Security Audit

honeybadger-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

honeybadger-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 Agent granted broad access to Honeybadger operations.

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

Shell Execution

1 finding

Dynamic Code

1 finding

Excessive Permissions

1 finding

Security Findings1

Severity	Finding	Layer	Location
HIGH	Agent granted broad access to Honeybadger operations The skill instructs the agent to dynamically discover and execute any available Honeybadger operations via `RUBE_SEARCH_TOOLS`, `RUBE_MULTI_EXECUTE_TOOL`, and `RUBE_REMOTE_WORKBENCH`. This design pattern grants the agent overly broad access to the connected Honeybadger account. If the agent is compromised or misused, it could perform unauthorized actions (e.g., delete projects, modify settings) or exfiltrate sensitive data (e.g., error logs containing PII) that Honeybadger collects. The skill does not define any scope or restriction on the types of operations the agent can perform, leading to excessive permissions. Implement strict access controls and scope limitations for the agent's interaction with the Rube MCP and Honeybadger toolkit. Ensure the agent can only discover and execute a predefined, minimal set of necessary operations. Consider using a proxy or wrapper that filters tool calls and arguments based on a whitelist of allowed actions.	LLM	SKILL.md:40

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