Paper 2605.14271
Auditing Agent Harness Safety
- Published
- May 2026
- Research lab
- Independent
- Citations
- 1
- GitHub
- 51 stars
01 In brief
Summary
This paper introduces HarnessAudit, a framework for auditing LLM agent execution harnesses, and HarnessAudit-Bench, a benchmark of 210 tasks across 8 domains.
The framework evaluates full execution trajectories on three layers: boundary compliance (tool, resource, and information-flow violations), execution fidelity (action validity and task completion), and system stability under perturbations like indirect injection and ambiguous goals.
Evaluation of ten harness configurations across frontier models and three multi-agent frameworks reveals that task completion is misaligned with safe execution, violations increase with trajectory length, and safety risks vary by domain and role.
Most violations concentrate in resource access and inter-agent information transfer.
Multi-agent collaboration expands the safety risk surface, while harness design sets the upper bound of safe deployment.
The best overall safety score is 0.32, indicating substantial room for improvement.
02 From the paper
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.