Security Audit

ferminrp/agent-skills:skills/crypto-prices-criptoya

github.com/ferminrp/agent-skills

AI SkillCommit 84b0da6385e2

CAUTION

Scanned about 1 month ago

Critical

Immediate action required

High

Priority fixes suggested

Medium

Best practices review

Low

Acknowledged / Tracked

Trust Assessment

ferminrp/agent-skills:skills/crypto-prices-criptoya 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 Shell Execution.

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 24, 2026 (commit 84b0da63). 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

Shell Execution

1 finding

Dynamic Code

1 finding

Security Findings1

Severity	Finding	Layer	Location
CRITICAL	Potential Command Injection via Shell Execution The skill's workflow explicitly states the execution of shell commands (`curl -s` and `jq '.'`) to fetch and parse data. If user-controlled inputs (e.g., `exchange`, `coin`, `fiat`, `volumen`) are directly interpolated into these shell commands without rigorous sanitization and escaping, a malicious user could inject arbitrary shell commands, leading to command injection. The `SKILL.md` mentions 'Validar inputs requeridos' but does not specify the sanitization mechanism, leaving a critical vulnerability if not handled correctly in the skill's implementation. Avoid direct shell execution for operations involving user-controlled input. Instead of `curl` and `jq`, use secure HTTP client libraries (e.g., `requests` in Python) and JSON parsing libraries available in the agent's runtime environment. If shell execution is unavoidable, ensure all user-provided arguments are strictly validated against an allow-list and properly escaped using language-specific shell escaping functions (e.g., `shlex.quote` in Python) before being passed to the shell. Prefer passing arguments as a list to subprocess calls rather than a single string.	LLM	SKILL.md:34

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