Security Audit

ip2location-automation

github.com/ComposioHQ/awesome-claude-skills

AI SkillCommit 99e2a2951545

TRUSTED

Scanned 2 months ago

Critical

Immediate action required

High

Priority fixes suggested

Medium

Best practices review

Low

Acknowledged / Tracked

Trust Assessment

ip2location-automation received a trust score of 78/100, 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 Potential Arbitrary Code Execution via RUBE_REMOTE_WORKBENCH, Reliance on External MCP and Toolkits (Supply Chain Risk).

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

78%

Dependency Graph

100%

LLM Behavioral Safety

100%

Behavioral Risk Signals

Network Access

1 finding

Shell Execution

1 finding

Dynamic Code

1 finding

Security Findings2

Severity	Finding	Layer	Location
HIGH	Potential Arbitrary Code Execution via RUBE_REMOTE_WORKBENCH The skill's 'Quick Reference' section mentions `RUBE_REMOTE_WORKBENCH` for 'Bulk ops' using `run_composio_tool()`. This phrasing suggests a capability for executing complex operations or scripts. If `run_composio_tool()` allows the execution of arbitrary scripts or commands provided by the LLM or an attacker, it could lead to command injection or arbitrary code execution within the remote workbench environment. The lack of specific details about the security model and sandboxing of this tool raises a significant concern regarding its potential for misuse. Clarify the exact capabilities and security model of `RUBE_REMOTE_WORKBENCH` and `run_composio_tool()`. Ensure that any execution environment is strictly sandboxed and isolated. Implement robust input validation and sanitization for all arguments passed to `run_composio_tool()` to prevent arbitrary code or command injection. Consider implementing strict allow-listing for commands or scripts if possible, rather than a broad execution capability.	Static	SKILL.md:69
MEDIUM	Reliance on External MCP and Toolkits (Supply Chain Risk) The skill explicitly relies on external services for its core functionality: `rube.app/mcp` for the MCP server and `composio.dev` for toolkit documentation and underlying tools. This introduces a significant supply chain risk. A compromise of either `rube.app` or `composio.dev` could lead to the delivery of malicious tools, altered schemas, or instructions to the LLM, potentially resulting in data exfiltration, unauthorized actions, or further system compromise. The security of this skill is directly dependent on the security posture and trustworthiness of these third-party entities. Implement robust vetting processes for all third-party dependencies and external services. Continuously monitor the security posture and reputation of `rube.app` and `composio.dev`. Consider implementing runtime checks, strict sandboxing, or network egress filtering for tools retrieved from external sources to limit their potential impact in case of a supply chain compromise. Ensure that all communications with these external services are secured with strong encryption and authentication.	Static	SKILL.md:31

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