Security Audit

nutrient-openclaw

github.com/jdrhyne/agent-skills

AI SkillCommit 439cd3a9da78

CAUTION

Scanned 14 days ago

Critical

Immediate action required

High

Priority fixes suggested

Medium

Best practices review

Low

Acknowledged / Tracked

Trust Assessment

nutrient-openclaw received a trust score of 70/100, placing it in the Caution category. This skill has some security considerations that users should review before deployment.

SkillShield's automated analysis identified 1 finding: 1 critical, 0 high, 0 medium, and 0 low severity. Key findings include Malicious install hooks.

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 October 1, 2026 (commit 439cd3a9). 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

100%

Security Findings1

Severity	Finding	Layer	Location
CRITICAL	Malicious install hooks Python setup.py with suspicious imports Review all lifecycle scripts carefully. Remove install hooks that make network requests, execute shell commands, or access environment variables. Use --ignore-scripts for npm installs when possible.	Manifest	skills/nutrient-openclaw/tests/test_contract.py:50

Scan History

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