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auth技能安全扫描

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

275

周安装

11

GitHub Stars

9

下载量

89
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

2

许可证

unknown

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:auth(技能安全扫描)
来源仓库:https://github.com/florianbuetow/claude-code
仓库路径:skills/auth
安装命令:
npx skills add https://github.com/florianbuetow/claude-code --skill auth
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/florianbuetow/claude-code --skill auth

简介

用于安全审计、权限检查和认证流程分析。

  • 适合梳理敏感配置和生成安全复核清单。
  • 不能将工具输出直接作为最终结论。auth 属于研究检索类 Skill,可作为该场景下的辅助能力补充。
  • 涉及密钥或生产系统时需确认最小权限。
  • 安装前应核实操作边界和脱敏方式。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

Identification and Authentication Failures

Analyze source code for authentication and session management vulnerabilities. Detect weak credential handling, missing brute force protections, insecure session management, and absent multi-factor authentication. Produce actionable findings with severity ratings, code locations, and concrete remediation steps.

Supported Flags

All flags from ../../shared/schemas/flags.md are supported:

FlagRelevant Behavior
--scope <value>Determines which files to analyze (default: changed)
--depth <value>quick: pattern scan only. standard: full read + analysis. deep: trace auth flows cross-file. expert: red team simulation with DREAD scoring
--severity <value>Filter findings by minimum severity
--format <value>Output format: text, json, sarif, md
--fixChain into remediation after analysis
--quietFindings only, no explanations
--explainAdd learning context to each finding

Framework Context

OWASP Top 10 2021 - A07: Identification and Authentication Failures

Confirmation of the user's identity, authentication, and session management is critical to protect against authentication-related attacks. Applications are vulnerable when they:

  • Permit automated attacks such as credential stuffing or brute force
  • Permit default, weak, or well-known passwords
  • Use weak credential recovery processes (e.g., knowledge-based answers)
  • Store passwords in plain text, encrypted, or with weak hashes (MD5, SHA1)
  • Lack or have ineffective multi-factor authentication
  • Expose session identifiers in URLs
  • Reuse session identifiers after successful login
  • Fail to properly invalidate sessions on logout or timeout

STRIDE Mapping: Spoofing, Repudiation

CWE References: CWE-287 (Improper Authentication), CWE-384 (Session Fixation), CWE-307 (Brute Force), CWE-521 (Weak Password Requirements), CWE-916 (Weak Password Hash), CWE-613 (Insufficient Session Expiration), CWE-308 (Missing MFA)

Detection Patterns

Read references/detection-patterns.md before performing analysis. It contains detailed Grep heuristics, language-specific code examples, scanner coverage, and false positive guidance for each vulnerability pattern.

Workflow

1. Determine Scope

Parse --scope flag and resolve to a concrete file list:

  1. Apply scope resolution per ../../shared/schemas/flags.md.
  2. Filter to files relevant to authentication:

- Route handlers, middleware, and controllers (login, register, password reset endpoints) - Authentication modules and services - Session configuration files - Password hashing and validation utilities - JWT/token generation and validation code - OAuth/OIDC integration code - Configuration files (session timeout, password policy settings)

  1. Include framework-specific auth files (e.g., passport.js configs, Django auth backends, Spring Security configs, Go auth middleware).

2. Check for Scanners

Detect available scanners in order of preference:

ScannerDetectRelevant Rules
semgrepwhich semgrepAuth bypass, weak hashing, JWT issues, session management
banditwhich banditHardcoded passwords, weak hashes (Python)
gosecwhich gosecHardcoded credentials, weak crypto (Go)
gitleakswhich gitleaksHardcoded secrets, API keys, passwords in code

If no scanner is available, proceed with Claude analysis using Grep patterns from references/detection-patterns.md. Note in output: "No scanner available -- findings based on code pattern analysis only."

3. Run Scanners

For each available scanner:

  1. Execute against the scoped file list.
  2. Parse JSON output.
  3. Filter to authentication-related rules only.
  4. Normalize findings to the schema in ../../shared/schemas/findings.md.
  5. Set scanner.confirmed: true for scanner-detected findings.

