Security Audit

tencent-finance

github.com/openclaw/skills

AI SkillCommit 13146e6a3d46

TRUSTED

Scanned about 2 months ago

Critical

Immediate action required

High

Priority fixes suggested

Medium

Best practices review

Low

Acknowledged / Tracked

Trust Assessment

tencent-finance 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 Python dependencies.

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

Manifest Analysis

100%

Static Code Analysis

100%

Dependency Graph

100%

LLM Behavioral Safety

93%

Behavioral Risk Signals

Network Access

1 finding

Security Findings1

Severity	Finding	Layer	Location
MEDIUM	Unpinned Python dependencies The skill's installation instructions recommend installing Python packages (`requests`, `rich`) without specifying exact versions. This can lead to supply chain attacks if a malicious version of a dependency is published, as the user would unknowingly install it. Pin all Python dependencies to exact versions (e.g., `pip3 install requests==2.28.1 rich==12.1.0`) to ensure reproducible and secure installations.	LLM	SKILL.md:76

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