Token导航 LogoToken导航

Agent Skill · 研究检索

security-review(安全审查)

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。

security-review 是研究检索类 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,第三方扫描有未通过项,按安装量在研究检索类的 73,675 个 Skill 里排第 1,345。

总安装 98,784周安装 4,217GitHub Stars 648下载 34,608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:security-review(安全审查)
来源仓库:https://github.com/getsentry/skills
仓库路径:skills/security-review
安装命令:
npx skills add https://github.com/getsentry/skills --skill security-review
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/getsentry/skills --skill security-review

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

系统安全代码审查通过数据流验证识别高可信度漏洞。

专注于高置信度发现:具有已确认的攻击者控制输入的易受攻击模式,跳过理论问题和框架缓解的代码 在报告之前需要进行代码库研究:跟踪数据流、检查验证/清理并验证可利用性,而不是单独进行模式匹配 涵盖 14 个漏洞类别(注入、XSS、授权、加密、反序列化、SSRF 等)以及针对 Python、JavaScript、Go、Rust 和 Java 的语言特定指南 区分服务器控制的值(设置、环境变量、硬编码常量)和攻击者控制的输入,以消除误报 报告结果,包括严重性分类(严重/高/中/低)、位置、影响、证据和补救指南

来源仓库内路径:skills/security-review

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/getsentry/skills --skill security-review;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

security-review 怎么安装?

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

security-review 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。

security-review 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。

security-review 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。

security-review 用的人多吗?

公开数据是累计安装 98,784 次,近一周安装 4,217 次,下载 34,608 次,GitHub 648 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。

security-review 安全吗?

第三方扫描有未通过项,风险较高。除非你确认过源码,否则不建议直接安装到常用环境。

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。

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。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 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。
  • 需要处理研究检索类任务、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。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
security-review

安全审查 · 本页

98,784648接触敏感数据未明确未通过

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

Security Review Skill

Identify exploitable security vulnerabilities in code. Report only HIGH CONFIDENCE findings—clear vulnerable patterns with attacker-controlled input.

Scope: Research vs. Reporting

CRITICAL DISTINCTION:

  • Report on: Only the specific file, diff, or code provided by the user
  • Research: The ENTIRE codebase to build confidence before reporting

Before flagging any issue, you MUST research the codebase to understand:

  • Where does this input actually come from? (Trace data flow)
  • Is there validation/sanitization elsewhere?
  • How is this configured? (Check settings, config files, middleware)
  • What framework protections exist?

Do NOT report issues based solely on pattern matching. Investigate first, then report only what you're confident is exploitable.

Confidence Levels

LevelCriteriaAction
HIGHVulnerable pattern + attacker-controlled input confirmedReport with severity
MEDIUMVulnerable pattern, input source unclearNote as "Needs verification"
LOWTheoretical, best practice, defense-in-depthDo not report

Do Not Flag

General Rules

  • Test files (unless explicitly reviewing test security)
  • Dead code, commented code, documentation strings
  • Patterns using constants or server-controlled configuration
  • Code paths that require prior authentication to reach (note the auth requirement instead)

Server-Controlled Values (NOT Attacker-Controlled)

These are configured by operators, not controlled by attackers:

SourceExampleWhy It's Safe
Django settingssettings.API_URL, settings.ALLOWED_HOSTSSet via config/env at deployment
Environment variablesos.environ.get('DATABASE_URL')Deployment configuration
Config filesconfig.yaml, app.config['KEY']Server-side files
Framework constantsdjango.conf.settings.*Not user-modifiable
Hardcoded valuesBASE_URL = "https://api.internal"Compile-time constants

SSRF Example - NOT a vulnerability:

# SAFE: URL comes from Django settings (server-controlled)
response = requests.get(f"{settings.SEER_AUTOFIX_URL}{path}")

SSRF Example - IS a vulnerability:

# VULNERABLE: URL comes from request (attacker-controlled)
response = requests.get(request.GET.get('url'))

Framework-Mitigated Patterns

Check language guides before flagging. Common false positives:

PatternWhy It's Usually Safe
Django {{variable}}Auto-escaped by default
React {variable}Auto-escaped by default
Vue {{variable}}Auto-escaped by default
User.objects.filter(id=input)ORM parameterizes queries
cursor.execute("...%s", (input,))Parameterized query
innerHTML = "<b>Loading...</b>"Constant string, no user input

Only flag these when:

  • Django: {{var|safe}}, {% autoescape off %}, mark_safe(user_input)
  • React: dangerouslySetInnerHTML={{__html: userInput}}
  • Vue: v-html="userInput"
  • ORM: .raw(), .extra(), RawSQL() with string interpolation

Review Process

1. Detect Context

What type of code am I reviewing?

