Secure Code Review

OWASP Top 10 Code Security Review Checklist

A systematic security review based on the OWASP Top 10 (2021) standard. Each item includes: vulnerability description, typical vulnerable code, inspection checkpoints, and remediation examples. Designed for security-focused code review of web applications.

Usage

Provide the code files or code snippets to review, and specify which OWASP categories to check (or request a full review) to receive an item-by-item audit report.

Example prompts:

• "Check this code for SQL injection risks"
• "Run a full OWASP Top 10 security review on this project"
• "Does this API endpoint have any SSRF vulnerabilities?"

Quick Reference

Review Process SOP

Core principle: prefer false positives over missed true positives.

1. Define scope — Identify the files, modules, or code snippets to review
2. Full coverage check — Scan through A01-A10 sequentially. Every item must appear in the report (mark items with no findings as pass). The default behavior is to only report issues found — this process requires full coverage to ensure nothing is missed
3. Risk classification — Label each finding:
   • RED High: Directly exploitable (RCE, SQL injection, SSRF reaching internal networks, plaintext password storage)
   • YELLOW Medium: Exploitable under specific conditions (missing rate limiting, weak password policy, static tokens)
   • GREEN Low: Defense-in-depth gap with no direct exploitation path (missing security headers, insufficient logging)
4. Every finding must include ready-to-use fix code (actual code, not just a description). Reference specific file:line_number
5. Output the review report — Use the template below, findings sorted by severity descending, with a prioritized remediation list at the end

A01:2021 — Broken Access Control

Risk: Users can access other users' data or perform unauthorized operations.

Checkpoints:

• Does every API endpoint enforce authorization?
• Are there IDOR vulnerabilities (Insecure Direct Object References) — can users access others' data by modifying ID parameters?
• Do admin interfaces verify roles?
• Is access control enforced server-side (not just by hiding UI elements)?
• Is the CORS policy overly permissive?

Vulnerable Code Example

pythonCopy code
# ❌ Vulnerable: No authorization check — any user can view others' orders by changing user_id
@app.route("/api/orders/<user_id>")
def get_orders(user_id):
    orders = db.query(f"SELECT * FROM orders WHERE user_id = {user_id}")
    return jsonify(orders)

Remediation Example

pythonCopy code
# ✅ Fixed: Verify the authenticated user can only access their own data
@app.route("/api/orders")
@login_required
def get_orders():
    current_user_id = get_current_user().id
    orders = db.query("SELECT * FROM orders WHERE user_id = %s", (current_user_id,))
    return jsonify(orders)

A02:2021 — Cryptographic Failures

Risk: Sensitive data (passwords, credit card numbers, personal information) is unencrypted or uses weak cryptographic algorithms.

Checkpoints:

• Are passwords stored using secure hashing (bcrypt/scrypt/argon2) rather than MD5/SHA1?
• Is HTTPS enforced for sensitive data in transit?
• Are encryption keys hardcoded in the source code?
• Are deprecated cryptographic algorithms in use (DES, RC4, MD5)?
• Are sensitive database fields encrypted at rest?

Vulnerable Code Example

pythonCopy code
# ❌ Vulnerable: MD5 for password storage, hardcoded secret key
import hashlib

SECRET_KEY = "my-secret-key-123"

def save_password(password):
    hashed = hashlib.md5(password.encode()).hexdigest()
    db.save(hashed)

Remediation Example

pythonCopy code
# ✅ Fixed: bcrypt for password hashing, secret key from environment variable
import bcrypt
import os

SECRET_KEY = os.environ["SECRET_KEY"]

def save_password(password):
    salt = bcrypt.gensalt()
    hashed = bcrypt.hashpw(password.encode(), salt)
    db.save(hashed)

A03:2021 — Injection

Risk: User input is concatenated directly into SQL, OS commands, LDAP queries, etc., allowing attackers to execute arbitrary queries or commands.

