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Agent Skill · 开发

agentic-workflow-security(Agent 工作流安全)

用于辅助安全审计、权限检查、凭据风险、认证流程和常见漏洞排查。它适合让 Agent 梳理敏感配置、检查依赖风险、分析鉴权逻辑或生成安全复核清单。使用时不能把工具输出直接当最终结论,涉及密钥、令牌、用户数据或生产系统时,应先确认最小权限、脱敏方式和操作边界。

agentic-workflow-security 是开发类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为接触敏感数据;许可证信息还不明确,第三方扫描已通过,按安装量在开发类的 21,746 个 Skill 里排第 16,443。

总安装 499周安装 20GitHub Stars 6下载 162核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:agentic-workflow-security(Agent 工作流安全)
来源仓库:https://github.com/hack23/homepage
仓库路径:skills/agentic-workflow-security
安装命令:
npx skills add https://github.com/hack23/homepage --skill agentic-workflow-security
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/hack23/homepage --skill agentic-workflow-security

这个 Skill 是做什么的

开发类 Skill 面向写代码、改代码和排查问题,一般会读写仓库文件,部分还会执行构建或测试命令。

为 GitHub Agentic Workflows 提供五层纵深防御安全架构指导。适用于设计安全工作流、配置输入输出防护、防火墙规则及威胁检测机制。强调只读令牌、无密钥运行、容器化执行与安全输出生成等核心实践。涉及敏感数据或生产系统时,必须验证最小权限、脱敏策略和操作边界。

agentic-workflow-security 属于开发类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/agentic-workflow-security

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/hack23/homepage --skill agentic-workflow-secur…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要接触敏感数据,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

agentic-workflow-security 怎么安装?

在终端执行 npx skills add https://github.com/hack23/homepage --skill agentic-workflow-security。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

agentic-workflow-security 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

agentic-workflow-security 需要什么权限?

权限级别是接触敏感数据。该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

agentic-workflow-security 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

agentic-workflow-security 用的人多吗?

公开数据是累计安装 499 次,近一周安装 20 次,下载 162 次,GitHub 6 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

agentic-workflow-security 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 需要接触敏感数据,装到常用环境前要先评估影响面。
  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理开发类任务、又不想每次都手写提示词的人。

不太适合

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

开发类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
skill-vetter

技能审查员 · OpenClaw

8,779,018986操作浏览器MIT-0通过
ontology

本体论 · OpenClaw

6,636,960576只读MIT-0通过
entra-app-registration

内部应用程序注册 · Codex、Claude

6,631,872764接触敏感数据未明确通过
entra-app-registration

内部应用程序注册 · Codex、Claude

3,757,680201接触敏感数据未明确通过
nano-banana-pro

纳米香蕉专业版 · OpenClaw

3,526,898364接触敏感数据MIT-0有提醒
agentic-workflow-security

Agent 工作流安全 · 本页

4996接触敏感数据未明确通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

🔒 Agentic Workflow Security Skill

Purpose

Comprehensive security guidance for GitHub Agentic Workflows implementing the official 5-layer defense-in-depth architecture: read-only tokens, zero secrets in agent, containerized execution with Agent Workflow Firewall (AWF), safe outputs with guardrails, and agentic threat detection.

When to Use

Apply this skill when:

  • Designing secure agentic workflows
  • Configuring safe-inputs, safe-outputs, and threat detection
  • Setting up network firewall rules (AWF)
  • Implementing integrity filtering for public repositories
  • Responding to security incidents in agentic workflows

Rules

5-Layer Defense-in-Depth Architecture

MUST implement all five official security layers:

  1. Read-only tokens — Agent receives only read-scoped GitHub token; cannot push, create PRs, or delete files
  2. Zero secrets in agent — Write tokens and API keys exist only in separate, isolated post-agent jobs
  3. Containerized with AWF — Agent Workflow Firewall routes all outbound traffic through Squid proxy with domain allowlist; kernel-level blocking
  4. Safe outputs with guardrails — Agent produces structured artifacts; separate gated job applies only explicitly permitted actions with hard limits
  5. Agentic threat detection — AI-powered scan checks for prompt injection, leaked credentials, and malicious code before any write

MUST NOT:

  • Rely on any single security layer
  • Bypass safe-outputs for convenience
  • Assume AI agents are inherently trustworthy

Principle of Least Privilege

MUST:

