AgentScope — agentic threat model
AgentScope is a highly capable multi-agent orchestration framework whose distributed execution, MCP integration, and automatic prompt tuning introduce significant risks of cascading agent-to-agent trust abuse and unauthorized tool execution if deployed without strict infrastructure-level sandboxing.
OWASP AIVSS score rationale
| Autonomy of Action | 0.70 | |
| Goal-Driven Planning | 0.80 | |
| Self-Modification | 0.60 | |
| Dynamic Tool Use | 0.80 | |
| Persistent Memory | 0.50 | |
| Contextual Awareness | 0.70 | |
| Dynamic Identity | 0.40 | |
| Multi-Agent Interactions | 1.00 | |
| Non-Determinism | 0.70 | |
| Opacity & Reflexivity | 0.60 |
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.
Not certain from the listing — AgentScope is model-agnostic, but its automatic prompt tuning feature could be vulnerable to prompt injection or adversarial reprogramming if untrusted inputs influence the tuning process.
Not certain from the listing — While it supports tools and MCP, specific data storage, vector databases, or RAG pipeline security controls are not detailed in the directory listing.
As an orchestration framework, primary risks include insecure tool integration via MCP, prompt injection exploiting automatic prompt tuning, and message-passing manipulation between agents.
Not certain from the listing — Distributed execution and actor-based distribution imply network-level communication, but specific sandboxing, containerization, or secret management controls are not detailed.
Features built-in monitoring and fault tolerance, which helps detect failures, but lacks explicit details on security-focused guardrails or anomaly detection for malicious agent behavior.
Not certain from the listing — As an open-source framework, security controls like identity management, access policies, and compliance audits are left to the deploying developer.
High risk of cascading failures and agent-to-agent trust abuse due to its explicit multi-agent orchestration, actor-based distributed execution, and Model Context Protocol integration.
MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).
These scores are auto-generated from public information (the agent's own listing, docs, and repository) using the canonical OWASP AIVSS formula and the MAESTRO framework — an estimate for guidance, not a penetration test, audit, or certification. See the scoring methodology. Are you the vendor? Factual corrections are free.