Security Audit
conductor-validator
github.com/sickn33/antigravity-awesome-skillsTrust Assessment
conductor-validator received a trust score of 72/100, placing it in the Caution category. This skill has some security considerations that users should review before deployment.
SkillShield's automated analysis identified 1 finding: 1 critical, 0 high, 0 medium, and 0 low severity. Key findings include Excessive 'Bash' tool permission declared.
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 | |
|---|---|---|---|---|
| CRITICAL | Excessive 'Bash' tool permission declared The skill explicitly declares 'Bash' as an allowed tool in its manifest. This grants the AI agent the capability to execute arbitrary shell commands on the host system. This poses a critical security risk, as a malicious or cleverly crafted prompt could instruct the LLM to leverage this permission for data exfiltration, system modification, or further compromise. While the skill's purpose (validating project artifacts) might require file system interaction, full 'Bash' access is overly broad and provides an extensive attack surface. Restrict tool access to the absolute minimum necessary. Replace 'Bash' with more specific, sandboxed tools (e.g., dedicated file system APIs for 'read', 'list', 'check_existence') or a highly restricted 'Bash' wrapper that only permits a whitelist of safe commands and arguments. If 'Bash' is deemed unavoidable, implement stringent input validation and sanitization for any user-controlled arguments passed to it, and consider running the skill in a highly isolated environment. | LLM | SKILL.md:1 |
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