TensorX
返回文献探索

Paper · arXiv 2605.14271

Auditing Agent Harness Safety

Chengzhi Liu, Yichen Guo, Yepeng Liu, Yuzhe Yang, Qianqi Yan, Xuandong Zhao, Wenyue Hua, Sheng Liu, Sharon Li, Yuheng Bu, Xin Eric Wang

56 upvotesMay 14, 2026arXiv 预印本
AI 摘要

LLM agents executing within execution harnesses can produce correct outputs while violating safety constraints during execution, necessitating trajectory-level auditing to ensure proper resource access and information flow across multi-agent systems.

execution harnessestool dispatchingresource allocationmulti-agent systemssafety benchmarkstrajectory auditingboundary complianceinformation-flow constraintsHarnessAuditHarnessAudit-Bench

Abstract

LLM agents increasingly run inside execution harnesses that dispatch tools, allocate resources, and route messages between specialized components. However, a harness can return a correct, benign answer over a trajectory that accesses unauthorized resources or leaks context to the wrong agent. Output-level evaluation cannot see these failures, yet most safety benchmarks score only final outputs or terminal states, even though many violations occur mid-trajectory rather than at termination. The central question is whether the harness respects user intent, permission boundaries, and information-flow constraints throughout execution. To address this gap, we propose HarnessAudit, a framework that audits full execution trajectories across boundary compliance, execution fidelity, and system stability, with a focus on multi-agent harnesses where these risks are most pronounced. We further introduce HarnessAudit-Bench, a benchmark of 210 tasks across eight real-world domains, instantiated in both single-agent and multi-agent configurations with embedded safety constraints. Evaluating ten harness configurations across frontier models and three multi-agent frameworks, we find that: (i) task completion is misaligned with safe execution, and violations accumulate with trajectory length; (ii) safety risks vary across domains, task types, and agent roles; (iii) most violations concentrate in resource access and inter-agent information transfer; and (iv) multi-agent collaboration expands the safety risk surface, while harness design sets the upper bound of safe deployment.

北京市昌平区探索星信息技术及软件开发工作室

京ICP备2026059466号