Security Audit
shipengine-automation
github.com/ComposioHQ/awesome-claude-skillsTrust Assessment
shipengine-automation received a trust score of 95/100, placing it in the Trusted category. This skill has passed all critical security checks and demonstrates strong security practices.
SkillShield's automated analysis identified 1 finding: 0 critical, 0 high, 1 medium, and 0 low severity. Key findings include Skill enables broad Shipengine API access.
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 February 17, 2026 (commit 99e2a295). SkillShield performs automated 4-layer security analysis on AI skills and MCP servers.
Layer Breakdown
Behavioral Risk Signals
Security Findings1
| Severity | Finding | Layer | Location | |
|---|---|---|---|---|
| MEDIUM | Skill enables broad Shipengine API access The skill describes how to use `RUBE_MULTI_EXECUTE_TOOL` to perform 'Shipengine operations'. This tool, when used with an underlying Shipengine connection that has broad permissions, could allow an attacker to manipulate the LLM into performing a wide range of actions within Shipengine, such as creating/modifying shipments, accessing customer data, or incurring costs. The skill itself does not enforce least privilege principles for the underlying API connection, relying on the Rube MCP setup. Ensure the Shipengine connection configured via `RUBE_MANAGE_CONNECTIONS` uses API keys or OAuth tokens with the principle of least privilege, granting only the necessary permissions for the skill's intended functionality. Implement strict input validation and sanitization for `tool_slug` and `arguments` passed to `RUBE_MULTI_EXECUTE_TOOL` to prevent arbitrary operation execution by a compromised LLM. | LLM | SKILL.md:40 |
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