Huobidex — agentic threat model
Huobidex is a human-curated web directory with zero agentic capabilities, presenting no AI-specific security risks. Its threat profile is entirely limited to traditional web application vulnerabilities, such as malicious link submissions or database injection.
OWASP AIVSS score rationale
| Autonomy of Action | 0.00 | |
| Goal-Driven Planning | 0.00 | |
| Self-Modification | 0.00 | |
| Dynamic Tool Use | 0.00 | |
| Persistent Memory | 0.00 | |
| Contextual Awareness | 0.00 | |
| Dynamic Identity | 0.00 | |
| Multi-Agent Interactions | 0.00 | |
| Non-Determinism | 0.00 | |
| Opacity & Reflexivity | 0.00 |
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.
The system does not utilize any foundation models or perform model inference, eliminating model-specific threats like adversarial prompt injection, model stealing, or data poisoning.
Data operations are limited to a standard database storing user-submitted tool names, URLs, and descriptions. The primary threat is database poisoning or malicious URL submission (XSS/phishing links) rather than vector store or embedding attacks.
No agentic orchestration framework, memory systems, or tool-calling mechanisms are implemented, removing risks associated with insecure tool integration or autonomous execution.
Hosted as a standard server-rendered Next.js website behind HTTPS. Standard web infrastructure threats apply (e.g., server compromise, DDoS, dependency vulnerabilities), but there is no AI sandbox or runtime environment to secure.
No AI-specific evaluation or guardrails are present. Quality control relies entirely on a human editorial review queue for maker-submitted products before publication.
Not certain from the listing — standard web security practices (like input sanitization, CSRF protection, and access controls for editors) are assumed but not detailed. Compliance is limited to standard web data privacy regulations.
The system does not participate in any multi-agent ecosystem or marketplace interactions, eliminating risks of cascading agent failures or autonomous trust abuse.
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 — every score is re-derived by the same automated method as an agent's public evidence changes.