Openclaw Wealth Guide

Security checks across malware telemetry and agentic risk

Overview

This is a disclosed data collection skill with broad scraping, file, database, export, and scheduling features, but I found no hidden exfiltration, destructive behavior, or automatic privileged execution.

Install only if you intend to grant a tool broad data-collection authority. Configure it with authorized sources only, avoid placing long-lived secrets in plain config files, review scheduled jobs before enabling them, and direct exports to controlled paths because it can read configured files/databases and write local output files.

SkillSpector

By NVIDIA
Vulnerability Patterns
  • Data ExfiltrationExternal Transmission, Env Variable Harvesting, File System Enumeration
  • Supply ChainUnpinned Dependencies, External Script Fetching, Obfuscated Code
  • Excessive AgencyUnrestricted Tool Access, Autonomous Decision Making, Scope Creep
  • Behavioral ASTexec() Call, eval() Call, Dynamic Import
  • Prompt InjectionInstruction Override, Hidden Instructions, Exfiltration Commands
Findings (43)

subprocess module call

Medium
Category
Dangerous Code Execution
Content
def run_command(cmd, cwd=None):
    """运行命令并返回结果"""
    print(f"执行: {cmd}")
    result = subprocess.run(cmd, shell=True, cwd=cwd, capture_output=True, text=True)
    
    if result.stdout:
        print(f"输出: {result.stdout[:500]}...")
Confidence
95% confidence
Finding
result = subprocess.run(cmd, shell=True, cwd=cwd, capture_output=True, text=True)

subprocess module call

Medium
Category
Dangerous Code Execution
Content
def run_command(cmd, cwd=None):
    """Run command and return result"""
    print(f"Execute: {cmd}")
    result = subprocess.run(cmd, shell=True, cwd=cwd, capture_output=True, text=True, encoding='utf-8', errors='replace')
    
    if result.stdout:
        # Safe print for stdout
Confidence
93% confidence
Finding
result = subprocess.run(cmd, shell=True, cwd=cwd, capture_output=True, text=True, encoding='utf-8', errors='replace')

Missing User Warnings

Medium
Confidence
90% confidence
Finding
The README promotes a tool that can collect data from websites, APIs, databases, and local files, schedule recurring jobs, and export results to disk, but it provides no guidance on authorization, privacy, data sensitivity, rate limiting, or storage safety. In an agent skill context, this omission increases the chance that users deploy the capability against unauthorized sources or mishandle collected data, leading to privacy, compliance, or local system impact issues.

Missing User Warnings

Medium
Confidence
92% confidence
Finding
The usage examples explicitly instruct scraping remote URLs and saving outputs locally, yet they omit warnings about permission, terms-of-service compliance, personal-data collection, and the risk of overwriting or exposing local files. Because READMEs shape real user behavior, these examples normalize potentially unsafe collection and storage practices in a tool designed for automation.

Missing User Warnings

Medium
Confidence
91% confidence
Finding
The skill describes web scraping, API calls, database queries, file reads, exports, and scheduled execution, but does not warn users that these operations may collect, store, and repeatedly process sensitive or regulated data. In a data-harvesting skill, omission of privacy, retention, consent, and scheduling warnings can lead to unsafe deployment and unintentional over-collection or persistence of sensitive information.

Missing User Warnings

Medium
Confidence
86% confidence
Finding
The manifest advertises automated data collection, processing, and export across multiple source types including web, API, database, and file, but provides no warning or constraints around handling sensitive data, credentials, or privacy-sensitive material. In a skill explicitly designed for harvesting and exporting data, the lack of user-facing disclosure and guardrails increases the risk of over-collection, misuse of secrets in auth fields, and exfiltration of personal or regulated data.

Missing User Warnings

Medium
Confidence
83% confidence
Finding
The manifest declares web:fetch, web:search, browser:automate, and network:outbound scopes for collecting data but provides no privacy or transmission warning. Because this skill is explicitly a data harvester, the context makes outbound transmission more sensitive: users may not understand what sources are contacted, what data is sent externally, or whether collected content contains sensitive information.

Missing User Warnings

Medium
Confidence
83% confidence
Finding
The manifest declares web:fetch, web:search, browser:automate, and network:outbound scopes for collecting data but provides no privacy or transmission warning. Because this skill is explicitly a data harvester, the context makes outbound transmission more sensitive: users may not understand what sources are contacted, what data is sent externally, or whether collected content contains sensitive information.

