arXiv:2608.23858cs.CRcs.AI2026-08

分析谷歌购物代理支付协议的安全风险,发现签名无法保证用户真实意图。

Beyond the Mandate: A Systematic Security Analysis of the Agent Payments Protocol (AP2)

论文配图:Beyond the Mandate: A Systematic Security Analysis of the Agent Payments Protocol (AP2)
图 1 · 摘自论文原文
  • 分阶段拆解支付流程,构建五类部署架构与威胁模型
  • 识别48种威胁,其中8个在特定架构中属高风险
  • 自建测试床验证高危攻击与防护方案,适合安全研究人员参考

谷歌推出的代理支付协议(AP2)使大语言模型驱动的购物代理能代表用户授权并执行支付。其签发的结账与支付指令保障了签名后数据的完整性,但签名前的代理交互和外部输入(如A2A消息、MCP工具调用)未受保护。已有研究揭示AP2 v0.1存在重放和提示注入攻击。AP2 v0.2虽修复部分问题,但引入新能力与部署假设,需重新评估。本文基于角色、交易生命周期、部署架构与信任边界,系统分析AP2 v0.2。将生命周期划分为五个阶段,定义五种部署架构,使用MAESTRO框架建模四类威胁者、十一处攻击面、十八项攻击能力及六项攻击目标,生成涵盖五类攻击家族的48项威胁。采用人工智能漏洞评分系统(AIVSS)评估,发现八个威胁在至少一种架构中达高风险等级。因无完整公开部署实例,我们搭建覆盖全部五种架构的测试床,开发五项概念验证演示,覆盖全部八项高风险威胁及其缓解措施,并设计一个部署感知扫描器,可映射静态一致性、跨角色一致性和对抗性检查适用的威胁。分析表明,仅凭有效指令签名,仍不足以确保代理支付交易反映用户真实意图,若签名前上下文被操控,则存在严重风险。

原文摘要 · Abstract (English)

The Agent Payments Protocol (AP2), introduced by Google, enables large language model (LLM)-driven shopping agents to authorize and execute payments on behalf of users. Its signed Checkout and Payment Mandates protect the integrity of transaction data after signing. Agent interactions and external inputs that shape a transaction before authorization remain outside that protection, including Agent-to-Agent Protocol (A2A) messages and Model Context Protocol (MCP) tool calls. Prior work identified replay and prompt-injection attacks in AP2 v0.1. AP2 v0.2 addresses some of these issues but adds capabilities and deployment assumptions that require renewed analysis. We present a systematic security analysis of AP2 v0.2 based on its roles, transaction lifecycle, deployment architectures, and trust boundaries. We divide the lifecycle into five phases and identify five deployment architectures. Using MAESTRO (Multi-Agent Environment, Security, Threat, Risk, Outcome), we model four threat actors, eleven attack surfaces, eighteen adversary capabilities, and six attacker goals. The resulting catalog contains 48 threats spanning five attack families. We score these threats with the Artificial Intelligence Vulnerability Scoring System (AIVSS), identifying eight that reach the High band in at least one architecture. Because no complete public AP2 deployment was available, we build a testbed spanning all five architectures and develop five proof-of-concept demonstrations covering all eight High-risk threats and their mitigations. We also develop a deployment-aware scanner that maps applicable threats to static, cross-role consistency, and adversarial checks. Our analysis shows that valid mandate signatures alone do not ensure that an agent-mediated transaction reflects the user's intent when its pre-authorization context is manipulated.

支付安全LLM代理威胁建模漏洞分析

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