Security Audit
mixpanel-automation
github.com/sickn33/antigravity-awesome-skillsTrust Assessment
mixpanel-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 Arbitrary JQL script execution via MIXPANEL_JQL_QUERY.
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 e36d6fd3). SkillShield performs automated 4-layer security analysis on AI skills and MCP servers.
Layer Breakdown
Behavioral Risk Signals
Security Findings1
| Severity | Finding | Layer | Location | |
|---|---|---|---|---|
| HIGH | Arbitrary JQL script execution via MIXPANEL_JQL_QUERY The `MIXPANEL_JQL_QUERY` tool allows execution of arbitrary JavaScript Query Language (JQL) scripts via its `script` parameter. If this parameter is populated directly from untrusted user input without proper sanitization or validation, a malicious user could inject arbitrary JQL code. This could lead to unauthorized data access, modification, or denial of service within the Mixpanel environment. While not local command injection, it represents arbitrary code execution on a remote system. 1. Implement strict validation and sanitization of the `script` parameter to ensure only safe and intended JQL constructs are allowed. 2. Prefer using pre-defined JQL scripts where possible, allowing users to select from a limited set of safe operations rather than providing arbitrary code. 3. Ensure the Mixpanel API key used by the Rube MCP connection has the minimum necessary permissions to execute JQL queries, limiting potential damage. 4. Add a clear warning in the skill's documentation about the dangers of executing untrusted JQL scripts. | LLM | SKILL.md:142 |
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