  • Use specific resource permissions (e.g., issues: read, contents: read) not read-all
  • Grant write operations only through safe-outputs with max: limits
  • Use fine-grained PATs with minimal scopes
  • Set timeout-minutes: on all workflows
  • Audit permission usage regularly

MUST NOT:

  • Use permissions: write-all without security review
  • Use classic PATs instead of fine-grained tokens
  • Allow unrestricted network access

Safe Outputs (Write Operations via Gated Jobs)

MUST:

  • Configure all write operations in safe-outputs: with specific constraints:

- max: — Hard limit per operation per run - title-prefix: — Required prefix for created issues/PRs - labels: — Required/allowed labels - allowed: — Allowlist of label values for add-labels - close-older-issues: — Auto-close previous reports - branch: — Target branch for asset uploads - max-size: — File size limits for uploads - allowed-exts: — Permitted file extensions

  • Enable threat-detection: with action: block for all production workflows
  • Use separate permission-controlled jobs to execute safe outputs
  • Include human review gates for critical operations

MUST NOT:

  • Grant direct write permissions when safe-outputs can be used
  • Set excessive max: limits without justification
  • Auto-merge AI-generated PRs without review
  • Skip threat detection for write operations

Safe Inputs (Custom Tools)

MUST:

  • Define custom tools inline using safe-inputs: section
  • Use typed input parameters with validation
  • Scope tool access appropriately
  • Provide clear descriptions for each tool
  • Use environment variables for secrets (never hard-code)
  • Test tools thoroughly before production use

MUST NOT:

  • Execute arbitrary code from external sources
  • Trust user input without validation
  • Expose secrets in tool definitions
  • Grant excessive capabilities to custom tools
  • Skip input sanitization

Threat Detection

MUST:

  • Enable automatic threat detection for safe-outputs workflows
  • Configure threat-detection: settings appropriately
  • Review threat detection alerts promptly
  • Block workflow execution on critical threats
  • Monitor for prompt injection attempts
  • Scan for exposed credentials in outputs
  • Detect malicious code patterns

MUST NOT:

  • Disable threat detection without security review
  • Ignore threat detection warnings
  • Auto-approve flagged outputs
  • Skip investigation of security alerts

Network Security (Agent Workflow Firewall)

MUST:

  • Use network: {} for zero external access (most secure)
  • Use network: defaults for GitHub-only access (github.com, api.github.com)
  • Explicitly allowlist required domains when external access is needed
  • Use HTTPS for all external communications
  • Understand that AWF uses Squid proxy with kernel-level blocking

MUST NOT:

  • Allow unrestricted internet access without justification
  • Use HTTP for sensitive communications
  • Trust external APIs without validation
  • Bypass certificate validation

Secret Management

MUST:

  • Store all secrets in GitHub Secrets (repository or organization level)
  • Use descriptive secret names (e.g., ANTHROPIC_API_KEY)
  • Rotate secrets regularly
  • Use fine-grained PATs with minimal scopes
  • Document required secrets in workflow documentation
  • Audit secret access patterns
  • Revoke compromised secrets immediately

MUST NOT:

  • Hard-code secrets in workflow files
  • Commit secrets to version control
  • Share secrets between unrelated workflows
  • Use overly permissive tokens
  • Log secret values
  • Expose secrets in error messages

Prompt Injection Protection

MUST:

  • Validate and sanitize all user inputs
  • Use structured data formats (JSON, YAML) for inputs
  • Implement input length limits
  • Escape special characters in user content
  • Separate instructions from user data
  • Use safe-inputs for user-provided data
  • Monitor for injection attempts

MUST NOT:

  • Trust user input in issue titles, bodies, or comments
  • Include raw user input in system prompts
  • Execute commands containing user input without validation
  • Allow users to modify workflow instructions
  • Skip input validation for "trusted" users

Audit and Monitoring

MUST:

  • Log all workflow executions with timestamps
  • Record AI model interactions and decisions
  • Track safe output usage and approvals
  • Monitor for unusual patterns or behaviors
  • Generate security audit trails
  • Review logs regularly
  • Alert on suspicious activities

MUST NOT:

  • Disable logging for performance
  • Delete logs before retention period
  • Log sensitive data (passwords, tokens)
  • Ignore monitoring alerts
  • Skip periodic security reviews

Human-in-the-Loop Controls

MUST:

  • Require human approval for critical operations:

- Production deployments - Data modifications - Security-sensitive changes - User-facing content

  • Implement approval workflows for safe-outputs
  • Provide clear context for approval decisions
  • Time-limit approval windows
  • Escalate approval failures

MUST NOT:

  • Auto-approve all AI-generated changes
  • Skip review for "low-risk" operations without assessment
  • Combine approval and execution in same role
  • Allow expired approvals

Examples

Example 1: Minimal Security Configuration

---
on: issues
permissions: read-all  # Read-only default
tools:
  github:
network: {}  # No external network access
safe-outputs:
  create-comment:
    max: 1  # Single comment per execution
---

# Secure Issue Triage

Analyze issue and post triage comment.

