aliyun-clawscan

Analyzes the security posture of a user's OpenClaw environment and installed skills. Use when a user is about to install a new skill and wants to verify its safety, has concerns about the behavior of an existing skill, or needs a comprehensive security check of their entire OpenClaw setup. Helpful for users performing a security audit, investigating a suspicious skill, or needing to assess configuration risks and potential vulnerabilities before proceeding with installations.

3,891 stars

Best use case

aliyun-clawscan is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Analyzes the security posture of a user's OpenClaw environment and installed skills. Use when a user is about to install a new skill and wants to verify its safety, has concerns about the behavior of an existing skill, or needs a comprehensive security check of their entire OpenClaw setup. Helpful for users performing a security audit, investigating a suspicious skill, or needing to assess configuration risks and potential vulnerabilities before proceeding with installations.

Teams using aliyun-clawscan should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/aliyun-clawscan/SKILL.md --create-dirs "https://raw.githubusercontent.com/openclaw/skills/main/skills/aliyun-ai-sec/aliyun-clawscan/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/aliyun-clawscan/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How aliyun-clawscan Compares

Feature / Agentaliyun-clawscanStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Analyzes the security posture of a user's OpenClaw environment and installed skills. Use when a user is about to install a new skill and wants to verify its safety, has concerns about the behavior of an existing skill, or needs a comprehensive security check of their entire OpenClaw setup. Helpful for users performing a security audit, investigating a suspicious skill, or needing to assess configuration risks and potential vulnerabilities before proceeding with installations.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

Related Guides

SKILL.md Source

> **说明**:本 Skill 由 **阿里云(Alibaba Cloud)** 提供的安全防护检查能力,用于对 OpenClaw 环境与 Skill 进行安全评估与风险检测。

---

# aliyun-clawscan

Comprehensive OpenClaw security assessment combining configuration audit and skill security analysis.

---

## When to Use

| Scenario | Example Triggers |
|----------|------------------|
| Full Assessment | `OpenClaw安全评估`, `风险评估`, `安全体检` |
| Config Audit | `配置审计`, `检查OpenClaw配置` |
| Skill Scan | `skill安全扫描`, `检查skill风险` |
| Pre-install Check | `安装前检查`, `这个skill安全吗` |

---

## Assessment Workflow

```
Step 1: Configuration Audit
  └─ openclaw security audit --deep
     └─ See: reference/baseline.md

Step 2: Skill Security Audit
  ├─ Inventory: openclaw skills list
  └─ Static Analysis (local rules)
     └─ See: reference/skillaudit.md

Step 3: Consolidated Report
  └─ Overview + findings
```

---

# Step 1: Configuration Audit

Run OpenClaw built-in security audit:

```bash
openclaw security audit --deep
```

Parse results into categories (Gateway, Network, Tools, Browser, Files, Room).

**Reference:** `reference/baseline.md` for detailed check categories and parsing rules.

---

# Step 2: Skill Security Audit

## Phase 1: Inventory

```bash
openclaw skills list
```

## Phase 2: Static Analysis

Apply local detection rules across 11 categories:

| Category | Severity | Reference |
|----------|----------|-----------|
| Reverse Shell / Backdoor | 🚨 Critical | skillaudit.md Scenario 1 |
| Credential Harvesting | 🚨 Critical | skillaudit.md Scenario 2 |
| Data Exfiltration | 🔴 High | skillaudit.md Scenario 3 |
| Cryptominer | 🚨 Critical | skillaudit.md Scenario 4 |
| Permission Abuse | 🔴 High | skillaudit.md Scenario 5 |
| Prompt Injection | 🔴 High | skillaudit.md Scenario 6 |
| Code Obfuscation | 🟡 Medium | skillaudit.md Scenario 7 |
| Ransomware | 🚨 Critical | skillaudit.md Scenario 8 |
| Persistence | 🟡 Medium | skillaudit.md Scenario 9 |
| Supply Chain | 🟡 Medium | skillaudit.md Scenario 10 |
| **Malicious Service Downloader** | 🚨 Critical | skillaudit.md Scenario 11 |

