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研究检索敏感数据github未标认证来源可访问许可证需确认审计异常

code-review-security代码审查安全

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

6,360

周安装

265

GitHub Stars

8

下载量

2,120
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:code-review-security(代码审查安全)
来源仓库:https://github.com/hieutrtr/ai1-skills
仓库路径:skills/code-review-security
安装命令:
npx skills add https://github.com/hieutrtr/ai1-skills --skill code-review-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/hieutrtr/ai1-skills --skill code-review-security

简介

Code Review Security 专注于安全漏洞检测,覆盖认证授权、输入处理和依赖风险等关键领域。

  • 适用于敏感数据处理模块或外部接口变更的安全复核,可识别 OWASP Top 10 威胁。
  • 输出写入 security-review.md 文件,包含严重等级、位置描述和改进建议。
  • 不得用于部署配置或生产环境操作,仅限开发阶段代码分析用途。
  • code-review-security 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

Code Review Security

When to Use

Activate this skill when:

  • Reviewing pull requests for security vulnerabilities
  • Auditing authentication or authorization code changes
  • Reviewing code that handles user input, file uploads, or external data
  • Checking for OWASP Top 10 vulnerabilities in new features
  • Validating that secrets are not committed to the repository
  • Scanning dependencies for known vulnerabilities
  • Reviewing API endpoints that expose sensitive data

Output: Write findings to security-review.md with severity, file:line, description, and recommendations.

Do NOT use this skill for:

  • Deployment infrastructure security (use docker-best-practices)
  • Incident response procedures (use incident-response)
  • General code quality review without security focus (use pre-merge-checklist)
  • Writing implementation code (use python-backend-expert or react-frontend-expert)

Instructions

OWASP Top 10 Checklist

Review every PR against the OWASP Top 10 (2021 edition). Each category below includes specific checks for Python/FastAPI and React codebases.


A01: Broken Access Control

What to look for:

  • Missing authorization checks on endpoints
  • Direct object reference without ownership verification
  • Endpoints that expose data without role-based filtering
  • Missing Depends() for auth on new routes

Python/FastAPI checks:

# BAD: No authorization check -- any authenticated user can access any user
@router.get("/users/{user_id}")
async def get_user(user_id: int, db: Session = Depends(get_db)):
    return await user_repo.get(user_id)

# GOOD: Verify the requesting user owns the resource or is admin
@router.get("/users/{user_id}")
async def get_user(
    user_id: int,
    current_user: User = Depends(get_current_user),
    db: Session = Depends(get_db),
):
    if current_user.id != user_id and current_user.role != "admin":
        raise HTTPException(status_code=403, detail="Forbidden")
    return await user_repo.get(user_id)

Review checklist:

  • Every route has authentication (Depends(get_current_user))
  • Resource access is verified against the requesting user
  • Admin-only endpoints check role == "admin"
  • List endpoints filter by user ownership (unless admin)
  • No IDOR (Insecure Direct Object Reference) vulnerabilities

A02: Cryptographic Failures

What to look for:

  • Passwords stored in plaintext or with weak hashing
  • Sensitive data in logs or error messages
  • Hardcoded secrets, API keys, or tokens
  • Weak JWT configuration

Python checks:

# BAD: Weak password hashing
import hashlib
password_hash = hashlib.md5(password.encode()).hexdigest()

# GOOD: Use bcrypt via passlib
from passlib.context import CryptContext
pwd_context = CryptContext(schemes=["bcrypt"], deprecated="auto")
password_hash = pwd_context.hash(password)

# BAD: Secret in code
SECRET_KEY = "my-super-secret-key-123"

# GOOD: Secret from environment
SECRET_KEY = os.environ["SECRET_KEY"]

Review checklist:

  • Passwords hashed with bcrypt (never MD5, SHA1, or plaintext)
  • JWT secret loaded from environment, not hardcoded
  • Sensitive data excluded from logs (passwords, tokens, PII)
  • HTTPS enforced for all external communication
  • No secrets in source code (check .env.example has placeholders only)

A03: Injection

What to look for:

  • Raw SQL queries with string interpolation
  • eval(), exec(), compile() with user input
  • subprocess calls with shell=True
  • Template injection

Python checks:

# BAD: SQL injection via string formatting
query = f"SELECT * FROM users WHERE email = '{email}'"
db.execute(text(query))

# GOOD: Parameterized query
db.execute(text("SELECT * FROM users WHERE email = :email"), {"email": email})

# GOOD: SQLAlchemy ORM (always parameterized)
user = db.query(User).filter(User.email == email).first()

# BAD: Command injection
subprocess.run(f"convert {filename}", shell=True)

# GOOD: Pass arguments as a list
subprocess.run(["convert", filename], shell=False)

# BAD: Code execution with user input
result = eval(user_input)

# GOOD: Never eval user input. Use ast.literal_eval for safe parsing.
result = ast.literal_eval(user_input)  # Only for literal structures

Review checklist:

