Agent skill

Code Review Security

by nicepkg in nicepkg/auto-company

Security-focused code review checklist and automated scanning patterns.

MITAuto-check passedSecurity

Install Code Review Security

skills CLI
$ npx skills add nicepkg/auto-company --skill code-review-security -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install nicepkg/auto-company code-review-security --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/nicepkg/auto-company.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.claude/skills/code-review-security .claude/skills/code-review-security && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
code-review-security
GitHub stars
192
Used in
1 other repo
Token cost
~3.9k tokens
SKILL.md length
1,094 words
Files
2 (incl. scripts)
Skills in repo
23
Repo updated
First seen
Licence
MIT

At a glance

Security-focused code review checklist and automated scanning patterns.

  • Reviewing pull requests for security issues
  • SKILL.md covers When to Use, Instructions and Examples
  • Runs Python scripts from its folder; calls npm; needs SECRET_KEY
  • Auditing authentication/authorization code

What it does

Code Review Security is an agent skill from nicepkg/auto-company. Security-focused code review checklist and automated scanning patterns. Use when reviewing pull requests for security issues, auditing authentication/authorization code, checking for OWASP Top 10 vulnerabilities, or validating input sanitization. Covers SQL injection prevention, XSS protection, CSRF tokens, authentication flow review, secrets detection, dependency vulnerability scanning, and secure coding patterns for Python (FastAPI) and React. Does NOT cover deployment security (use docker-best-practices) or…

Its SKILL.md is about 3.9k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files, including scripts (for example `scripts/security-scan.py`). Compatibility notes: Python 3.12+, FastAPI, React, TypeScript

It sits in Security, covering Web application vulnerabilities and Code review. It works with Python, FastAPI, React and Docker. The repository describes itself as: 🤖 A fully autonomous AI company that runs 24/7. 14 AI agents (Bezos, Munger, DHH...) brainstorm ideas, write code, deploy products & make money — no human in the loop. Powered… The licence is MIT.

When your agent uses it

  • Reviewing pull requests for security issues
  • Auditing authentication/authorization code
  • Checking for OWASP Top 10 vulnerabilities
  • Validating input sanitization

Example prompts

  • “/code-review-security”

Requirements

  • Python 3
  • Docker
  • A credential in SECRET_KEY
  • Compatibility (from SKILL.md): Python 3.12+, FastAPI, React, TypeScript
  • Pre-approved tools (allowed-tools): Read, Grep, Glob, Write, Bash(python:*), Bash(npm:*)

What it can do on your machine

Read from SKILL.md and the folder at commit 1252920. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • Read
    • Grep
    • Glob
    • Write
    • Bash(python:*)
    • Bash(npm:*)

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 1 file in scripts/ (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • npm

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md. Its commands use npm, which can reach the network depending on how they are called.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names these keys or tokens, usually read from environment variables:

    • SECRET_KEY

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

  • Compatibility

    Python 3.12+, FastAPI, React, TypeScript

    From compatibility in the SKILL.md frontmatter.

Context cost

Code Review Security loads about 3.9k tokens when it runs. Until then it costs about 145 tokens; SKILL.md has 1,094 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~145
When it runs · the whole SKILL.md, loaded when a task matches
~3.9k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from nicepkg/auto-company at commit 1252920, republished under its MIT licence (© nicepkg). 1,094 words, ~3,906 tokens.

Download SKILL.mdSave it as .claude/skills/code-review-security/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
code-review-security
description
Security-focused code review checklist and automated scanning patterns. Use when reviewing pull requests for security issues, auditing authentication/authorization code, checking for OWASP Top 10 vulnerabilities, or validating input sanitization. Covers SQL injection prevention, XSS protection, CSRF tokens, authentication flow review, secrets detection, dependency vulnerability scanning, and secure coding patterns for Python (FastAPI) and React. Does NOT cover deployment security (use docker-best-practices) or incident handling (use incident-response).
allowed-tools
Read, Grep, Glob, Write, Bash(python:*), Bash(npm:*)
compatibility
Python 3.12+, FastAPI, React, TypeScript
license
MIT
metadata.author
security-team
metadata.version
1.0.0
metadata.sdlc-phase
code-review
context
fork

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:

python
# 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:

python
# 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:

python
# 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:

python
# 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:

python
# 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)

Show full SKILL.md (427 more words)Show less
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:

python
# 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:

tsx
// 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:

markdown
## 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
```python
# The problematic code
vulnerable_function(user_input)
python
# 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):**
```bash
# 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:

markdown
# 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

© nicepkg, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 1 other file (scripts) in .claude/skills/code-review-security of nicepkg/auto-company.

  • SKILL.md
  • scripts/security-scan.py

Open the folder on GitHubat commit 1252920

Used in 1 other repository

We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in nicepkg/auto-company, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Code Review Security next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

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Security Analyzeraiskillstore/marketplace430—~1.2kAutomated safety check: NotesNone
Code Review Skillawesome-skills/code-review-skill2.1k—~2.8kAutomated safety check: NotesMIT

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Questions about Code Review Security

What does Code Review Security do?

Security-focused code review checklist and automated scanning patterns. Code Review Security is an agent skill from nicepkg/auto-company. Security-focused code review checklist and automated scanning patterns.

When should I use Code Review Security?

Code Review Security fits situations like: reviewing pull requests for security issues; auditing authentication/authorization code; checking for OWASP Top 10 vulnerabilities; validating input sanitization.

How do I install Code Review Security in Claude Code?

Run `npx skills add nicepkg/auto-company --skill code-review-security -a claude-code`. Or copy the skill folder (.claude/skills/code-review-security in nicepkg/auto-company) into .claude/skills/code-review-security in your project. Claude Code loads it when a task matches its description.

How do I install Code Review Security in Codex?

Run `npx skills add nicepkg/auto-company --skill code-review-security -a codex`. Or copy the skill folder (.claude/skills/code-review-security in nicepkg/auto-company) into .agents/skills/code-review-security in your project. Codex loads it when a task matches its description.

Can I use Code Review Security in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add nicepkg/auto-company --skill code-review-security -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/code-review-security, .gemini/skills/code-review-security, .github/skills/code-review-security and .opencode/skills/code-review-security in your project.

What does Code Review Security need to run?

Going by SKILL.md and its folder, Code Review Security needs Python for the scripts in its folder, the command-line tools its instructions call (npm) and credentials named SECRET_KEY. Our summary lists: Python 3; Docker; A credential in SECRET_KEY. Its frontmatter pre-approves these tools: Read, Grep, Glob, Write, Bash(python:*), Bash(npm:*). Compatibility (from SKILL.md): Python 3.12+, FastAPI, React, TypeScript.

Does Code Review Security access the network?

SKILL.md contains no URLs. Its commands use npm, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Code Review Security safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Code Review Security use?

Code Review Security is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Code Review Security use?

About 3.9k tokens (SKILL.md is roughly 16k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Code Review Security?

Skills that share tags, products or a category with Code Review Security: Create PR (beyonders-studio/initiative, 170 stars), Cyber Neo (Hainrixz/cyber-neo, 281 stars), Flowfile Debugging Playbook (Edwardvaneechoud/Flowfile, 370 stars) and Security Analyzer (aiskillstore/marketplace, 430 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Code Review Security?

nicepkg (a GitHub organization) maintains it in nicepkg/auto-company, which has 192 GitHub stars. The repository holds 23 skills in this directory. The repository was last updated on February 12, 2026.

Source: nicepkg/auto-company on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.