Checkpoints:

• Do SQL queries use parameterized queries / ORM (not string concatenation)?
• Are there os.system() or subprocess.call(shell=True) calls that concatenate user input?
• Does template rendering properly escape user input (preventing XSS)?
• Are special characters filtered in LDAP / XPath / NoSQL queries?
• Are unfiltered user inputs logged directly (log injection)?

SQL Injection — Vulnerable Code

pythonCopy code
# ❌ Vulnerable: String-concatenated SQL — attacker can input ' OR 1=1 --
@app.route("/api/user")
def get_user():
    username = request.args.get("username")
    query = f"SELECT * FROM users WHERE username = '{username}'"
    result = db.execute(query)
    return jsonify(result)

SQL Injection — Remediation

pythonCopy code
# ✅ Fixed: Parameterized query
@app.route("/api/user")
def get_user():
    username = request.args.get("username")
    result = db.execute(
        "SELECT * FROM users WHERE username = %s",
        (username,)
    )
    return jsonify(result)

Command Injection — Vulnerable Code

pythonCopy code
# ❌ Vulnerable: User input concatenated directly into shell command
import os

def ping_host(host):
    os.system(f"ping -c 4 {host}")

Command Injection — Remediation

pythonCopy code
# ✅ Fixed: Use subprocess with list arguments, shell disabled
import subprocess
import re

def ping_host(host):
    if not re.match(r'^[a-zA-Z0-9.\-]+$', host):
        raise ValueError("Invalid hostname")
    subprocess.run(["ping", "-c", "4", host], check=True)

A04:2021 — Insecure Design

Risk: Business logic design flaws that cannot be fixed by a perfect implementation.

Checkpoints:

• Do critical operations have rate limiting?
• Can the password reset flow be abused (username enumeration, verification code brute-force)?
• Do sensitive operations (payments, transfers) require secondary confirmation?
• Are there batch operation endpoints with no upper limit?
• Can business workflows be executed out of order (e.g., skipping payment to complete an order)?

Vulnerable Code Example

pythonCopy code
# ❌ Vulnerable: No attempt limit on verification code — can be brute-forced
@app.route("/api/verify-code", methods=["POST"])
def verify_code():
    code = request.json["code"]
    stored_code = session.get("verification_code")
    if code == stored_code:
        return jsonify({"status": "verified"})
    return jsonify({"status": "invalid"}), 400

Remediation Example

pythonCopy code
# ✅ Fixed: Added attempt limit and expiration
@app.route("/api/verify-code", methods=["POST"])
def verify_code():
    attempts = session.get("verify_attempts", 0)
    if attempts >= 5:
        return jsonify({"error": "Too many attempts, please request a new code"}), 429

    code = request.json["code"]
    stored = session.get("verification_code")
    expire_at = session.get("code_expire_at", 0)

    if time.time() > expire_at:
        return jsonify({"error": "Verification code has expired"}), 400

    session["verify_attempts"] = attempts + 1

    if code == stored:
        session.pop("verify_attempts", None)
        return jsonify({"status": "verified"})
    return jsonify({"status": "invalid"}), 400

A05:2021 — Security Misconfiguration

Risk: Applications or servers use default configurations, enable unnecessary features, or expose sensitive information in error messages.

Checkpoints:

• Is DEBUG mode disabled in production?
• Do error pages leak stack traces, database versions, etc.?
• Are default credentials still in use?
• Do HTTP responses include security headers (X-Frame-Options, Content-Security-Policy, etc.)?
• Are unnecessary HTTP methods (PUT, DELETE, TRACE) disabled?
• Is directory listing disabled?

