guizang-social-card-skill — agentic threat model
This agent is a specialized design-generation skill with low agentic risk, acting primarily as a deterministic asset generator with minimal autonomy or external tool access.
OWASP AIVSS score rationale
| Autonomy of Action | 0.20 | |
| Goal-Driven Planning | 0.30 | |
| Self-Modification | 0.00 | |
| Dynamic Tool Use | 0.10 | |
| Persistent Memory | 0.10 | |
| Contextual Awareness | 0.40 | |
| Dynamic Identity | 0.00 | |
| Multi-Agent Interactions | 0.10 | |
| Non-Determinism | 0.50 | |
| Opacity & Reflexivity | 0.30 |
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.
Utilizes Claude Code / Codex foundation models. Primary threats include prompt injection designed to bypass template constraints or generate inappropriate/copyright-infringing visual layouts.
Not certain from the listing — processes user-provided articles, scripts, screenshots, and videos. Risks include processing malicious input files (e.g., polyglot files or exploit payloads disguised as media) and potential data leakage of sensitive input drafts.
Operates as a skill within Claude Code. Vulnerabilities are limited to how the framework orchestrates the template rendering and whether input parameters can trigger command injection during image/video processing.
Not certain from the listing — depends entirely on the host environment running Claude Code. If executed locally or in an unsandboxed container, malicious inputs exploiting image rendering libraries could lead to local code execution.
Not certain from the listing — likely lacks dedicated guardrails or observability for generated content, relying instead on the parent framework's safety filters to block harmful outputs.
As an open-source skill, it lacks built-in enterprise compliance, access controls, or audit logging, shifting all security and licensing compliance responsibilities to the end-user.
Designed as a self-contained skill with bundled templates. It has no native multi-agent coordination or marketplace interactions, minimizing ecosystem-level cascading risks.
MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).