Code TypeLoad These References
API endpoints, routesauthorization.md, authentication.md, injection.md
Frontend, templatesxss.md, csrf.md
File handling, uploadsfile-security.md
Crypto, secrets, tokenscryptography.md, data-protection.md
Data serializationdeserialization.md
External requestsssrf.md
Business workflowsbusiness-logic.md
GraphQL, REST designapi-security.md
Config, headers, CORSmisconfiguration.md
CI/CD, dependenciessupply-chain.md
Error handlingerror-handling.md
Audit, logginglogging.md

2. Load Language Guide

Based on file extension or imports:

IndicatorsGuide
.py, django, flask, fastapilanguages/python.md
.js, .ts, express, react, vue, nextlanguages/javascript.md
.go, go.modlanguages/go.md
.rs, Cargo.tomllanguages/rust.md
.java, spring, @Controllerlanguages/java.md

3. Load Infrastructure Guide (if applicable)

File TypeGuide
Dockerfile, .dockerignoreinfrastructure/docker.md
K8s manifests, Helm chartsinfrastructure/kubernetes.md
.tf, Terraforminfrastructure/terraform.md
GitHub Actions, .gitlab-ci.ymlinfrastructure/ci-cd.md
AWS/GCP/Azure configs, IAMinfrastructure/cloud.md

4. Research Before Flagging

For each potential issue, research the codebase to build confidence:

  • Where does this value actually come from? Trace the data flow.
  • Is it configured at deployment (settings, env vars) or from user input?
  • Is there validation, sanitization, or allowlisting elsewhere?
  • What framework protections apply?

Only report issues where you have HIGH confidence after understanding the broader context.

5. Verify Exploitability

For each potential finding, confirm:

Is the input attacker-controlled?

Attacker-Controlled (Investigate)Server-Controlled (Usually Safe)
request.GET, request.POST, request.argssettings.X, app.config['X']
request.json, request.data, request.bodyos.environ.get('X')
request.headers (most headers)Hardcoded constants
request.cookies (unsigned)Internal service URLs from config
URL path segments: /users/<id>/Database content from admin/system
File uploads (content and names)Signed session data
Database content from other usersFramework settings
WebSocket messages

Does the framework mitigate this?

  • Check language guide for auto-escaping, parameterization
  • Check for middleware/decorators that sanitize

Is there validation upstream?

  • Input validation before this code
  • Sanitization libraries (DOMPurify, bleach, etc.)

6. Report HIGH Confidence Only

Skip theoretical issues. Report only what you've confirmed is exploitable after research.


Severity Classification

SeverityImpactExamples
CriticalDirect exploit, severe impact, no auth requiredRCE, SQL injection to data, auth bypass, hardcoded secrets
HighExploitable with conditions, significant impactStored XSS, SSRF to metadata, IDOR to sensitive data
MediumSpecific conditions required, moderate impactReflected XSS, CSRF on state-changing actions, path traversal
LowDefense-in-depth, minimal direct impactMissing headers, verbose errors, weak algorithms in non-critical context

Quick Patterns Reference

Always Flag (Critical)

eval(user_input)           # Any language
exec(user_input)           # Any language
pickle.loads(user_data)    # Python
yaml.load(user_data)       # Python (not safe_load)
unserialize($user_data)    # PHP
deserialize(user_data)     # Java ObjectInputStream
shell=True + user_input    # Python subprocess
child_process.exec(user)   # Node.js

