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Microsoft Copilot Studio — agentic threat model

5.7AIVSS 5.7 · Medium

Microsoft Copilot Studio presents a high-impact risk profile due to its deep integration with enterprise data via Microsoft 365 Graph and autonomous plugin execution capabilities, though this is heavily mitigated by Microsoft's robust enterprise-grade security controls and compliance frameworks.

OWASP AIVSS score rationale

AIVSS = (CVSS_Base + AARS) × Mitigation_Factor, where AARS = (10 − CVSS_Base) × (Factor_Sum / 10) × ThM
CVSS base 8.5AARS uplift 1.01Factor sum 6.7/10Threat ×1.0Mitigation ×0.6
Autonomy of Action
0.80
Goal-Driven Planning
0.70
Self-Modification
0.30
Dynamic Tool Use
0.80
Persistent Memory
0.60
Contextual Awareness
0.90
Dynamic Identity
0.70
Multi-Agent Interactions
0.80
Non-Determinism
0.60
Opacity & Reflexivity
0.50

Scored with the canonical OWASP AIVSS formula (AIVSS calculator reference); agentic risk factors estimated from the agent’s described capabilities.

MAESTRO 7-layer threat model

Per-layer threats for this agent. Layers tagged “not certain from listing” are general, caveated commentary where the public description didn’t pin that layer.

L1 · Foundation Models✓ mapped

Utilizes Microsoft's state-of-the-art foundation models (Azure OpenAI / GPT-4). Primary threats include prompt injection, model reprogramming, and indirect prompt injection via untrusted data sources integrated into the copilot.

L2 · Data Operations✓ mapped

Connects directly to diverse enterprise data sources and Microsoft 365 Graph. Risks include data exfiltration via RAG, unauthorized access to sensitive SharePoint/OneDrive files, and knowledge-base poisoning from untrusted external connectors.

L3 · Agent Frameworks✓ mapped

Provides a low-code environment for building autonomous agents and custom GPTs. Threat vectors include insecure tool/plugin integration, logic bypasses in the graphical orchestration flows, and unauthorized tool execution.

L4 · Deployment & Infrastructure✓ mapped

Hosted on Microsoft's secure Azure cloud infrastructure. While direct container/host compromise is highly mitigated by Azure's isolation, risks remain around tenant-to-tenant isolation and misconfigured API endpoints.

L5 · Evaluation & Observability✓ mapped

Includes built-in analytics and user controls. However, complex autonomous agent behaviors and multi-step plugin executions can create logging blind spots, making it difficult to audit malicious prompt injection payloads in real-time.

L6 · Security & Compliance (cross-cutting)✓ mapped

Benefits from Microsoft's enterprise compliance suite (Purview, DLP, IAM, and OAuth). The primary threat is misconfiguration of these access controls, allowing agents to act with elevated user privileges.

L7 · Agent Ecosystem✓ mapped

Integrates with Microsoft 365 Copilot and supports custom generative AI plugins. This creates a multi-agent ecosystem where a compromised custom plugin or external agent can abuse trust boundaries to access the broader M365 tenant.

MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).