Unpinned Dependencies

Low
Category
Supply Chain
Content
# 安装: pip install -r requirements-dev.txt

# 测试框架
pytest>=7.0.0
pytest-cov>=4.0.0
pytest-mock>=3.10.0
pytest-asyncio>=0.21.0
Confidence
88% confidence
Finding
pytest>=7.0.0

Unpinned Dependencies

Low
Category
Supply Chain
Content
# 测试框架
pytest>=7.0.0
pytest-cov>=4.0.0
pytest-mock>=3.10.0
pytest-asyncio>=0.21.0
Confidence
88% confidence
Finding
pytest-cov>=4.0.0

Unpinned Dependencies

Low
Category
Supply Chain
Content
# 测试框架
pytest>=7.0.0
pytest-cov>=4.0.0
pytest-mock>=3.10.0
pytest-asyncio>=0.21.0

# 代码质量和风格
Confidence
88% confidence
Finding
pytest-mock>=3.10.0

Unpinned Dependencies

Low
Category
Supply Chain
Content
pytest>=7.0.0
pytest-cov>=4.0.0
pytest-mock>=3.10.0
pytest-asyncio>=0.21.0

# 代码质量和风格
black>=23.0.0
Confidence
88% confidence
Finding
pytest-asyncio>=0.21.0

Unpinned Dependencies

Low
Category
Supply Chain
Content
pytest-asyncio>=0.21.0

# 代码质量和风格
black>=23.0.0
flake8>=6.0.0
isort>=5.12.0
mypy>=1.0.0
Confidence
90% confidence
Finding
black>=23.0.0

Unpinned Dependencies

Low
Category
Supply Chain
Content
# 代码质量和风格
black>=23.0.0
flake8>=6.0.0
isort>=5.12.0
mypy>=1.0.0
pre-commit>=3.0.0
Confidence
87% confidence
Finding
flake8>=6.0.0

Unpinned Dependencies

Low
Category
Supply Chain
Content
# 代码质量和风格
black>=23.0.0
flake8>=6.0.0
isort>=5.12.0
mypy>=1.0.0
pre-commit>=3.0.0
Confidence
87% confidence
Finding
isort>=5.12.0

Unpinned Dependencies

Low
Category
Supply Chain
Content
black>=23.0.0
flake8>=6.0.0
isort>=5.12.0
mypy>=1.0.0
pre-commit>=3.0.0

# 文档生成
Confidence
87% confidence
Finding
mypy>=1.0.0

Unpinned Dependencies

Low
Category
Supply Chain
Content
flake8>=6.0.0
isort>=5.12.0
mypy>=1.0.0
pre-commit>=3.0.0

# 文档生成
sphinx>=7.0.0
Confidence
88% confidence
Finding
pre-commit>=3.0.0

Unpinned Dependencies

Low
Category
Supply Chain
Content
pre-commit>=3.0.0

# 文档生成
sphinx>=7.0.0
sphinx-rtd-theme>=1.3.0
myst-parser>=2.0.0
Confidence
87% confidence
Finding
sphinx>=7.0.0

Unpinned Dependencies

Low
Category
Supply Chain
Content
# 文档生成
sphinx>=7.0.0
sphinx-rtd-theme>=1.3.0
myst-parser>=2.0.0

# 构建和发布
Confidence
87% confidence
Finding
sphinx-rtd-theme>=1.3.0

Unpinned Dependencies

Low
Category
Supply Chain
Content
# 文档生成
sphinx>=7.0.0
sphinx-rtd-theme>=1.3.0
myst-parser>=2.0.0

# 构建和发布
build>=0.10.0
Confidence
87% confidence
Finding
myst-parser>=2.0.0

Unpinned Dependencies

Low
Category
Supply Chain
Content
myst-parser>=2.0.0

# 构建和发布
build>=0.10.0
twine>=4.0.0
wheel>=0.40.0
Confidence
88% confidence
Finding
build>=0.10.0

Unpinned Dependencies

Low
Category
Supply Chain
Content
# 构建和发布
build>=0.10.0
twine>=4.0.0
wheel>=0.40.0

# 其他开发工具
Confidence
88% confidence
Finding
twine>=4.0.0

Unpinned Dependencies

Low
Category
Supply Chain
Content
# 构建和发布
build>=0.10.0
twine>=4.0.0
wheel>=0.40.0

# 其他开发工具
ipython>=8.15.0
Confidence
90% confidence
Finding
wheel>=0.40.0

Unpinned Dependencies

Low
Category
Supply Chain
Content
wheel>=0.40.0

# 其他开发工具
ipython>=8.15.0
jupyter>=1.0.0
autopep8>=2.0.0
bandit>=1.7.0  # 安全扫描
Confidence
92% confidence
Finding
ipython>=8.15.0

Unpinned Dependencies

Low
Category
Supply Chain
Content
# 其他开发工具
ipython>=8.15.0
jupyter>=1.0.0
autopep8>=2.0.0
bandit>=1.7.0  # 安全扫描
Confidence
88% confidence
Finding
jupyter>=1.0.0

VirusTotal

63/63 vendors flagged this skill as clean.

View on VirusTotal