4. Claude Analysis

Regardless of scanner availability, perform manual code analysis:

  1. Read references/detection-patterns.md for the full pattern catalog.
  2. Use Grep with the regex patterns to locate suspicious constructs.
  3. Read surrounding code context (30-50 lines) to assess each match.
  4. Trace authentication flows from entry point to credential validation.
  5. At --depth deep or higher: follow imports, trace session lifecycle, map the complete auth flow across files.
  6. Deduplicate against scanner findings (same file + line = same finding).
  7. Set confidence: medium for Claude-only findings, confidence: high when confirmed by a scanner.

5. Report Findings

Format output per --format flag. Each finding uses the schema from ../../shared/schemas/findings.md with these specifics:

  • ID prefix: AUTH (e.g., AUTH-001, AUTH-002)
  • references.owasp: A07:2021
  • references.stride: S (Spoofing) or R (Repudiation)
  • metadata.tool: auth
  • metadata.framework: owasp
  • metadata.category: A07

Summary block (appended after all findings):

## Summary

| Severity | Count |
|----------|-------|
| CRITICAL | N     |
| HIGH     | N     |
| MEDIUM   | N     |
| LOW      | N     |

**Scanners used**: [list or "none"]
**Scanners missing**: [list of recommended but unavailable]
**Top priorities**: [top 3 findings to fix first and why]

What to Look For

These are the primary vulnerability patterns. See references/detection-patterns.md for detailed regex patterns and code examples.

  1. Missing rate limiting on login -- No throttling, delay, or account lockout on authentication endpoints, enabling brute force and credential stuffing.
  2. Weak password validation -- No complexity requirements, missing minimum length checks, or no check against common password lists.
  3. Plaintext or weakly hashed passwords -- Passwords stored with MD5, SHA1, plain SHA256, or without salting. Must use Argon2, bcrypt, or scrypt.
  4. Session ID in URL parameters -- Session tokens passed via query strings, visible in logs, referrer headers, and browser history.
  5. Missing session regeneration after login -- Same session ID used before and after authentication, enabling session fixation attacks.
  6. JWT with none algorithm accepted -- JWT verification allows alg: "none", letting attackers forge unsigned tokens.
  7. Hardcoded JWT secrets -- Signing keys embedded in source code rather than loaded from environment or secrets management.
  8. Missing or ineffective MFA -- No multi-factor authentication on sensitive operations, or MFA that can be bypassed.
  9. Insufficient session invalidation -- Sessions not destroyed on logout, or no server-side session expiration/timeout.

Scanner Integration

Refer to ../../shared/schemas/scanners.md for full scanner details.

Primary: semgrep (broad auth rule coverage across languages) Secondary: bandit (Python), gosec (Go), gitleaks (hardcoded credentials) Fallback: Grep-based pattern matching from references/detection-patterns.md

When running as a subagent of the OWASP dispatcher, receive scope and flags from the parent agent prompt. Do not re-parse user input.

Output Format

All findings conform to the schema defined in ../../shared/schemas/findings.md.

ID prefix: AUTH (registered in the ID Prefix Registry as OWASP A07)

Example finding:

{
  "id": "AUTH-001",
  "title": "Passwords hashed with MD5 in user registration",
  "severity": "critical",
  "confidence": "high",
  "location": {
    "file": "src/auth/register.py",
    "line": 34,
    "function": "create_user",
    "snippet": "password_hash = hashlib.md5(password.encode()).hexdigest()"
  },
  "description": "User passwords are hashed with MD5, which is cryptographically broken and trivially reversible with rainbow tables or GPU cracking.",
  "impact": "An attacker with database access can recover all user passwords within minutes, enabling account takeover across the application and any services where users reuse passwords.",
  "fix": {
    "summary": "Replace MD5 with bcrypt or Argon2id",
    "diff": "- password_hash = hashlib.md5(password.encode()).hexdigest()\n+ password_hash = bcrypt.hashpw(password.encode(), bcrypt.gensalt())"
  },
  "references": {
    "cwe": "CWE-916",
    "owasp": "A07:2021",
    "stride": "S"
  },
  "metadata": {
    "tool": "auth",
    "framework": "owasp",
    "category": "A07"
  }
}

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

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

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

Codex

36.13%
按下载量换算32

Claude

29.29%
按下载量换算26

Cursor

19.88%
按下载量换算18

Gemini CLI

9.18%
按下载量换算8

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

未通过

权限和风险

操作浏览器

该 Skill 可能涉及浏览器控制能力,使用时可能读取或操作网页内容,需要在受控环境中确认权限边界。

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 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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