# HazardAuditor：从可执行威胁到更安全的计算机使用智能体

- 来源：HuggingFace Daily Papers（社区热门论文）
- 发布时间：2026-09-14 08:00
- AIHOT 分数：44
- AIHOT 链接：https://aihot.news/items/cmu27n6l7001orove224i5su7
- 原文链接：https://arxiv.org/abs/2609.15134

## AI 摘要

HazardAuditor 是一个面向计算机使用智能体的执行级安全框架，可在受控环境中运行 Claude Code、Codex、Hermes、OpenClaw 等异构智能体，并把交互归一化为统一事件表示以支持跨框架监督。

## 正文

Computer-use agents increasingly interact with browsers, terminals, file systems, and external services, introducing safety risks that emerge through runtime behavior rather than generated content alone. Existing guard models target static prompts and responses and are poorly suited to agent execution; existing executable safety platforms produce evaluation verdicts rather than the normalized supervision a guard model needs to learn across heterogeneous agent frameworks. We introduce HazardAuditor, an execution-grounded framework that closes both gaps. Its infrastructure runs heterogeneous agents (Claude Code, Codex, Hermes, and OpenClaw) in controlled environments and normalizes their interactions into a canonical event representation for cross-framework supervision. We further observe that token-level post-training objectives create a structural mismatch for generative guards, causing longer rationales to dominate gradient updates. Guard Policy Optimization (GuardPO) addresses this by converting deterministic safety outcomes into sequence-level advantages and normalizing rationale and verdict regions, making the safety decision the effective unit of optimization. Across multiple benchmarks and heterogeneous computer-use systems, HazardAuditor improves accuracy by up to 16.5 percentage points over the strongest prior guard. Code, models, and evaluation artifacts will be available at https://yunhao-feng.github.io/HazardAuditor/.