><mo>∈</mo><msub><mi mathvariant=\"normal\">Π</mi><mtext>adv</mtext></msub></mrow></math> and the loop has not halted. Since <math display=\"inline\"><mi>σ</mi></math> maps to <math display=\"inline\"><msub><mi mathvariant=\"normal\">Π</mi><mtext>adv</mtext></msub></math> and the controller only halts when <math display=\"inline\"><mrow><mrow><msub><mi>D</mi><mi>t</mi></msub><mo lspace=\"0.222em\" rspace=\"0.222em\">⋅</mo><msub><mi>E</mi><mi>t</mi></msub></mrow><mo>=</mo><mn>1</mn></mrow></math>, the survival probability per round is <math display=\"inline\"><mrow><mn>1</mn><mo>−</mo><mrow><msub><mi>p</mi><mi>d</mi></msub><mo lspace=\"0.222em\" rspace=\"0.222em\">⋅</mo><msub><mi>p</mi><mi>e</mi></msub></mrow></mrow></math>. Over <math display=\"inline\"><mi>T</mi></math> rounds, the attack reaches the executor with probability at least <math display=\"inline\"><msup><mrow><mo stretchy=\"false\">(</mo><mrow><mn>1</mn><mo>−</mo><mrow><msub><mi>p</mi><mi>d</mi></msub><mo lspace=\"0em\" rspace=\"0em\">​</mo><msub><mi>p</mi><mi>e</mi></msub></mrow></mrow><mo stretchy=\"false\">)</mo></mrow><mi>T</mi></msup></math>, and given <math display=\"inline\"><msub><mi mathvariant=\"normal\">Π</mi><mtext>adv</mtext></msub></math>-membership at the executor, the attacker realises harm. Hence:",
      "headline": "",
      "explanation": "",
      "objective": "",
      "symbols": {},
      "evidence": "",
      "evidence_url": "",
      "source_url": ""
    }
  ],
  "equations_status": "selected",
  "core_kind": "formula",
  "equations_fetched_at": "2026-10-06",
  "equations_source_url": "",
  "equations_source_sha256": "",
  "exposures_reviewed_at": "",
  "exposures_source_sha256": ""
}