Security Audit

digicert-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

digicert-automation received a trust score of 81/100, placing it in the Mostly Trusted category. This skill has passed most security checks with only minor considerations noted.

SkillShield's automated analysis identified 2 findings: 0 critical, 1 high, 1 medium, and 0 low severity. Key findings include Unpinned Rube MCP dependency, Skill instructs LLM to use broad Rube MCP tools.

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

78%

Behavioral Risk Signals

Shell Execution

1 finding

Dynamic Code

1 finding

Excessive Permissions

1 finding

Security Findings2

Severity	Finding	Layer	Location
HIGH	Skill instructs LLM to use broad Rube MCP tools The skill guides the LLM to utilize Rube MCP tools such as `RUBE_MULTI_EXECUTE_TOOL`, `RUBE_REMOTE_WORKBENCH`, and `RUBE_MANAGE_CONNECTIONS`. These tools provide extensive capabilities, allowing the LLM to discover and execute a wide range of Digicert operations and manage connections. If the LLM is compromised or misdirected, it could leverage these broad permissions to perform unauthorized actions, including creating/deleting certificates, managing users, or altering connection settings. The dynamic discovery via `RUBE_SEARCH_TOOLS` further amplifies this risk by allowing access to any current or future Digicert operation exposed by Rube. Implement stricter access controls or fine-grained permissions within the Rube MCP configuration for the Digicert toolkit, if possible. Alternatively, design skills to only expose and instruct the LLM to use specific, limited-scope Rube tools rather than general execution tools like `RUBE_MULTI_EXECUTE_TOOL` for all operations. Ensure robust guardrails are in place for the LLM to prevent misuse of these powerful capabilities.	LLM	SKILL.md:48
MEDIUM	Unpinned Rube MCP dependency The skill's manifest specifies a dependency on the 'rube' MCP without a version constraint. This can lead to unexpected behavior or security vulnerabilities if future versions of Rube MCP introduce breaking changes or security flaws. Relying on an unpinned dependency makes the skill susceptible to supply chain 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@^1.0.0"]`.	LLM	SKILL.md

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