Skip to main content

Security Audit

sage-wallet

github.com/openclaw/skills
AI SkillCommit 13146e6a3d46
10
CRITICAL
Scanned 3 months ago
6
Critical
Immediate action required
1
High
Priority fixes suggested
7
Medium
Best practices review
1
Low
Acknowledged / Tracked

Trust Assessment

sage-wallet received a trust score of 10/100, placing it in the Untrusted category. This skill has significant security findings that require attention before use in production.

SkillShield's automated analysis identified 15 findings: 6 critical, 1 high, 7 medium, and 1 low severity. Key findings include Network egress to untrusted endpoints, Sensitive environment variable access: $HOME, jq command injection via user-controlled config keys/values.

The analysis covered 4 layers: Manifest Analysis, Static Code Analysis, Dependency Graph, LLM Behavioral Safety. The Manifest Analysis layer scored lowest at 0/100, indicating areas for improvement.

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
0%
Static Code Analysis
86%
Dependency Graph
100%
LLM Behavioral Safety
16%

Behavioral Risk Signals

Network Access
10 findings
Filesystem Write
5 findings
Shell Execution
7 findings
Dynamic Code
5 findings
Excessive Permissions
4 findings

Security Findings15

SeverityFindingLayerLocation

Scan History

Embed Code

[![SkillShield](https://skillshield.io/api/v1/badge/6873abe552989bc9.svg)](https://skillshield.io/report/6873abe552989bc9)
SkillShield Badge

Powered by SkillShield