Agent Zero — agentic threat model
Agent Zero is a highly flexible, open-source multi-agent framework with capabilities for command execution and tool customization, presenting significant risks of tool misuse and cascading multi-agent failures, partially mitigated by its real-time interactive transparency.
OWASP AIVSS score rationale
| Autonomy of Action | 0.70 | |
| Goal-Driven Planning | 0.80 | |
| Self-Modification | 0.50 | |
| Dynamic Tool Use | 0.80 | |
| Persistent Memory | 0.90 | |
| Contextual Awareness | 0.70 | |
| Dynamic Identity | 0.40 | |
| Multi-Agent Interactions | 0.90 | |
| Non-Determinism | 0.70 | |
| Opacity & Reflexivity | 0.40 |
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 — The framework does not mandate a specific LLM, but supporting diverse foundation models exposes it to model-agnostic threats like prompt injection, adversarial reprogramming, and misaligned outputs.
Not certain from the listing — While persistent memory is highlighted, the underlying storage, vector database, and data ingestion pipelines are unspecified, leaving potential gaps for memory poisoning or unauthorized data exfiltration.
As an orchestration framework with customizable tools and persistent memory, Agent Zero is highly susceptible to tool misuse, insecure tool integration, and memory poisoning if malicious inputs manipulate the agent's execution path.
Not certain from the listing — The deployment environment is user-defined. If run locally or in unsandboxed containers, executing arbitrary commands poses severe risks of host compromise and privilege escalation.
The framework provides a transparent environment with real-time interaction, enabling users to guide actions and monitor execution, which serves as an active human-in-the-loop observability control.
Not certain from the listing — There is no mention of built-in enterprise security controls, role-based access control (RBAC), or compliance certifications in this open-source framework.
With explicit support for multi-agent cooperation, the ecosystem is vulnerable to agent-to-agent trust abuse, where a single compromised agent can propagate malicious commands or trigger cascading failures across the network.
MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).