Trust Assessment
tushare received a trust score of 94/100, 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 Unpinned Dependency Installation.
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 14, 2026 (commit 13146e6a). SkillShield performs automated 4-layer security analysis on AI skills and MCP servers.
Layer Breakdown
Security Findings1
| Severity | Finding | Layer | Location | |
|---|---|---|---|---|
| MEDIUM | Unpinned Dependency Installation The skill's installation instructions recommend installing Python packages (`tushare`, `pandas`) without specifying exact versions. This introduces a supply chain risk, as future versions of these packages could contain vulnerabilities or malicious code, or an attacker could perform a dependency confusion attack if a private package with the same name exists. It is best practice to pin dependencies to specific versions to ensure reproducible and secure installations. Pin dependencies to specific versions (e.g., `pip3 install tushare==X.Y.Z pandas==A.B.C --user`) to ensure reproducible and secure installations. Regularly review and update pinned versions. | LLM | SKILL.md:23 |
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