Security Audit
teltel-automation
github.com/ComposioHQ/awesome-claude-skillsTrust Assessment
teltel-automation received a trust score of 82/100, 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 Skill advertises broad tool execution capabilities via Rube MCP, Unpinned dependency on 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
Behavioral Risk Signals
Security Findings2
| Severity | Finding | Layer | Location | |
|---|---|---|---|---|
| HIGH | Skill advertises broad tool execution capabilities via Rube MCP The skill documentation describes the `RUBE_REMOTE_WORKBENCH` tool as capable of "Bulk ops" and executing `run_composio_tool()`. This suggests that an LLM using this skill could be directed to execute a wide range of Composio tools through the Rube MCP, potentially leading to excessive permissions if not properly constrained by the underlying platform or user interaction. The scope of `run_composio_tool()` is not explicitly defined, but its name implies general Composio tool execution, which represents a powerful and potentially overly broad capability. Clarify and restrict the scope of `RUBE_REMOTE_WORKBENCH` and `run_composio_tool()`. Implement granular access controls within the Rube MCP or Composio platform to limit which tools can be executed and with what parameters. Ensure that LLM interactions requiring `RUBE_REMOTE_WORKBENCH` are subject to human approval or strict policy enforcement. | LLM | SKILL.md:80 | |
| MEDIUM | Unpinned dependency on Rube MCP The skill's manifest declares a dependency on the `rube` MCP without specifying a version. This means that any version of `rube` MCP could be used, including future versions that might introduce vulnerabilities, breaking changes, or malicious code. This lack of version pinning creates a supply chain risk, as the skill's behavior and security posture could change unexpectedly if the `rube` MCP dependency is updated. Pin the `rube` MCP dependency to a specific, known-good version or version range within the skill's manifest to mitigate risks from unexpected or malicious updates. Regularly review and update pinned dependencies. | LLM | SKILL.md:2 |
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