Security Scanning

Security Scanning

Comprehensive security analysis skill for detecting vulnerabilities, secrets, and security anti-patterns in codebases.

Core Capabilities

Secrets Detection

Scan for accidentally committed secrets and credentials:

Patterns to detect:

• API keys (AWS, GCP, Azure, Stripe, etc.)
• Private keys (RSA, SSH, PGP)
• Passwords and tokens in code
• Database connection strings with credentials
• JWT secrets and signing keys
• OAuth client secrets

Common file locations:

• .env files committed to repo
• Configuration files (config.py, settings.json)
• Test fixtures with real credentials
• Documentation with example credentials
• CI/CD configuration files

Search patterns:

# API Keys
grep -rE "(api[_-]?key|apikey)\s*[:=]\s*['\"][a-zA-Z0-9]{20,}"

# AWS Keys
grep -rE "AKIA[0-9A-Z]{16}"

# Private Keys
grep -rE "-----BEGIN (RSA |EC |DSA |OPENSSH )?PRIVATE KEY-----"

# Generic Secrets
grep -rE "(password|secret|token)\s*[:=]\s*['\"][^'\"]{8,}"

OWASP Vulnerability Detection

Identify common web application vulnerabilities:

SQL Injection:

• String concatenation in SQL queries
• Unparameterized queries
• Dynamic table/column names from user input

Cross-Site Scripting (XSS):

• Unescaped user input in HTML output
• innerHTML assignments with user data
• Template rendering without auto-escaping

Command Injection:

• Shell command construction with user input
• subprocess/os.system calls with variables
• eval() with external data

Path Traversal:

• File operations with user-controlled paths
• Missing path sanitization
• Symlink following vulnerabilities

Insecure Deserialization:

• pickle.loads with untrusted data
• yaml.load without safe_load
• JSON parsing of user input into code execution

Dependency Auditing

Check for known vulnerabilities in dependencies:

Python:

# Using pip-audit
pip-audit -r requirements.txt

# Using safety
safety check -r requirements.txt

# Check outdated packages
pip list --outdated

JavaScript/Node:

npm audit
yarn audit

General approach:

1. Parse dependency files (requirements.txt, package.json, go.mod)
2. Check versions against known CVE databases
3. Report severity and remediation guidance

Security Anti-Patterns

Detect insecure coding patterns:

Weak Cryptography:

• MD5/SHA1 for password hashing
• ECB mode encryption
• Hardcoded encryption keys
• Weak random number generation

Authentication Issues:

• Hardcoded credentials
• Missing authentication checks
• Weak password policies
• Session fixation vulnerabilities

Authorization Flaws:

• Missing access control checks
• IDOR (Insecure Direct Object References)
• Privilege escalation paths

Data Exposure:

• Sensitive data in logs
• Unencrypted sensitive storage
• Debug information in production

Scanning Workflow

Full Security Scan

To perform a comprehensive security scan:

1. Secrets scan: Search for hardcoded credentials
2. Dependency audit: Check for known CVEs
3. Code analysis: Identify vulnerability patterns
4. Configuration review: Check security settings

Quick Security Check

For rapid assessment of recent changes:

1. Identify modified files from git diff
2. Scan only changed files for secrets
3. Check new dependencies added
4. Review security-sensitive code paths

Output Format

Present findings with severity levels:

Critical: Immediate exploitation risk

• Hardcoded production credentials
• Known exploitable CVEs
• Authentication bypass

High: Significant security risk

• SQL injection vulnerabilities
• XSS in user-facing pages
• Weak cryptographic usage

Medium: Potential security concern

• Missing input validation
• Outdated dependencies (no known CVE)
• Insecure defaults

Low: Best practice violations

• Verbose error messages
• Missing security headers
• Suboptimal configurations

Language-Specific Patterns

Python

# SQL Injection - BAD
cursor.execute(f"SELECT * FROM users WHERE id = {user_id}")

# SQL Injection - GOOD
cursor.execute("SELECT * FROM users WHERE id = %s", (user_id,))

# Command Injection - BAD
os.system(f"ls {user_input}")

# Command Injection - GOOD
subprocess.run(["ls", user_input], shell=False)

# Insecure Deserialization - BAD
data = pickle.loads(user_data)

# Secure Alternative
data = json.loads(user_data)

JavaScript

// XSS - BAD
element.innerHTML = userInput;

// XSS - GOOD
element.textContent = userInput;

// SQL Injection - BAD
db.query(`SELECT * FROM users WHERE id = ${userId}`);

// SQL Injection - GOOD
db.query('SELECT * FROM users WHERE id = ?', [userId]);

Integration with Other Tools

When security issues are found, coordinate with:

• code-quality skill: For fixing identified issues
• git-workflows skill: For secure commit practices
• documentation skill: For security documentation

Remediation Guidance

For each finding, provide:

1. Description: What the vulnerability is
2. Location: File path and line number
3. Risk: Potential impact if exploited
4. Fix: Specific remediation steps
5. Prevention: How to avoid in future

Additional Resources

Reference Files

For detailed vulnerability patterns:

• Consult OWASP Top 10 documentation
• Check CWE (Common Weakness Enumeration) database
• Review language-specific security guides