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Security Audit

technews

github.com/openclaw/skills
AI SkillCommit 13146e6a3d46
60
CAUTION
Scanned 3 months ago
0
Critical
Immediate action required
0
High
Priority fixes suggested
6
Medium
Best practices review
0
Low
Acknowledged / Tracked

Trust Assessment

technews received a trust score of 60/100, placing it in the Caution category. This skill has some security considerations that users should review before deployment.

SkillShield's automated analysis identified 6 findings: 0 critical, 0 high, 6 medium, and 0 low severity. Key findings include Suspicious import: requests, Unpinned Python dependency version, Untrusted content embedded directly into LLM output.

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
79%
Dependency Graph
86%
LLM Behavioral Safety
93%

Behavioral Risk Signals

Network Access
5 findings
Dynamic Code
1 finding
Excessive Permissions
3 findings

Security Findings6

SeverityFindingLayerLocation

Scan History

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