  • No raw SQL with string interpolation (use ORM or parameterized queries)
  • No eval(), exec(), or compile() with external input
  • No subprocess.run(..., shell=True) with dynamic arguments
  • No pickle.loads() on untrusted data
  • All user input validated by Pydantic schemas before use

A04: Insecure Design

What to look for:

  • Missing rate limiting on authentication endpoints
  • No account lockout after failed login attempts
  • Missing CAPTCHA on public-facing forms
  • Business logic flaws (e.g., negative amounts, self-privilege-escalation)

Review checklist:

  • Rate limiting on login, registration, and password reset
  • Account lockout or exponential backoff after 5+ failed attempts
  • Business logic validates constraints (positive amounts, valid transitions)
  • Sensitive operations require re-authentication

A05: Security Misconfiguration

What to look for:

  • Debug mode enabled in production
  • CORS configured with wildcard * origins
  • Default credentials or admin accounts
  • Verbose error messages exposing stack traces

Python/FastAPI checks:

# BAD: Wide-open CORS
app.add_middleware(CORSMiddleware, allow_origins=["*"])

# GOOD: Explicit allowed origins
app.add_middleware(
    CORSMiddleware,
    allow_origins=["https://app.example.com"],
    allow_methods=["GET", "POST", "PUT", "DELETE"],
    allow_headers=["Authorization", "Content-Type"],
)

# BAD: Debug mode in production
app = FastAPI(debug=True)

# GOOD: Debug only in development
app = FastAPI(debug=settings.DEBUG)  # DEBUG=False in production

Review checklist:

  • CORS origins are explicit (no wildcard in production)
  • Debug mode disabled in production configuration
  • Error responses do not expose stack traces or internal details
  • Default admin credentials are changed or removed
  • Security headers set (X-Content-Type-Options, X-Frame-Options, etc.)

A06: Vulnerable and Outdated Components

Review checklist:

  • No known CVEs in Python dependencies (pip-audit or safety check)
  • No known CVEs in npm dependencies (npm audit)
  • Dependencies pinned to specific versions in lock files
  • No deprecated packages still in use

A07: Identification and Authentication Failures

What to look for:

  • Weak password policies
  • Session tokens that do not expire
  • Missing multi-factor authentication for admin actions
  • JWT tokens without expiration

Python checks:

# BAD: JWT without expiration
token = jwt.encode({"sub": user_id}, SECRET_KEY, algorithm="HS256")

# GOOD: JWT with expiration
token = jwt.encode(
    {"sub": user_id, "exp": datetime.utcnow() + timedelta(minutes=30)},
    SECRET_KEY,
    algorithm="HS256",
)

Review checklist:

  • JWT tokens have expiration (exp claim)
  • Refresh tokens are stored securely and can be revoked
  • Password policy enforces minimum length (12+) and complexity
  • Session invalidation on password change or logout
  • No user enumeration via login error messages

A08: Software and Data Integrity Failures

Review checklist:

  • CI/CD pipeline validates artifact integrity
  • No unsigned or unverified packages
  • Deserialization of untrusted data uses safe methods (no pickle.loads)
  • Database migrations are reviewed before execution

A09: Security Logging and Monitoring Failures

Review checklist:

  • Authentication events are logged (login, logout, failed attempts)
  • Authorization failures are logged with context
  • Sensitive data is NOT included in logs (passwords, tokens, PII)
  • Log entries include timestamp, user ID, IP address, action
  • Alerting configured for suspicious patterns (brute force, unusual access)

A10: Server-Side Request Forgery (SSRF)

What to look for:

  • User-supplied URLs used in server-side requests
  • Redirect endpoints that accept arbitrary URLs

Python checks:

# BAD: Fetch arbitrary URL from user input
url = request.query_params["url"]
response = httpx.get(url)  # SSRF: can access internal services

# GOOD: Validate URL against allowlist
ALLOWED_HOSTS = {"api.example.com", "cdn.example.com"}
parsed = urlparse(url)
if parsed.hostname not in ALLOWED_HOSTS:
    raise HTTPException(400, "URL not allowed")
response = httpx.get(url)

Review checklist:

  • No server-side requests to user-controlled URLs without validation
  • URL allowlists used for external integrations
  • Internal service URLs not exposed in error messages

Python-Specific Security Checks

Beyond OWASP, review Python code for these patterns:

PatternRiskFix
eval(user_input)Remote code executionRemove or use ast.literal_eval
pickle.loads(data)Arbitrary code executionUse JSON or msgpack
subprocess.run(cmd, shell=True)Command injectionPass args as list, shell=False
yaml.load(data)Code executionUse yaml.safe_load(data)
os.system(cmd)Command injectionUse subprocess.run([...])
Raw SQL stringsSQL injectionUse ORM or parameterized queries
hashlib.md5(password)Weak hashingUse bcrypt via passlib
jwt.decode(token, options={"verify_signature": False})Auth bypassAlways verify signature
open(user_path)Path traversalValidate path, use pathlib.resolve()
tempfile.mktemp()Race conditionUse tempfile.mkstemp()

