unocss — agentic threat model
The UnoCSS skill presents a very low agentic risk profile, acting primarily as a passive code-generation assistant for styling. Its primary security boundaries lie in preventing CSS injection or malicious styling configurations from being integrated into downstream applications.
OWASP AIVSS score rationale
| Autonomy of Action | 0.10 | |
| Goal-Driven Planning | 0.10 | |
| Self-Modification | 0.00 | |
| Dynamic Tool Use | 0.10 | |
| Persistent Memory | 0.00 | |
| Contextual Awareness | 0.30 | |
| Dynamic Identity | 0.00 | |
| Multi-Agent Interactions | 0.10 | |
| Non-Determinism | 0.40 | |
| 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.
Not certain from the listing — the underlying LLM is not specified, but it is vulnerable to standard model risks like prompt injection which could alter the generated CSS rules or inject malicious styles.
Not certain from the listing — the training or RAG data likely consists of UnoCSS documentation and presets. Poisoning this reference data could lead to the generation of broken or insecure styling configurations.
The agent acts as a styling skill/reference surface. Framework risks are low as it lacks complex planning or autonomous tool execution, though insecure integration into a parent developer agent could lead to downstream code injection.
Not certain from the listing — deployment details are unspecified. If hosted in an unsandboxed environment, vulnerabilities in the execution of the parent agent could be exploited, though this skill itself is low-risk.
Not certain from the listing — there is no mention of built-in guardrails, logging, or observability to detect if the generated CSS contains malicious payloads or exploits.
Not certain from the listing — no compliance certifications, access controls, or identity management features are described for this open-source skill.
As an 'antfu skill', it is designed to integrate into a broader developer agent ecosystem. The primary risk is trust abuse, where a compromised parent agent relies blindly on this skill's styling outputs.
MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).