**Reference:** `reference/skillaudit.md` for complete detection patterns, code examples, and risk assessment logic.

## Phase 3: Risk Classification

| Level | Criteria |
|-------|----------|
| 🚨 Critical | Backdoor, credential theft, ransomware, miner |
| 🔴 High | Permission abuse, data exfil, privacy violation |
| 🟡 Medium | High permissions justified, benign obfuscation |
| 🟢 Low | Matches declared purpose |

---

# Step 3: Consolidated Report

## Report Header

```markdown
# 🔒 OpenClaw Risk Assessment Report

📅 {datetime}
🖥️ OpenClaw {version} · {os_info}
📊 Overall Risk: {🟢/🟡/🔴/🚨}

| Check Item | Status | Summary |
|------------|--------|---------|
| Configuration Audit | {✅/⚠️/🔴} | {N findings} |
| Skill Security | {✅/⚠️/🔴} | {N critical, N high} |
| Overall | {🟢/🟡/🔴/🚨} | {verdict} |
```

## Section 1: Configuration Audit Results

| Status | Item | Finding |
|--------|------|---------|
| ✅/⚠️/🔴 | {Category} | {Description} |

## Section 2: Skill Security Findings

| Risk | Count | Skills |
|------|-------|--------|
| 🚨 Critical | {N} | {names} |
| 🔴 High | {N} | {names} |
| 🟡 Medium | {N} | {names} |
| 🟢 Low | {N} | (see safe list) |

---

# Output Templates

## Quick Verdicts

| Result | Message |
|--------|---------|
| All Clear | ✅ OpenClaw风险评估完成。配置审计通过,Skill安全检查未发现明显风险。 |
| Config Issues | ⚠️ 发现配置风险。建议检查Gateway设置和文件权限配置。 |
| Skill Risks | 🔴 发现Skill安全风险。{N}个高风险Skill建议立即处理。 |
| Critical | 🚨 检测到严重安全风险!建议立即处理配置问题并移除恶意Skill。 |

## Single Skill Assessment

- **Safe:** `经检测暂未发现高风险问题,可继续安装;`
- **Sensitive:** `发现需关注项,但当前未见明确恶意证据。这个skill具备{高权限能力},主要用于完成它声明的{功能};建议仅在确认来源可信、权限范围可接受时使用。`
- **Risky:** `发现风险,不建议直接安装。这个skill{具体问题},超出了它声称的功能。`
- **Malicious:** `🚨 检测到恶意代码!这个skill包含{具体恶意行为},强烈建议立即删除。`
- **Malicious Downloader:** `🚨 检测到恶意下载器!这个skill伪装成{服务名称},通过base64混淆命令诱导执行远程恶意脚本(curl|bash模式),属于典型的社会工程+下载器攻击。切勿执行任何安装命令!`

---

# Safety Guardrails

- ✅ Static analysis only - never execute suspicious code
- ✅ Read code via file tools - no dynamic testing
- ✅ Evidence-based reporting - file:line references required
- ❌ Never bypass sandbox for analysis
- ❌ Never enumerate actual user files
- ❌ No speculation without clear evidence

---

# File Reference

| File | Purpose |
|------|---------|
| `reference/baseline.md` | Configuration audit rules and parsing logic |
| `reference/skillaudit.md` | Skill security detection patterns and scenarios |

---

> **说明**:本 Skill 由 **阿里云(Alibaba Cloud)** 提供的安全防护检查能力。使用本能力可对 OpenClaw 配置与已安装/待安装 Skill 进行安全审计与风险评估。

