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Security Audit

ticktick

github.com/openclaw/skills
AI SkillCommit 13146e6a3d46
56
CAUTION
Scanned about 2 months ago
1
Critical
Immediate action required
1
High
Priority fixes suggested
0
Medium
Best practices review
0
Low
Acknowledged / Tracked

Trust Assessment

ticktick received a trust score of 56/100, placing it in the Caution category. This skill has some security considerations that users should review before deployment.

SkillShield's automated analysis identified 2 findings: 1 critical, 1 high, 0 medium, and 0 low severity. Key findings include Network egress to untrusted endpoints, Potential Command Injection via `ticktick` CLI arguments.

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
70%
Static Code Analysis
100%
Dependency Graph
100%
LLM Behavioral Safety
85%

Behavioral Risk Signals

Network Access
1 finding
Shell Execution
1 finding
Dynamic Code
1 finding

Security Findings2

SeverityFindingLayerLocation

Scan History

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