Security Audit

memberspot-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

memberspot-automation received a trust score of 95/100, 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 Broad Rube MCP access enables extensive Memberspot operations.

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%

Behavioral Risk Signals

Filesystem Write

1 finding

Shell Execution

1 finding

Dynamic Code

1 finding

Excessive Permissions

1 finding

Security Findings1

Severity	Finding	Layer	Location
MEDIUM	Broad Rube MCP access enables extensive Memberspot operations The skill's manifest requires access to the entire Rube MCP (`mcp: ["rube"]`). The skill then instructs the LLM on how to use powerful Rube tools like `RUBE_MULTI_EXECUTE_TOOL` and `RUBE_REMOTE_WORKBENCH` to perform 'Memberspot operations'. While this is the skill's intended purpose, granting access to the full Rube MCP without more granular scope definition means that a compromised agent could be instructed to perform any Memberspot action (read, write, delete, etc.) that Rube supports, potentially leading to unauthorized data modification or deletion. The skill itself does not define or enforce finer-grained permissions within the Rube framework, increasing the attack surface if the agent is compromised via prompt injection. Consider if the `mcp` requirement can be made more granular, or if Rube itself offers mechanisms to scope tool access (e.g., `mcp: ["rube:memberspot:read_only"]`). If not, ensure robust prompt engineering and agent safeguards are in place to prevent misuse of these powerful tools.	LLM	SKILL.md:1

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