Always Flag (High)

innerHTML = userInput              # DOM XSS
dangerouslySetInnerHTML={user}     # React XSS
v-html="userInput"                 # Vue XSS
f"SELECT * FROM x WHERE {user}"    # SQL injection
`SELECT * FROM x WHERE ${user}`    # SQL injection
os.system(f"cmd {user_input}")     # Command injection

Always Flag (Secrets)

password = "hardcoded"
api_key = "sk-..."
AWS_SECRET_ACCESS_KEY = "..."
private_key = "-----BEGIN"

Check Context First (MUST Investigate Before Flagging)

# SSRF - ONLY if URL is from user input, NOT from settings/config
requests.get(request.GET['url'])     # FLAG: User-controlled URL
requests.get(settings.API_URL)       # SAFE: Server-controlled config
requests.get(f"{settings.BASE}/{x}") # CHECK: Is 'x' user input?

# Path traversal - ONLY if path is from user input
open(request.GET['file'])            # FLAG: User-controlled path
open(settings.LOG_PATH)              # SAFE: Server-controlled config
open(f"{BASE_DIR}/{filename}")       # CHECK: Is 'filename' user input?

# Open redirect - ONLY if URL is from user input
redirect(request.GET['next'])        # FLAG: User-controlled redirect
redirect(settings.LOGIN_URL)         # SAFE: Server-controlled config

# Weak crypto - ONLY if used for security purposes
hashlib.md5(file_content)            # SAFE: File checksums, caching
hashlib.md5(password)                # FLAG: Password hashing
random.random()                      # SAFE: Non-security uses (UI, sampling)
random.random() for token            # FLAG: Security tokens need secrets module

Output Format

## Security Review: [File/Component Name]

### Summary
- **Findings**: X (Y Critical, Z High, ...)
- **Risk Level**: Critical/High/Medium/Low
- **Confidence**: High/Mixed

### Findings

#### [VULN-001] [Vulnerability Type] (Severity)
- **Location**: `file.py:123`
- **Confidence**: High
- **Issue**: [What the vulnerability is]
- **Impact**: [What an attacker could do]
- **Evidence**:

[Vulnerable code snippet]


- **Fix**: [How to remediate]

### Needs Verification

#### [VERIFY-001] [Potential Issue]

- **Location**: `file.py:456`
- **Question**: [What needs to be verified]

If no vulnerabilities found, state: "No high-confidence vulnerabilities identified."


Reference Files

Core Vulnerabilities (references/)

FileCovers
injection.mdSQL, NoSQL, OS command, LDAP, template injection
xss.mdReflected, stored, DOM-based XSS
authorization.mdAuthorization, IDOR, privilege escalation
authentication.mdSessions, credentials, password storage
cryptography.mdAlgorithms, key management, randomness
deserialization.mdPickle, YAML, Java, PHP deserialization
file-security.mdPath traversal, uploads, XXE
ssrf.mdServer-side request forgery
csrf.mdCross-site request forgery
data-protection.mdSecrets exposure, PII, logging
api-security.mdREST, GraphQL, mass assignment
business-logic.mdRace conditions, workflow bypass
modern-threats.mdPrototype pollution, LLM injection, WebSocket
misconfiguration.mdHeaders, CORS, debug mode, defaults
error-handling.mdFail-open, information disclosure
supply-chain.mdDependencies, build security
logging.mdAudit failures, log injection

Language Guides (languages/)

  • python.md - Django, Flask, FastAPI patterns
  • javascript.md - Node, Express, React, Vue, Next.js
  • go.md - Go-specific security patterns
  • rust.md - Rust unsafe blocks, FFI security
  • java.md - Spring, Java EE patterns

Infrastructure (infrastructure/)

  • docker.md - Container security
  • kubernetes.md - K8s RBAC, secrets, policies
  • terraform.md - IaC security
  • ci-cd.md - Pipeline security
  • cloud.md - AWS/GCP/Azure security

平台分布

Codex

33.19%
按下载量换算11,486

Claude

30.67%
按下载量换算10,614

Cursor

18.4%
按下载量换算6,368

Gemini CLI

9.82%
按下载量换算3,399

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

未通过

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。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

继续浏览同类 Skills