Security Audit

giphy-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

giphy-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 Generic Tool Execution via Rube MCP.

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

100%

Dependency Graph

100%

LLM Behavioral Safety

93%

Behavioral Risk Signals

Shell Execution

1 finding

Excessive Permissions

1 finding

Security Findings1

Severity	Finding	Layer	Location
MEDIUM	Generic Tool Execution via Rube MCP The skill documentation introduces `RUBE_MULTI_EXECUTE_TOOL` and `RUBE_REMOTE_WORKBENCH` as mechanisms for executing tools via the Rube MCP. While the skill guides the LLM to use these for Giphy-specific operations (e.g., by suggesting `use_case: "Giphy operations"` in `RUBE_SEARCH_TOOLS`), the execution tools themselves are generic and not inherently scoped to Giphy. If the Rube MCP is configured with other toolkits, an LLM could potentially deviate from the intended Giphy-only use and execute tools from other services, leading to broader access than intended by the skill's specific purpose. 1. Restrict Rube MCP Configuration: Ensure the Rube MCP instance used by the LLM is configured to only expose Giphy-related tools, or tools explicitly approved for the LLM's scope. 2. LLM Prompt Engineering: Reinforce in the LLM's system prompt that it must strictly adhere to the `use_case` and `toolkit` parameters to limit tool discovery and execution to Giphy. 3. Tool-level Scoping: If possible, enhance the `RUBE_MULTI_EXECUTE_TOOL` and `RUBE_REMOTE_WORKBENCH` to accept an explicit `toolkit` parameter that restricts execution to tools within that toolkit, overriding what `RUBE_SEARCH_TOOLS` might return.	LLM	SKILL.md:50

Scan History

Embed Code

[![SkillShield](https://skillshield.io/api/v1/badge/c370884056bc406c.svg)](https://skillshield.io/report/c370884056bc406c)