Security Audit

modelready

github.com/openclaw/skills

AI SkillCommit 13146e6a3d46

CAUTION

Scanned about 2 months ago

Critical

Immediate action required

High

Priority fixes suggested

Medium

Best practices review

Low

Acknowledged / Tracked

Trust Assessment

modelready received a trust score of 73/100, 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 Potential Command Injection via User-Supplied 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

100%

Static Code Analysis

100%

Dependency Graph

100%

LLM Behavioral Safety

70%

Behavioral Risk Signals

Network Access

1 finding

Filesystem Write

1 finding

Shell Execution

1 finding

Dynamic Code

1 finding

Security Findings1

Severity	Finding	Layer	Location
CRITICAL	Potential Command Injection via User-Supplied Arguments The skill manifest indicates a dependency on `bash` and `curl`, suggesting that shell commands are executed. The `SKILL.md` describes commands like `/modelready start` which accepts a `repo` argument (e.g., `repo=<path-or-hf-repo>`) and `/modelready set_ip` which accepts an `ip` argument. If these user-supplied arguments are directly interpolated into shell commands without proper sanitization or validation, an attacker could inject arbitrary shell commands. For example, providing `repo='; rm -rf /;'` could lead to arbitrary code execution on the host system. All user-supplied arguments (`repo`, `port`, `ip`, `text`, `tp`, `dtype`) must be strictly validated and sanitized before being used in any shell command. For file paths or repository names, ensure they conform to expected patterns and do not contain shell metacharacters. For network parameters like `port` and `ip`, validate them as integers or valid network addresses respectively. Prefer using libraries or functions that safely execute external commands with parameterized arguments rather than direct string interpolation.	LLM	SKILL.md:30

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