Trust Assessment
zoominfo received a trust score of 95/100, placing it in the Trusted category. This skill has passed all critical security checks and demonstrates strong security practices.
SkillShield's automated analysis identified 1 finding: 0 critical, 0 high, 1 medium, and 0 low severity. Key findings include Unsanitized environment variable interpolation in JSON payload.
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 | |
|---|---|---|---|---|
| MEDIUM | Unsanitized environment variable interpolation in JSON payload The `curl` command provided as an example for authentication directly interpolates the `ZOOMINFO_USERNAME` and `ZOOMINFO_PASSWORD` environment variables into a JSON string without proper escaping. If these environment variables contain malicious JSON fragments (e.g., `", "malicious_field": "value"`), it could lead to JSON injection. This could potentially alter the API request, leading to data exfiltration (e.g., by adding a callback URL) or unexpected behavior if the ZoomInfo API processes additional or malformed fields. While these are 'required env vars', a robust skill should sanitize all external inputs, including environment variables, before embedding them into structured data. When constructing JSON payloads from variables in shell scripts, use a JSON parser/builder like `jq` to ensure proper escaping of values. For example: `jq -n --arg u "$ZOOMINFO_USERNAME" --arg p "$ZOOMINFO_PASSWORD" '{username: $u, password: $p}'` and pass its output to `curl -d`. | LLM | SKILL.md:10 |
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