Security Audit

junglescout-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

junglescout-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, 1 high, 0 medium, and 0 low severity. Key findings include Potential for excessive permissions and command injection via RUBE_REMOTE_WORKBENCH.

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

85%

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
HIGH	Potential for excessive permissions and command injection via RUBE_REMOTE_WORKBENCH The skill documentation mentions `RUBE_REMOTE_WORKBENCH` for 'Bulk ops' using `run_composio_tool()`. The term 'workbench' often implies a broader, less constrained execution environment that could potentially allow arbitrary code execution, shell commands, or access to the underlying filesystem. If `RUBE_REMOTE_WORKBENCH` is not properly sandboxed and restricted to specific, safe operations, it could lead to excessive permissions and command injection, allowing an attacker to execute arbitrary commands or exfiltrate data from the host system. Clarify the security boundaries and sandboxing of `RUBE_REMOTE_WORKBENCH`. Ensure it only allows execution of explicitly defined and sandboxed Composio tools, and does not permit arbitrary code execution, shell commands, or unrestricted file system access. If arbitrary execution is intended, clearly document its implications and provide strong warnings about its use.	LLM	SKILL.md:65

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