Security Audit
peopledatalabs-automation
github.com/ComposioHQ/awesome-claude-skillsTrust Assessment
peopledatalabs-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 Broad Tool Execution Capabilities Exposed.
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
Behavioral Risk Signals
Security Findings1
| Severity | Finding | Layer | Location | |
|---|---|---|---|---|
| MEDIUM | Broad Tool Execution Capabilities Exposed The skill explicitly guides the AI agent to use `RUBE_MULTI_EXECUTE_TOOL` and `RUBE_REMOTE_WORKBENCH`. These tools, by design, allow for dynamic discovery and execution of a wide range of operations within the connected Peopledatalabs toolkit. While this is the intended functionality of the Composio platform, it means the skill grants the AI agent very broad operational capabilities. If the agent's reasoning is compromised (e.g., via prompt injection), an attacker could leverage these tools to perform unauthorized or malicious operations within Peopledatalabs, limited only by the permissions of the connected account. Implement robust input validation and authorization checks on the AI agent's side to ensure that tool calls, especially those involving broad execution capabilities like `RUBE_MULTI_EXECUTE_TOOL` and `RUBE_REMOTE_WORKBENCH`, align with the user's intent and are within authorized scope. Consider adding more granular permission controls or explicit whitelisting for specific Peopledatalabs operations if the underlying platform allows it, rather than relying solely on dynamic discovery and execution. | LLM | SKILL.md:56 |
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