Security Audit

render-automation

github.com/ComposioHQ/awesome-claude-skills

AI SkillCommit 99e2a2951545

TRUSTED

Scanned about 2 months ago

Critical

Immediate action required

High

Priority fixes suggested

Medium

Best practices review

Low

Acknowledged / Tracked

Trust Assessment

render-automation received a trust score of 93/100, 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 Unpinned Multi-Capability Provider (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

Manifest Analysis

100%

Static Code Analysis

93%

Dependency Graph

100%

LLM Behavioral Safety

100%

Security Findings1

Severity	Finding	Layer	Location
MEDIUM	Unpinned Multi-Capability Provider (MCP) Dependency The skill's manifest specifies a dependency on the 'rube' Multi-Capability Provider (MCP) without a pinned version. This means that any version of 'rube' could be used, including potentially vulnerable or malicious future versions, or versions with breaking changes. This introduces a supply chain risk as the skill's behavior and security posture could change unexpectedly if the 'rube' MCP is updated or compromised. Pin the 'rube' MCP dependency to a specific, known-good version in the manifest. For example, if versioning is supported, change `"mcp": ["rube"]` to `"mcp": ["rube@1.2.3"]` or use a content hash if available.	Static	SKILL.md:5

Scan History

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