Security Audit

gladia-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

gladia-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 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%

Behavioral Risk Signals

Dynamic Code

1 finding

Security Findings1

Severity	Finding	Layer	Location
MEDIUM	Unpinned MCP dependency The skill's manifest declares a dependency on the 'rube' MCP without specifying a version. This can lead to unexpected behavior, breaking changes, or the introduction of vulnerabilities if the 'rube' MCP updates in a way that is incompatible or insecure with the skill's assumptions. Without version pinning, the skill's runtime environment might silently upgrade to a new, untested version of the dependency. Pin the 'rube' MCP dependency to a specific version or a version range (e.g., `{"mcp": ["rube@1.0.0"]}` or `{"mcp": ["rube@^1.0.0"]}`) to ensure consistent and predictable behavior and to mitigate risks from unvetted updates.	Static	SKILL.md:1

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