Security Audit

share_point-automation

github.com/ComposioHQ/awesome-claude-skills

AI SkillCommit 99e2a2951545

TRUSTED

Scanned 6 days ago

Critical

Immediate action required

High

Priority fixes suggested

Medium

Best practices review

Low

Acknowledged / Tracked

Trust Assessment

share_point-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 Unpinned Rube 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

100%

Dependency Graph

100%

LLM Behavioral Safety

93%

Security Findings1

Severity	Finding	Layer	Location
MEDIUM	Unpinned Rube MCP dependency The skill's manifest specifies a dependency on the 'rube' MCP without a version constraint. This allows any version of 'rube' to be used, which could lead to unexpected behavior, breaking changes, or the introduction of vulnerabilities if a future version of 'rube' is compromised or contains regressions. Pinning dependencies is a best practice for supply chain security. Pin the 'rube' MCP dependency to a specific, known-good version (e.g., `{"mcp": ["rube@1.2.3"]}`) in the skill's manifest to ensure consistent and secure behavior. Regularly review and update the pinned version.	LLM	SKILL.md:1

Scan History

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