Trust Assessment
n8n-node-configuration received a trust score of 85/100, placing it in the Mostly Trusted category. This skill has passed most security checks with only minor considerations noted.
SkillShield's automated analysis identified 1 finding: 0 critical, 1 high, 0 medium, and 0 low severity. Key findings include Skill teaches modification of executable code in n8n workflows.
The analysis covered 4 layers: Manifest Analysis, Static Code Analysis, Dependency Graph, LLM Behavioral Safety. All layers scored 70 or above, reflecting consistent security practices.
Last analyzed on May 1, 2026 (commit d85d0e24). SkillShield performs automated 4-layer security analysis on AI skills and MCP servers.
Layer Breakdown
Behavioral Risk Signals
Security Findings1
| Severity | Finding | Layer | Location | |
|---|---|---|---|---|
| HIGH | Skill teaches modification of executable code in n8n workflows The skill explicitly instructs the LLM on how to use the `n8n_update_partial_workflow` tool with the `patchNodeField` operation to modify the `jsCode` parameter of an n8n 'Code' node. This allows for arbitrary JavaScript code injection into an n8n workflow if the LLM is compromised via prompt injection or other means. An attacker could craft a prompt that causes the LLM to use this functionality to insert malicious code into a workflow's 'Code' node. Implement strict access controls and validation for the `n8n_update_partial_workflow` tool, especially when used with `patchNodeField` on sensitive fields like `parameters.jsCode` for 'Code' nodes. Consider requiring human approval for such operations or limiting the LLM's ability to modify executable code. Ensure any `find` and `replace` values derived from untrusted user input are thoroughly sanitized. | LLM | SKILL.md:460 |
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