Security Audit

openai/skills:skills/.system/skill-installer

github.com/openai/skills

AI SkillCommit 49f948faa925

CRITICAL

Scanned about 10 hours ago

Critical

Immediate action required

High

Priority fixes suggested

Medium

Best practices review

Low

Acknowledged / Tracked

Trust Assessment

openai/skills:skills/.system/skill-installer 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 5 findings: 2 critical, 2 high, 1 medium, and 0 low severity. Key findings include Unsafe environment variable passthrough, Arbitrary command execution, Credential harvesting.

The analysis covered 4 layers: Manifest Analysis, Static Code Analysis, Dependency Graph, LLM Behavioral Safety. The Manifest Analysis layer scored lowest at 25/100, indicating areas for improvement.

Last analyzed on July 17, 2026 (commit 49f948fa). SkillShield performs automated 4-layer security analysis on AI skills and MCP servers.

Layer Breakdown

Manifest Analysis

25%

Static Code Analysis

78%

Dependency Graph

100%

LLM Behavioral Safety

100%

Behavioral Risk Signals

Network Access

1 finding

Shell Execution

2 findings

Excessive Permissions

2 findings

Security Findings5

Severity	Finding	Layer	Location
CRITICAL	Arbitrary command execution Python shell execution (os.system, subprocess) Review all shell execution calls. Ensure commands are static (not built from user input), use absolute paths, and are strictly necessary. Prefer library APIs over shell commands.	Manifest	skills/.system/skill-installer/scripts/install-skill-from-github.py:100
CRITICAL	Credential harvesting Reading well-known credential environment variables Skills should only access environment variables they explicitly need. Bulk environment dumps (os.environ.copy, JSON.stringify(process.env)) are almost always malicious. Remove access to Keychain, GPG keys, and credential stores.	Manifest	skills/.system/skill-installer/scripts/github_utils.py:12
HIGH	Unsafe environment variable passthrough Access to well-known credential environment variables Minimize environment variable exposure. Only pass required, non-sensitive variables to MCP servers. Use dedicated secret management instead of environment passthrough.	Manifest	skills/.system/skill-installer/scripts/github_utils.py:12
HIGH	Dangerous call: subprocess.run() Call to 'subprocess.run()' detected in function '_run_git'. This can execute arbitrary code. Avoid using dangerous functions like exec/eval/os.system. Use safer alternatives.	Static	skills/.system/skill-installer/scripts/install-skill-from-github.py:100
MEDIUM	Suspicious import: urllib.request Import of 'urllib.request' detected. This module provides network or low-level system access. Verify this import is necessary. Network and system modules in skill code may indicate data exfiltration.	Static	skills/.system/skill-installer/scripts/github_utils.py:7

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