Example 2: Safe Outputs with Threat Detection

---
on: pull_request
permissions: read-all
tools:
  github:
safe-outputs:
  create-comment:
    max: 3
  threat-detection:
    enabled: true
    scan-for:
      - prompt-injection
      - secret-leak
      - malicious-code
    action: block  # Block on threats
---

# Secure Code Review

Review pull request for security issues.
Threat detection automatically scans outputs before posting.

Example 3: Safe Inputs with Validation

---
on: issues
permissions: read-all
tools:
  github:
safe-inputs:
  calculate_risk_score:
    type: function
    description: Calculate security risk score
    code: |
      function calculate_risk_score(title, labels) {
        // Input validation
        if (!title || typeof title !== 'string') return 0;
        if (!Array.isArray(labels)) return 0;

        let score = 0;
        // Sanitize inputs
        const safetitle = String(title).toLowerCase();

        if (labels.includes('security')) score += 10;
        if (labels.includes('vulnerability')) score += 10;
        if (safetitle.includes('rce')) score += 8;
        if (safetitle.includes('sql injection')) score += 8;

        return Math.min(score, 10);
      }
safe-outputs:
  create-comment:
    max: 1
---

# Security Risk Assessment

Use calculate_risk_score to assess security issues.
Post risk score and recommended response timeline.

Example 4: Network-Restricted Workflow

---
on: workflow_dispatch
permissions: read-all
tools:
  github:
network:
  defaults:
    - github.com
    - api.github.com
    - raw.githubusercontent.com
  # Explicitly no other domains allowed
safe-outputs:
  create-issue:
    max: 1
---

# Security Audit (Network Restricted)

Perform security audit using only GitHub APIs.
No external network access to prevent data exfiltration.

Example 5: SARIF Security Report

---
on: pull_request
permissions: read-all
tools:
  github:
safe-outputs:
  create-code-scanning-alert:
    max: 1
---

# Security Code Scanning

Analyze code changes for security vulnerabilities:
1. Check for hard-coded secrets
2. Identify injection vulnerabilities
3. Detect unsafe deserialization
4. Find insecure cryptography usage

Generate SARIF report and upload to GitHub Code Scanning.

Example 6: Asset Upload Security

---
on: workflow_dispatch
permissions: read-all
tools:
  github:
  playwright:
safe-outputs:
  upload-asset:
    branch: "assets/security-reports"
    max-size: 5120  # 5MB limit
    allowed-exts: [.png, .pdf, .json]
---

# Security Screenshot Generation

Generate security dashboard screenshots.
Upload only allowed file types to isolated branch.

Example 7: Multi-Layer Security

---
on: issues
permissions: read-all
tools:
  github:
network:
  defaults:  # Layer 1: Network restriction
safe-inputs:  # Layer 2: Validated custom tools
  sanitize_input:
    type: function
    code: |
      function sanitize_input(text) {
        return String(text)
          .replace(/[<>]/g, '')
          .substring(0, 1000);
      }
safe-outputs:  # Layer 3: Safe write operations
  create-comment:
    max: 1
  threat-detection:  # Layer 4: Output validation
    enabled: true
    action: block
---

# Defense-in-Depth Security Analysis

Multi-layer security for issue analysis.

Example 8: Fine-Grained Token Configuration

---
on: pull_request
permissions: read-all
tools:
  github:
safe-outputs:
  update-project:
    # Use fine-grained PAT with minimal scopes:
    # - Read access to metadata
    # - Write access to projects
    github-token: ${{ secrets.GH_AW_PROJECT_TOKEN }}
    max: 1
---

# Secure Project Board Update

Update project board with PR status.
Uses minimal-scope token for Projects API only.

