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senior-security高级保安

Agent Skill

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。

总安装

888

周安装

37

GitHub Stars

37

下载量

296
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

3

许可证

MIT

最后核验

2026-05-01

来源状态

来源可访问

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:senior-security(高级保安)
来源仓库:https://github.com/ovachiever/droid-tings
仓库路径:skills/senior-security
安装命令:
npx skills add https://github.com/ovachiever/droid-tings --skill senior-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。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/ovachiever/droid-tings --skill senior-security

简介

senior-security 用于辅助安全审计、权限检查和常见漏洞排查,支持识别凭据风险和认证逻辑问题。

  • 适用于需要梳理敏感配置、分析依赖风险或生成安全清单的场景。
  • 使用时不能直接将工具输出视为最终结论;涉及密钥或用户数据时应先确认最小权限原则。
  • 不支持自动修改生产环境配置,仅提供分析建议和复核指引。
  • 适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

SKILL.md

Senior Security

Complete toolkit for senior security with modern tools and best practices.

Quick Start

Main Capabilities

This skill provides three core capabilities through automated scripts:

# Script 1: Threat Modeler
python scripts/threat_modeler.py [options]

# Script 2: Security Auditor
python scripts/security_auditor.py [options]

# Script 3: Pentest Automator
python scripts/pentest_automator.py [options]

Core Capabilities

1. Threat Modeler

Automated tool for threat modeler tasks.

Features:

  • Automated scaffolding
  • Best practices built-in
  • Configurable templates
  • Quality checks

Usage:

python scripts/threat_modeler.py <project-path> [options]

2. Security Auditor

Comprehensive analysis and optimization tool.

Features:

  • Deep analysis
  • Performance metrics
  • Recommendations
  • Automated fixes

Usage:

python scripts/security_auditor.py <target-path> [--verbose]

3. Pentest Automator

Advanced tooling for specialized tasks.

Features:

  • Expert-level automation
  • Custom configurations
  • Integration ready
  • Production-grade output

Usage:

python scripts/pentest_automator.py [arguments] [options]

Reference Documentation

Security Architecture Patterns

Comprehensive guide available in references/security_architecture_patterns.md:

  • Detailed patterns and practices
  • Code examples
  • Best practices
  • Anti-patterns to avoid
  • Real-world scenarios

Penetration Testing Guide

Complete workflow documentation in references/penetration_testing_guide.md:

  • Step-by-step processes
  • Optimization strategies
  • Tool integrations
  • Performance tuning
  • Troubleshooting guide

Cryptography Implementation

Technical reference guide in references/cryptography_implementation.md:

  • Technology stack details
  • Configuration examples
  • Integration patterns
  • Security considerations
  • Scalability guidelines

Tech Stack

Languages: TypeScript, JavaScript, Python, Go, Swift, Kotlin Frontend: React, Next.js, React Native, Flutter Backend: Node.js, Express, GraphQL, REST APIs Database: PostgreSQL, Prisma, NeonDB, Supabase DevOps: Docker, Kubernetes, Terraform, GitHub Actions, CircleCI Cloud: AWS, GCP, Azure

Development Workflow

1. Setup and Configuration

# Install dependencies
npm install
# or
pip install -r requirements.txt

# Configure environment
cp .env.example .env

2. Run Quality Checks

# Use the analyzer script
python scripts/security_auditor.py .

# Review recommendations
# Apply fixes

3. Implement Best Practices

Follow the patterns and practices documented in:

  • references/security_architecture_patterns.md
  • references/penetration_testing_guide.md
  • references/cryptography_implementation.md

Best Practices Summary

Code Quality

  • Follow established patterns
  • Write comprehensive tests
  • Document decisions
  • Review regularly

Performance

  • Measure before optimizing
  • Use appropriate caching
  • Optimize critical paths
  • Monitor in production

Security

  • Validate all inputs
  • Use parameterized queries
  • Implement proper authentication
  • Keep dependencies updated

Maintainability

  • Write clear code
  • Use consistent naming
  • Add helpful comments
  • Keep it simple

Common Commands

# Development
npm run dev
npm run build
npm run test
npm run lint

# Analysis
python scripts/security_auditor.py .
python scripts/pentest_automator.py --analyze

# Deployment
docker build -t app:latest .
docker-compose up -d
kubectl apply -f k8s/

Troubleshooting

Common Issues

Check the comprehensive troubleshooting section in references/cryptography_implementation.md.

Getting Help

  • Review reference documentation
  • Check script output messages
  • Consult tech stack documentation
  • Review error logs

Resources

  • Pattern Reference: references/security_architecture_patterns.md
  • Workflow Guide: references/penetration_testing_guide.md
  • Technical Guide: references/cryptography_implementation.md
  • Tool Scripts: scripts/ directory

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

04

需要参考平台分布和安装热度时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Claude Code

29.84%
按下载量换算88

Antigravity

23.86%
按下载量换算71

Gemini CLI

19.59%
按下载量换算58

OpenCode

12.83%
按下载量换算38

github-copilot

7.94%
按下载量换算24

Codex

3.81%
按下载量换算11

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

external-service

该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

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。

来源信息

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