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Security Audit

canvas-design

github.com/anthropics/skills
AI SkillCommit 1ed29a03dc85
88
TRUSTED
Scanned about 2 months ago
0
Critical
Immediate action required
0
High
Priority fixes suggested
2
Medium
Best practices review
0
Low
Acknowledged / Tracked

Trust Assessment

canvas-design received a trust score of 88/100, placing it in the Mostly Trusted category. This skill has passed most security checks with only minor considerations noted.

SkillShield's automated analysis identified 2 findings: 0 critical, 0 high, 2 medium, and 0 low severity. Key findings include Direct filesystem directory access, Unrestricted external resource download.

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 11, 2026 (commit 1ed29a03). 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
86%

Behavioral Risk Signals

Network Access
1 finding
Filesystem Write
2 findings
Shell Execution
1 finding
Excessive Permissions
2 findings

Security Findings2

SeverityFindingLayerLocation

Scan History

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