Security Audit
imagekit-io-automation
github.com/ComposioHQ/awesome-claude-skillsTrust Assessment
imagekit-io-automation received a trust score of 94/100, 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 Unversioned external MCP dependency.
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 | Unversioned external MCP dependency The skill explicitly relies on the `rube` Multi-tool Control Plane (MCP) hosted at `https://rube.app/mcp`. This dependency is unversioned and external, meaning the behavior, available tools, and security posture of the MCP can change at any time without explicit updates or version pinning within the skill. A compromise of the `rube.app` service could lead to the execution of malicious tools or instructions by the agent, posing a supply chain risk. Implement versioning or content-addressable references for external MCPs or services to ensure predictable and auditable behavior. Regularly audit the external service for security and integrity. Consider sandboxing or strict permission controls for interactions with external services. | LLM | SKILL.md:20 |
Scan History
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