Security Audit

sundial-org/awesome-openclaw-skills:skills/apple-reminders

github.com/sundial-org/awesome-openclaw-skills

AI SkillCommit 6d998e005da6

CRITICAL

Scanned 27 days ago

Critical

Immediate action required

High

Priority fixes suggested

Medium

Best practices review

Low

Acknowledged / Tracked

Trust Assessment

sundial-org/awesome-openclaw-skills:skills/apple-reminders received a trust score of 43/100, placing it in the Untrusted category. This skill has significant security findings that require attention before use in production.

SkillShield's automated analysis identified 1 finding: 1 critical, 0 high, 0 medium, and 0 low severity. Key findings include Potential Command Injection via CLI Wrapper.

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 March 3, 2026 (commit 6d998e00). 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

Shell Execution

1 finding

Dynamic Code

1 finding

Security Findings1

Severity	Finding	Layer	Location
CRITICAL	Potential Command Injection via CLI Wrapper The skill wraps the `remindctl` command-line interface. User-provided inputs such as reminder titles, list names, and dates are directly passed as arguments to `remindctl`. If the LLM constructs shell commands by directly interpolating unsanitized user input into these arguments, it creates a critical command injection vulnerability. A malicious user could inject arbitrary shell commands by crafting inputs that break out of the intended argument string (e.g., using quotes, semicolons, or backticks). This could lead to arbitrary code execution on the host system. The LLM implementation must rigorously sanitize and escape all user-provided inputs before constructing and executing `remindctl` commands. This typically involves using a robust shell escaping mechanism for each argument to prevent shell metacharacters from being interpreted as commands. For example, using `shlex.quote()` in Python or similar functions in other languages when building the command string.	LLM	SKILL.md:36

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