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Multi-Agentic System Threat Modeling

多智能体系统威胁建模

Conduct comprehensive threat modeling for multi-agent systems using the Cloud Security Alliance (CSA) MAESTRO framework's 7-layer architecture and OWASP Multi-Agentic System Threat Modeling Guide v1.0.
基于云安全联盟（CSA）MAESTRO框架的七层架构与OWASP多智能体系统威胁建模指南v1.0，针对多智能体系统开展全面威胁建模。

Steps

步骤

  1. MAESTRO 7-Layer Architecture Mapping — Decompose the system into CSA's layered reference architecture:
    • Layer 7: Agent Ecosystem — User-facing applications, agent marketplace, business integrations
    • Layer 6: Security & Compliance — Cross-cutting security controls, compliance frameworks
    • Layer 5: Evaluation & Observability — Monitoring, metrics, anomaly detection, performance tracking
    • Layer 4: Deployment & Infrastructure — Containers, orchestration, cloud/on-premise resources
    • Layer 3: Agent Frameworks — Orchestration logic, agent-tool bindings, routing decisions
    • Layer 2: Data Operations — Memory stores, vector databases, RAG pipelines, context management
    • Layer 1: Foundation Models — Core LLMs, model APIs, inference engines
  2. Layer-Specific Threat Analysis — Identify threats unique to each MAESTRO layer using CSA taxonomy.
  3. Cross-Layer Threat Assessment — Analyze attack chains that span multiple layers (supply chain attacks, lateral movement, privilege escalation, data leakage cascades).
  4. Extended Multi-Agent Threats — Apply MAESTRO framework extensions for complex multi-agent scenarios:
    • Reasoning Collapse — Chain-of-thought breakdowns across agent delegation
    • Emergent Covert Coordination — Autonomous symbolic protocol development
    • Heterogeneous Multi-Agent Exploits — Coordinated attacks using diverse agent capabilities
    • Goal Drift in Delegated Chains — Intent mutation through agent handoffs
    • Trust Misuse Between Legitimate Agents — Strategic misreporting within valid roles
  5. Architecture Pattern Risk Assessment — Evaluate specific multi-agent patterns (supervisor-agent, hierarchical, distributed ecosystem, human-in-the-loop).
  6. Mitigation Strategy Development — Design layer-specific, cross-layer, and AI-specific security controls.
  1. MAESTRO七层架构映射 — 将系统分解为CSA的分层参考架构：
    • 第7层：Agent生态系统 — 面向用户的应用、Agent市场、业务集成
    • 第6层：安全与合规 — 跨域安全控制、合规框架
    • 第5层：评估与可观测性 — 监控、指标、异常检测、性能跟踪
    • 第4层：部署与基础设施 — 容器、编排、云/本地资源
    • 第3层：Agent框架 — 编排逻辑、Agent-工具绑定、路由决策
    • 第2层：数据操作 — 内存存储、向量数据库、RAG流水线、上下文管理
    • 第1层：基础模型 — 核心LLM、模型API、推理引擎
  2. 分层威胁分析 — 利用CSA分类法识别各MAESTRO层特有的威胁。
  3. 跨层威胁评估 — 分析跨多个层的攻击链（供应链攻击、横向移动、权限提升、数据泄露级联）。
  4. 扩展多智能体威胁 — 针对复杂多智能体场景应用MAESTRO框架扩展内容：
    • 推理崩溃 — Agent委托过程中的思维链断裂
    • 突发隐蔽协作 — 自主符号协议开发
    • 异构多智能体漏洞利用 — 利用多样化Agent能力发起协同攻击
    • 委托链中的目标偏移 — 通过Agent交接导致意图变异
    • 合法Agent间的信任滥用 — 有效角色内的战略性误报
  5. 架构模式风险评估 — 评估特定多智能体模式（监督者-Agent、分层式、分布式生态系统、人在回路）。
  6. 缓解策略制定 — 设计分层、跨层及AI专属的安全控制措施。

Output

输出

Use the finding format from 
templates/finding.md
. Produce:
  • MAESTRO 7-Layer Architecture Map — System decomposition across all layers
  • Layer-Specific Threat Assessment — Detailed analysis for each MAESTRO layer
  • Cross-Layer Attack Chain Analysis — Multi-layer threat scenarios
  • Extended Multi-Agent Threat Analysis — MAESTRO framework extensions
  • Architecture Pattern Risk Assessment — Pattern-specific vulnerabilities
  • Risk Prioritization Matrix — Likelihood vs. impact analysis
  • Layered Mitigation Strategy — Defense-in-depth recommendations
使用
templates/finding.md
中的发现格式生成以下内容：
  • MAESTRO七层架构图 — 全层系统分解图
  • 分层威胁评估报告 — 各MAESTRO层的详细分析
  • 跨层攻击链分析 — 多层威胁场景
  • 扩展多智能体威胁分析 — MAESTRO框架扩展内容
  • 架构模式风险评估 — 特定模式的漏洞
  • 风险优先级矩阵 — 可能性与影响分析
  • 分层缓解策略 — 纵深防御建议

OWASP References

OWASP参考资料

  • CSA MAESTRO Framework — 7-Layer Agentic AI Reference Architecture
  • OWASP Multi-Agentic System Threat Modeling Guide v1.0
  • OWASP Top 10 for Agentic Applications 2026
  • OWASP GenAI Security Project
  • CSA MAESTRO框架 — 七层Agentic AI参考架构
  • OWASP多智能体系统威胁建模指南v1.0
  • OWASP Agentic应用Top 10（2026）
  • OWASP GenAI安全项目