Trust Assessment
mailchimp received a trust score of 86/100, 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 Potential Command Injection via Unsanitized User Input.
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 13, 2026 (commit 13146e6a). 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 | Potential Command Injection via Unsanitized User Input The skill provides `curl` command templates that include placeholders for user-controlled input (e.g., `{list_id}`, `{campaign_id}`). If the AI agent directly substitutes untrusted user input into these placeholders without proper sanitization or validation, it could lead to command injection. An attacker could craft malicious input (e.g., `123/members; rm -rf /`) to execute arbitrary shell commands on the host system when the `curl` command is constructed and executed. This risk applies to all `curl` commands where user-controlled parameters are inserted directly into the shell command string. The AI agent should sanitize all user-provided input before substituting it into shell commands. This includes proper shell escaping for URL paths and JSON values, or using a dedicated API client library that handles parameter serialization securely. For URL paths, ensure input is URL-encoded and does not contain shell metacharacters. For JSON payloads, ensure user input is properly JSON-escaped. | LLM | SKILL.md:21 |
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