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Security Audit

remind-me

github.com/openclaw/skills
AI SkillCommit 13146e6a3d46
65
CAUTION
Scanned about 2 months ago
1
Critical
Immediate action required
1
High
Priority fixes suggested
1
Medium
Best practices review
0
Low
Acknowledged / Tracked

Trust Assessment

remind-me received a trust score of 65/100, placing it in the Caution category. This skill has some security considerations that users should review before deployment.

SkillShield's automated analysis identified 3 findings: 1 critical, 1 high, 1 medium, and 0 low severity. Key findings include Unsanitized user input in `date -d` leads to command injection, Command injection via unsanitized data from reminder log, User message content sent to hardcoded external chat ID.

The analysis covered 4 layers: Manifest Analysis, Static Code Analysis, Dependency Graph, LLM Behavioral Safety. The LLM Behavioral Safety layer scored lowest at 48/100, indicating areas for improvement.

Last analyzed on February 14, 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
48%

Behavioral Risk Signals

Network Access
1 finding
Filesystem Write
1 finding
Shell Execution
2 findings
Dynamic Code
2 findings

Security Findings3

SeverityFindingLayerLocation

Scan History

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