LobeChat — agentic threat model
LobeChat is a highly extensible, open-source multi-model chat platform whose primary risk lies in its plugin system and the management of sensitive API keys across multiple LLM providers. Its open-source nature allows for auditing, but self-deployment requires careful infrastructure sandboxing to prevent tool/plugin abuse.
OWASP AIVSS score rationale
| Autonomy of Action | 0.40 | |
| Goal-Driven Planning | 0.30 | |
| Self-Modification | 0.20 | |
| Dynamic Tool Use | 0.70 | |
| Persistent Memory | 0.50 | |
| Contextual Awareness | 0.60 | |
| Dynamic Identity | 0.30 | |
| Multi-Agent Interactions | 0.40 | |
| Non-Determinism | 0.70 | |
| 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.
Supports multiple foundation models (multi-model support). Risks include adversarial prompt injection bypassing system instructions, and model-specific vulnerabilities depending on which external API is connected.
Not certain from the listing — LobeChat supports custom agents which may involve RAG or local data storage, but specific vector database integrations or data lineage controls are not detailed in the directory listing.
Features an extensible plugin system and custom agent creation. This introduces significant risks of tool misuse, insecure tool integration, and remote code execution if third-party plugins are not properly sandboxed.
Supports cloud deployment and self-hosting. Key risks include exposure of service endpoints, container compromise, and the theft of stored API keys used to access various LLM providers.
Not certain from the listing — No specific evaluation, logging, or guardrail mechanisms are mentioned in the directory listing to monitor agent behavior or detect drift.
Not certain from the listing — While it supports cloud deployment, specific identity, authorization, or compliance controls (like SOC2 or NIST alignment) are not specified in the listing.
Allows users to create custom agents and leverage a plugin system. Risks include the execution of malicious or compromised plugins from the ecosystem, leading to cascading failures or data exfiltration.
MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).