AutoGLM Rumination — agentic threat model
AutoGLM Rumination exhibits moderate-to-high agentic risk due to its autonomous planning, web search capabilities, and task automation (such as travel planning), which could be exploited via prompt injection from untrusted web sources.
OWASP AIVSS score rationale
| Autonomy of Action | 0.70 | |
| Goal-Driven Planning | 0.80 | |
| Self-Modification | 0.10 | |
| Dynamic Tool Use | 0.60 | |
| Persistent Memory | 0.30 | |
| Contextual Awareness | 0.70 | |
| Dynamic Identity | 0.20 | |
| Multi-Agent Interactions | 0.10 | |
| Non-Determinism | 0.70 | |
| Opacity & Reflexivity | 0.80 |
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.
Powered by Zhipu's proprietary GLM-Z1-Air and GLM-4-Air-0414 models. Risks include adversarial prompt injection, model reprogramming, and misaligned outputs, which are critical given its autonomous research and planning capabilities.
Not certain from the listing — details on vector stores or RAG data pipelines are not specified, but its web search and deep research capabilities inherently expose the agent to data poisoning and prompt injection via retrieved web content.
Not certain from the listing — the orchestration framework is proprietary to Zhipu AI. The agent plans multi-step tasks (travel, research), presenting risks of tool misuse or insecure tool integration during web searches and automation.
Not certain from the listing — hosting and sandboxing details are proprietary. Mobile app and web deployment introduce standard client-side and API security risks, but sandboxing of the execution environment is unspecified.
Not certain from the listing — no details are provided regarding guardrails, logging, or real-time monitoring of the agent's execution or outputs.
Not certain from the listing — compliance certifications (like SOC2) or specific identity/authorization controls are not mentioned in the public directory listing.
Not certain from the listing — while it acts as an autonomous assistant, there is no explicit mention of multi-agent coordination or marketplace interactions.
MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).