Security Audit

amazon-automation

github.com/ComposioHQ/awesome-claude-skills

AI SkillCommit 27904475d127

TRUSTED

Scanned about 2 months ago

Critical

Immediate action required

High

Priority fixes suggested

Medium

Best practices review

Low

Acknowledged / Tracked

Trust Assessment

amazon-automation received a trust score of 85/100, placing it in the Mostly Trusted category. This skill has passed most security checks with only minor considerations noted.

SkillShield's automated analysis identified 1 finding: 0 critical, 0 high, 1 medium, and 0 low severity. Key findings include Unpinned dependency in manifest.

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 20, 2026 (commit 27904475). 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 dependency in manifest The skill's manifest declares a dependency on 'rube' without specifying a version constraint. This practice can introduce supply chain risks, as future updates to the 'rube' MCP could inadvertently introduce vulnerabilities, breaking changes, or malicious code. Without a pinned version, the skill would automatically use the latest available version, which might not have been vetted by the skill author. Pin the dependency to a specific version or a well-defined version range (e.g., `"rube@1.2.3"` or `"rube@^1.0.0"`) to ensure stability, predictability, and security against unexpected changes in upstream packages.	Static	SKILL.md

Scan History

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