---
id: 20260919-T0-04
title: "MAGS：多Agent自动形式化验证，为代码Agent输出提供安全保障"
title_en: "MAGS: Multi-Agent Auto-Formalization Guarantees Safety for Agentic Code Outputs"
url: https://ai.daily.yangsir.net/daily/20260919-T0-04
issue_date: 2026-09-19
publish_date: 2026-09-18T04:00:00.000Z
category: research
source_name: "arXiv cs.AI"
source_url: https://arxiv.org/abs/2609.19391
---

# MAGS：多Agent自动形式化验证，为代码Agent输出提供安全保障

arXiv论文提出MAGS方法，针对LLM编程Agent生成复杂程序时人工审查困难、安全风险上升的问题。现有方法如模糊测试、静态分析和LLM-as-a-Verifier各有局限，MAGS通过多Agent协作进行自动形式化验证，为Agent输出提供安全保障。具体技术方案和实验数据参见论文全文。

## English Version

**MAGS: Multi-Agent Auto-Formalization Guarantees Safety for Agentic Code Outputs**

A paper on arXiv proposes MAGS, a method addressing the safety risks of LLM coding agents generating complex programs at a scale that makes thorough human review difficult. Existing approaches like fuzz testing, static analysis, and LLM-as-a-Verifier have limitations. MAGS uses multi-agent auto-formalization to guarantee safety for agentic outputs. Technical details and experimental data are in the full paper.

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**来源**：[arXiv cs.AI](https://arxiv.org/abs/2609.19391)

**详情页**：https://ai.daily.yangsir.net/daily/20260919-T0-04

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