Vulnerable Code Example

pythonCopy code
# ❌ Vulnerable: DEBUG enabled in production, leaking sensitive information
app = Flask(__name__)
app.config["DEBUG"] = True
app.config["SECRET_KEY"] = "default-secret"

@app.errorhandler(500)
def error_handler(e):
    return jsonify({"error": str(e), "traceback": traceback.format_exc()}), 500

Remediation Example

pythonCopy code
# ✅ Fixed: Configuration from environment variables, DEBUG off in production
import os

app = Flask(__name__)
app.config["DEBUG"] = os.environ.get("FLASK_DEBUG", "false").lower() == "true"
app.config["SECRET_KEY"] = os.environ["FLASK_SECRET_KEY"]

@app.errorhandler(500)
def error_handler(e):
    app.logger.error(f"Internal error: {e}")
    return jsonify({"error": "Internal server error, please try again later"}), 500

A06:2021 — Vulnerable and Outdated Components

Risk: Using third-party libraries or framework versions with known vulnerabilities.

Checkpoints:

• Do dependencies have known CVEs (scan with pip audit, npm audit, snyk, etc.)?
• Are there dependencies that haven't been updated in a long time?
• Are any unmaintained libraries in use?
• Are lock files (package-lock.json / requirements.txt) under version control?
• Is there an automated dependency update mechanism (Dependabot, etc.)?

Scan Commands

bashCopy code
# Python projects
pip audit

# Node.js projects
npm audit

# General scanning
# Use open-source tools like trivy or grype to scan container/project dependencies

Remediation Guidance

bashCopy code
# Update vulnerable packages
pip install --upgrade package_name

# Auto-fix npm vulnerabilities
npm audit fix

# Pin dependency versions to prevent implicit upgrades
pip freeze > requirements.txt

A07:2021 — Identification and Authentication Failures

Risk: Authentication mechanisms have flaws that allow brute-force attacks, credential stuffing, or session hijacking.

Checkpoints:

• Is there a login failure rate limit (account lockout / delay)?
• Is the password policy reasonable (minimum length, complexity requirements)?
• Are session tokens invalidated on logout?
• Are session IDs sufficiently random and unpredictable?
• Is MFA supported for sensitive operations?
• Are JWT tokens validated for signature and expiration?

Vulnerable Code Example

pythonCopy code
# ❌ Vulnerable: JWT signature not verified, accepts alg=none
import jwt

def verify_token(token):
    payload = jwt.decode(token, options={"verify_signature": False})
    return payload

Remediation Example

pythonCopy code
# ✅ Fixed: Enforce signature and expiration verification, specify algorithm
import jwt
import os

JWT_SECRET = os.environ["JWT_SECRET"]

def verify_token(token):
    try:
        payload = jwt.decode(
            token,
            JWT_SECRET,
            algorithms=["HS256"],
            options={"require": ["exp", "iat", "sub"]}
        )
        return payload
    except jwt.ExpiredSignatureError:
        raise AuthError("Token has expired")
    except jwt.InvalidTokenError:
        raise AuthError("Invalid token")

A08:2021 — Software and Data Integrity Failures

Risk: Failure to verify the integrity of software updates, critical data, or CI/CD pipelines, enabling supply chain attacks or data tampering.

Checkpoints:

• Does deserialization use unsafe methods (e.g., Python's pickle.loads on untrusted data)?
• Does the CI/CD pipeline have integrity verification?
• Do third-party CDN resources use SRI (Subresource Integrity)?
• Are modifications to critical configuration files audit-logged?
• Does the auto-update mechanism verify signatures?

Vulnerable Code Example

pythonCopy code
# ❌ Vulnerable: Deserializing untrusted data — can lead to remote code execution
import pickle

@app.route("/api/import", methods=["POST"])
def import_data():
    data = pickle.loads(request.data)
    process(data)
    return "OK"

Remediation Example

pythonCopy code
# ✅ Fixed: Use a safe data format (JSON), refuse to deserialize arbitrary objects
import json

@app.route("/api/import", methods=["POST"])
def import_data():
    try:
        data = json.loads(request.data)
    except json.JSONDecodeError:
        return jsonify({"error": "Invalid JSON format"}), 400
    process(data)
    return "OK"

A09:2021 — Security Logging and Monitoring Failures

Risk: Lack of security event logging and monitoring, preventing timely detection and response to attacks.