React-Specific Security Checks

PatternRiskFix
dangerouslySetInnerHTMLXSSUse text content or sanitize with DOMPurify
javascript: in hrefXSSValidate URLs, allow only https:
window.location = userInputOpen redirectValidate against allowlist
Storing tokens in localStorageToken theft via XSSUse httpOnly cookies
Inline event handlers from dataXSSUse React event handlers
eval() or Function()Code executionRemove entirely
Rendering user HTMLXSSUse a sanitization library

React code review:

// BAD: XSS via dangerouslySetInnerHTML
<div dangerouslySetInnerHTML={{ __html: userBio }} />

// GOOD: Sanitize first, or use text content
import DOMPurify from "dompurify";
<div dangerouslySetInnerHTML={{ __html: DOMPurify.sanitize(userBio) }} />

// BETTER: Use text content when HTML is not needed
<p>{userBio}</p>

// BAD: javascript: URL
<a href={userLink}>Click</a>  // userLink could be "javascript:alert(1)"

// GOOD: Validate protocol
const safeHref = /^https?:\/\//.test(userLink) ? userLink : "#";
<a href={safeHref}>Click</a>

Severity Classification

Classify each finding by severity for prioritization:

SeverityDescriptionExamplesSLA
CriticalExploitable remotely, no auth needed, data breachSQL injection, RCE, auth bypassBlock merge, fix immediately
HighExploitable with auth, privilege escalationIDOR, broken access control, XSS (stored)Block merge, fix before release
MediumRequires specific conditions to exploitCSRF, XSS (reflected), open redirectFix within sprint
LowDefense-in-depth, informationalMissing headers, verbose errorsFix when convenient
InfoBest practice recommendationsDependency updates, code styleTrack in backlog

Finding Report Format

When reporting security findings, use this format for consistency:

## Security Finding: [Title]

**Severity:** Critical | High | Medium | Low | Info
**Category:** OWASP A01-A10 or custom category
**File:** path/to/file.py:42
**CWE:** CWE-89 (if applicable)

### Description
Brief description of the vulnerability and its impact.

### Vulnerable Code

The problematic code

vulnerable_function(user_input)


### Recommended Fix

The secure alternative

safe_function(sanitize(user_input))


### Impact

What an attacker could achieve by exploiting this vulnerability.

### References

- Link to relevant OWASP page
- Link to relevant CWE entry

Automated Scanning

Use scripts/security-scan.py to perform AST-based scanning for common vulnerability patterns in Python code. The script scans for:

  • eval() / exec() / compile() calls
  • subprocess with shell=True
  • pickle.loads() on potentially untrusted data
  • Raw SQL string construction
  • yaml.load() without Loader=SafeLoader
  • Hardcoded secret patterns (API keys, passwords)
  • Weak hash functions (MD5, SHA1 for passwords)

Run: python scripts/security-scan.py --path ./app --output-dir ./security-results

Dependency scanning (run separately):

# Python dependencies
pip-audit --requirement requirements.txt --output json > dep-audit.json

# npm dependencies
npm audit --json > npm-audit.json

Examples

Example Review Comment (Critical)

SECURITY: SQL Injection (Critical, OWASP A03) File: app/repositories/user_repository.py:47 ``python query = f"SELECT * FROM users WHERE name LIKE '%{search_term}%'" ` This constructs a raw SQL query with string interpolation, allowing SQL injection. An attacker could input '; DROP TABLE users; -- to destroy data. **Fix:** Use SQLAlchemy ORM filtering: `python users = db.query(User).filter(User.name.ilike(f"%{search_term}%")).all() ``

Example Review Comment (Medium)

SECURITY: Missing Rate Limiting (Medium, OWASP A04) File: app/routes/auth.py:12 The /auth/login endpoint has no rate limiting. An attacker could perform brute-force password attacks at unlimited speed. Fix: Add rate limiting middleware: ``python from slowapi import Limiter limiter = Limiter(key_func=get_remote_address) @router.post("/login") @limiter.limit("5/minute") async def login(request: Request, ...): ``

Output File

Write security findings to security-review.md:

# Security Review: [Feature/PR Name]

## Summary
- Critical: 0 | High: 1 | Medium: 2 | Low: 1

## Findings

### [CRITICAL] SQL Injection in user search
- **File:** app/routes/users.py:45
- **OWASP:** A03 Injection
- **Description:** Raw SQL with string interpolation
- **Recommendation:** Use SQLAlchemy ORM filtering

### [HIGH] Missing authorization check
...

## Passed Checks
- No hardcoded secrets found
- Dependencies up to date

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能力概览

能力 1

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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

37.31%
按下载量换算791

Claude

29.58%
按下载量换算627

Cursor

19.06%
按下载量换算404

Gemini CLI

10.36%
按下载量换算220

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

未通过

权限和风险

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。

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来源信息

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