Security Checklist

Before deploying an agentic workflow:

Design Phase

  • Threat model completed
  • Security requirements documented
  • Least privilege design implemented
  • Defense-in-depth layers identified

Implementation Phase

  • Read-only permissions by default
  • Safe-outputs configured for write operations
  • Network access restricted appropriately
  • Safe-inputs validated and tested
  • Secrets stored securely (not in code)
  • Threat detection enabled

Testing Phase

  • Prompt injection tests passed
  • Permission boundaries validated
  • Safe-output limits tested
  • Network isolation verified
  • Secret exposure tests passed
  • Threat detection alerts reviewed

Deployment Phase

  • Security review completed
  • Secrets configured correctly
  • Monitoring and alerting enabled
  • Incident response plan documented
  • Rollback procedure tested

Operations Phase

  • Logs reviewed regularly
  • Threat detection alerts monitored
  • Permission usage audited
  • Security metrics tracked
  • Incident response procedures tested

Incident Response

Detection

  1. Monitor threat detection alerts
  2. Review unusual workflow patterns
  3. Check for unexpected safe-output executions
  4. Investigate failed permission checks

Containment

  1. Pause affected workflows immediately
  2. Revoke compromised tokens
  3. Block suspicious network access
  4. Isolate affected repositories

Eradication

  1. Identify root cause
  2. Remove malicious content
  3. Update workflow security controls
  4. Patch vulnerabilities

Recovery

  1. Verify security controls are effective
  2. Re-enable workflows with enhanced monitoring
  3. Validate normal operations
  4. Document lessons learned

Post-Incident

  1. Conduct security review
  2. Update security procedures
  3. Train team on new threats
  4. Improve detection capabilities

Security Anti-Patterns

❌ Excessive Permissions

---
permissions: write-all  # WRONG: Too broad
---

✅ Correct Approach:

---
permissions: read-all
safe-outputs:
  create-comment:
    max: 1
---

❌ Hard-Coded Secrets

---
engine: claude
env:
  ANTHROPIC_API_KEY: sk-ant-abc123  # WRONG: Secret in code
---

✅ Correct Approach:

---
engine: claude
# Secret configured in GitHub Secrets
---

❌ Unrestricted Network

---
tools:
  web-fetch:  # WRONG: No network restrictions
---

✅ Correct Approach:

---
tools:
  web-fetch:
network:
  defaults:
    - trusted-domain.com
---

❌ No Threat Detection

---
safe-outputs:
  create-pull-request:
    max: 1
  # WRONG: No threat detection
---

✅ Correct Approach:

---
safe-outputs:
  create-pull-request:
    max: 1
  threat-detection:
    enabled: true
    action: block
---

❌ Trusting User Input

# WRONG: Using raw issue title in command
Execute: analyze-tool --input="${issue.title}"

✅ Correct Approach:

# Sanitize user input before use
safe-inputs:
  sanitize:
    code: |
      function sanitize(input) {
        return input.replace(/[^a-zA-Z0-9 ]/g, '');
      }

Related ISMS Policies

This skill implements requirements from:

Related Skills

Related Documentation

Compliance Mapping

ISO 27001:2022

  • A.5.23 Information security for use of cloud services
  • A.8.24 Use of cryptography
  • A.8.25 Secure development life cycle
  • A.8.28 Secure coding
  • A.16.1 Management of information security incidents

NIST Cybersecurity Framework 2.0

  • GV.RM-02: Risk appetite and tolerance are established
  • PR.AA-01: Identities are established, managed, and assured
  • PR.DS-02: Data-in-transit is protected
  • DE.CM-01: Network traffic is monitored

CIS Controls v8.1

  • Control 3: Data Protection

- 3.3 Configure Data Access Control Lists

  • Control 4: Secure Configuration

- 4.1 Establish and Maintain a Secure Configuration Process

  • Control 6: Access Control Management

- 6.1 Establish an Access Granting Process - 6.8 Define and Maintain Role-Based Access Control

Enforcement

Security violations in agentic workflows:

  • Critical: Exposed secrets, unrestricted permissions, disabled security controls - Immediate incident response
  • High: Missing threat detection, unsafe tool configuration - Block deployment
  • Medium: Excessive permissions, missing network restrictions - Require remediation
  • Low: Incomplete logging, missing documentation - Create improvement tickets

Version History

  • 2026-04-02: Major update with official 5-layer architecture, AWF firewall details, safe-output constraint types, integrity filtering, updated documentation links
  • 2026-02-11: Initial skill creation

平台分布

Codex

38.8%
按下载量换算63

Claude

28.07%
按下载量换算45

Cursor

18.48%
按下载量换算30

Gemini CLI

9.44%
按下载量换算15

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

接触敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

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