Related Skills

aliyun-oss

3891
from openclaw/skills

阿里云 OSS 对象存储技能。支持文件上传、下载、列出、删除、获取 URL 等操作。 两层架构:Node.js SDK(优先)→ ossutil CLI。

aliyun-ai-guardrail

3891
from openclaw/skills

Install and configure the Alibaba Cloud AI guardrail openclaw hook, which intercepts malicious content in LLM requests using Alibaba Cloud AI Guardrail service. Trigger when user mentions 'install aliyun ai guardrail', 'aliyun ai guardrail', 'aliyun-ai-guardrail', 'Aliyun AI Guardrail hook', or needs to set up AI security detection for openclaw.

aliyun-codeup

3891
from openclaw/skills

阿里云云效 Codeup 代码仓库管理 - 查询项目、分支、提交记录等

edgeone-clawscan

3891
from openclaw/skills

The first security skill to install after setting up OpenClaw — powered by Tencent Zhuque Lab. Works like an antivirus for your AI environment: audits installed skills, scans skills before installation, and performs a full OpenClaw security health check to prevent data leaks and privacy risks. Backed by Tencent Zhuque Lab A.I.G (AI-Infra-Guard). Use when the user asks to start a security health check or security scan for the current OpenClaw environment, such as `开始安全体检`, `做一次安全体检`, `开始安全扫描`, `全面安全检查`, or `检查 OpenClaw 安全`; also use when the user asks to audit a specific skill before installation, review installed skills for supply chain risk, or investigate whether a skill is safe. Do not trigger for general OpenClaw usage, project debugging, environment setup, or normal development requests. Optional cloud mode: set AIG_CLOUD_LOOKUP=off for zero outbound HTTPS; when enabled, only skill_name, source label, and OpenClaw version are sent to A.I.G (never skill bodies, chats, or workspace files).

---

3891
from openclaw/skills

name: article-factory-wechat

Content & Documentation

humanizer

3891
from openclaw/skills

Remove signs of AI-generated writing from text. Use when editing or reviewing text to make it sound more natural and human-written. Based on Wikipedia's comprehensive "Signs of AI writing" guide. Detects and fixes patterns including: inflated symbolism, promotional language, superficial -ing analyses, vague attributions, em dash overuse, rule of three, AI vocabulary words, negative parallelisms, and excessive conjunctive phrases.

Content & Documentation

find-skills

3891
from openclaw/skills

Helps users discover and install agent skills when they ask questions like "how do I do X", "find a skill for X", "is there a skill that can...", or express interest in extending capabilities. This skill should be used when the user is looking for functionality that might exist as an installable skill.

General Utilities

tavily-search

3891
from openclaw/skills

Use Tavily API for real-time web search and content extraction. Use when: user needs real-time web search results, research, or current information from the web. Requires Tavily API key.

Data & Research

baidu-search

3891
from openclaw/skills

Search the web using Baidu AI Search Engine (BDSE). Use for live information, documentation, or research topics.

Data & Research

agent-autonomy-kit

3891
from openclaw/skills

Stop waiting for prompts. Keep working.

Workflow & Productivity

Meeting Prep

3891
from openclaw/skills

Never walk into a meeting unprepared again. Your agent researches all attendees before calendar events—pulling LinkedIn profiles, recent company news, mutual connections, and conversation starters. Generates a briefing doc with talking points, icebreakers, and context so you show up informed and confident. Triggered automatically before meetings or on-demand. Configure research depth, advance timing, and output format. Walking into meetings blind is amateur hour—missed connections, generic small talk, zero leverage. Use when setting up meeting intelligence, researching specific attendees, generating pre-meeting briefs, or automating your prep workflow.

Workflow & Productivity

self-improvement

3891
from openclaw/skills

Captures learnings, errors, and corrections to enable continuous improvement. Use when: (1) A command or operation fails unexpectedly, (2) User corrects Claude ('No, that's wrong...', 'Actually...'), (3) User requests a capability that doesn't exist, (4) An external API or tool fails, (5) Claude realizes its knowledge is outdated or incorrect, (6) A better approach is discovered for a recurring task. Also review learnings before major tasks.

Agent Intelligence & Learning