Security Audit

workable-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

workable-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 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

93%

Dependency Graph

100%

LLM Behavioral Safety

100%

Security Findings1

Severity	Finding	Layer	Location
MEDIUM	Unpinned Rube MCP dependency The skill manifest requires the 'rube' MCP without specifying a version. This means that any future updates to the 'rube' MCP could introduce breaking changes, vulnerabilities, or malicious behavior without explicit review or consent, posing a supply chain risk. If the upstream 'rube' MCP becomes compromised or introduces malicious functionality, this skill would automatically inherit those risks. Pin the 'rube' MCP dependency to a specific version or version range in the manifest to ensure stability and security. For example, `{"mcp": ["rube@1.2.3"]}` or `{"mcp": ["rube@^1.0.0"]}`.	Static	SKILL.md:4

Scan History

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