Security audit

Mood Tracker

Security checks for vulnerabilities and agentic risk

Overview

This is a simple Chinese-language mood-tracking skill with no embedded executable code, though its install instructions use an unpinned latest-version command.

Install only from a trusted ClawHub/npm source, preferably with a pinned installer version when available. Be aware that mood notes can be sensitive personal information, and the documentation should be clearer about language support and why curl is listed as a requirement.

A.I.G

Vulnerability Patterns

Insecure DependenciesIntroduces malicious components through unsafe dependency sources
Skill Instruction HijackingAlters the agent's session goals or safety constraints when the skill loads
Agent Memory PoisoningWrites attacker-controlled rules into memory that affect later sessions
Remote Payload Retrieval and ExecutionFetches external code whose behavior can change after review
Embedded Malicious CodeShips malicious scripts inside the skill and executes them locally

Findings (1)

T08 · Insecure Dependencies

Warning

Location: README.md:7
Finding: Execution of an Unpinned Third-Party npm Package
Content: View full analysis
Remediation: View remediation

SkillSpector

Vulnerability Patterns

Prompt InjectionInstruction Override, Hidden Instructions, Exfiltration Commands
Data ExfiltrationExternal Transmission, Env Variable Harvesting, File System Enumeration
Privilege EscalationExcessive Permissions, Sudo/Root Execution, Credential Access
Supply ChainUnpinned Dependencies, External Script Fetching, Obfuscated Code
Excessive AgencyUnrestricted Tool Access, Autonomous Decision Making, Scope Creep

Findings (3)

Rp1

Medium

Category: MCP Rug Pull
Confidence: 92% confidence
Finding: The README instructs users to run npx clawhub@latest install mood-tracker, which pulls and executes the latest published package version at install time rather than a pinned, reviewed version. This creates a supply-chain risk: if the package is compromised or a breaking/malicious update is published, users may execute untrusted code simply by following the installation instructions.
Content: No source excerpt is available for this finding.

Natural-Language Policy Violations

Medium

Category: Not specified by scanner
Confidence: 94% confidence
Finding: The manifest description and nearly all user-facing documentation are written in Chinese, while the skill name and heading are in English, suggesting the skill may be presented to a broader audience without an explicit language opt-in. This creates a natural-language policy concern because the file imposes a specific language/locale experience without stating that the skill is China-specific or offering alternatives.
Content: No source excerpt is available for this finding.

Natural-Language Policy Violations

Low

Category: Not specified by scanner
Confidence: 94% confidence
Finding: The skill documentation is written in Chinese while the surrounding audit context is in English, and there is no indication that the skill is region-specific or that users can choose another language. This creates a natural-language policy concern because the skill effectively imposes a language/locale without opt-in or justification.
Content: No source excerpt is available for this finding.

Static analysis

No suspicious patterns detected.