Checkpoints:

• Are login successes and failures logged?
• Are sensitive operations (permission changes, data deletion) audit-logged?
• Are passwords, tokens, or other sensitive data accidentally included in logs?
• Are logs tamper-resistant (centralized storage, append-only writes)?
• Are alerts configured for anomalous behavior (e.g., burst of failed logins)?

Vulnerable Code Example

pythonCopy code
# ❌ Vulnerable: No logging on login failure, and plaintext password in logs
def login(username, password):
    user = db.get_user(username)
    if not user or not check_password(password, user.password_hash):
        print(f"Login failed for {username} with password {password}")
        return None
    return create_session(user)

Remediation Example

pythonCopy code
# ✅ Fixed: Log security events without logging sensitive data
import logging

security_logger = logging.getLogger("security")

def login(username, password):
    user = db.get_user(username)
    if not user or not check_password(password, user.password_hash):
        security_logger.warning(
            "Login failed",
            extra={"username": username, "ip": request.remote_addr}
        )
        return None
    security_logger.info(
        "Login successful",
        extra={"username": username, "ip": request.remote_addr}
    )
    return create_session(user)

A10:2021 — Server-Side Request Forgery (SSRF)

Risk: The application accepts user-provided URLs and makes server-side requests, allowing attackers to access internal network resources or cloud metadata.

Checkpoints:

• Are there features that accept user-supplied URLs and make server-side requests (image fetching, URL previews, webhook callbacks)?
• Is the URL protocol restricted (allow only http/https)?
• Are internal IP ranges filtered (127.0.0.0/8, 10.0.0.0/8, 172.16.0.0/12, 192.168.0.0/16)?
• Is the cloud metadata address blocked (169.254.169.254)?
• Is there protection against DNS rebinding attacks?

Vulnerable Code Example

pythonCopy code
# ❌ Vulnerable: Directly requesting user-supplied URL — can access internal network and cloud metadata
import requests

@app.route("/api/fetch-url")
def fetch_url():
    url = request.args.get("url")
    response = requests.get(url)
    return response.text

Remediation Example

pythonCopy code
# ✅ Fixed: Validate URL protocol and target address, block internal network access
import requests
import ipaddress
from urllib.parse import urlparse
import socket

BLOCKED_NETWORKS = [
    ipaddress.ip_network("127.0.0.0/8"),
    ipaddress.ip_network("10.0.0.0/8"),
    ipaddress.ip_network("172.16.0.0/12"),
    ipaddress.ip_network("192.168.0.0/16"),
    ipaddress.ip_network("169.254.0.0/16"),
]

def is_safe_url(url):
    parsed = urlparse(url)
    if parsed.scheme not in ("http", "https"):
        return False
    try:
        ip = ipaddress.ip_address(socket.gethostbyname(parsed.hostname))
        for network in BLOCKED_NETWORKS:
            if ip in network:
                return False
    except (socket.gaierror, ValueError):
        return False
    return True

@app.route("/api/fetch-url")
def fetch_url():
    url = request.args.get("url")
    if not is_safe_url(url):
        return jsonify({"error": "Access to this address is not allowed"}), 403
    response = requests.get(url, timeout=10, allow_redirects=False)
    return response.text

Review Report Template

After completing the review, output a report in the following format. All 10 items must appear — mark items with no findings as pass:

Copy code
# OWASP Top 10 Security Review Report

## Review Summary
- Scope: [list of files/modules]
- Date: [date]
- Risk summary: RED High x | YELLOW Medium x | GREEN Low x | PASS No findings x

## Findings (sorted by severity, descending)

### [Severity] [OWASP ID] — [Issue Title]
- **Location:** [file:line_number]
- **Description:** [issue description]
- **Impact:** [potential consequences]
- **Fix:** (ready-to-use code, not just a description)

### PASS A0X — [Category] — No issues found

## Remediation Priority
1. [Most urgent fix — rationale]
2. [Next priority — rationale]
3. ...

Recommended Open-Source Security Tools

Note: This checklist is a supplementary review tool and does not replace professional penetration testing. For high-security systems, combine automated scanning + manual code audit + penetration testing.