'Agent Safety Should Be a Runtime Contract': a title-level audit of 28,560 NeurIPS/ICML/ICLR papers finds an 8–12x train-vs-runtime imbalance

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This position paper argues that instilling safety during training (RLHF, DPO, Constitutional AI) is structurally insufficient for agents that execute code, mutate files and modify databases, and that safety must be a runtime contract enforced by the harness with two faces: preventive (sandboxes, permission gates, trajectory monitors) and evidential (gating task submission on hard proof — test runs, log captures, file diffs, citation grounding). It grounds this in four released datasets: a survey of 52 documented agent/LLM safety incidents, a false-completion audit with 31 non-contested cases, a trajectory-schema audit of 12 public agent systems and harnesses, and a title-level audit of all 28,560 papers accepted at NeurIPS/ICML/ICLR 2023–2025 showing a pooled 8–12x imbalance favoring training-time over runtime safety work.