/sast-configuration

name: sast-configuration
description: Configure Static Application Security Testing (SAST) tools for automated vulnerability detection in application code. Use when setting up security scanning, implementing DevSecOps practices, or automating code vulnerability detection.

SAST Configuration

Static Application Security Testing (SAST) tool setup, configuration, and custom rule creation for comprehensive security scanning across multiple programming languages.

Overview

This skill provides comprehensive guidance for setting up and configuring SAST tools including Semgrep, SonarQube, and CodeQL. Use this skill when you need to:

• Set up SAST scanning in CI/CD pipelines
• Create custom security rules for your codebase
• Configure quality gates and compliance policies
• Optimize scan performance and reduce false positives
• Integrate multiple SAST tools for defense-in-depth

Core Capabilities

1. Semgrep Configuration

• Custom rule creation with pattern matching
• Language-specific security rules (Python, JavaScript, Go, Java, etc.)
• CI/CD integration (GitHub Actions, GitLab CI, Jenkins)
• False positive tuning and rule optimization
• Organizational policy enforcement

2. SonarQube Setup

• Quality gate configuration
• Security hotspot analysis
• Code coverage and technical debt tracking
• Custom quality profiles for languages
• Enterprise integration with LDAP/SAML

3. CodeQL Analysis

• GitHub Advanced Security integration
• Custom query development
• Vulnerability variant analysis
• Security research workflows
• SARIF result processing

Quick Start

Initial Assessment

1. Identify primary programming languages in your codebase 2. Determine compliance requirements (PCI-DSS, SOC 2, etc.) 3. Choose SAST tool based on language support and integration needs 4. Review baseline scan to understand current security posture

Basic Setup

# Semgrep quick start
pip install semgrep
semgrep --config=auto --error

# SonarQube with Docker
docker run -d --name sonarqube -p 9000:9000 sonarqube:10.8-community

# CodeQL CLI setup
gh extension install github/gh-codeql
codeql database create mydb --language=python

Integration Patterns

CI/CD Pipeline Integration

# GitHub Actions example
- name: Run Semgrep
  uses: returntocorp/semgrep-action@v1
  with:
    config: >-
      p/security-audit
      p/owasp-top-ten

Pre-commit Hook

# .pre-commit-config.yaml
- repo: https://github.com/returntocorp/semgrep
  rev: v1.45.0
  hooks:
    - id: semgrep
      args: ['--config=auto', '--error']

Best Practices

1. **Start with Baseline**

• Run initial scan to establish security baseline
• Prioritize critical and high severity findings
• Create remediation roadmap

2. **Incremental Adoption**

• Begin with security-focused rules
• Gradually add code quality rules
• Implement blocking only for critical issues

3. **False Positive Management**

• Document legitimate suppressions
• Create allow lists for known safe patterns
• Regularly review suppressed findings

4. **Performance Optimization**

• Exclude test files and generated code
• Use incremental scanning for large codebases
• Cache scan results in CI/CD

5. **Team Enablement**

• Provide security training for developers
• Create internal documentation for common patterns
• Establish security champions program

Common Use Cases

New Project Setup

# Semgrep: install, then run an auto-config scan that exits non-zero on findings
pip install semgrep
semgrep --config=auto --error

# SonarQube: start a community server for local evaluation, then analyze with sonar-scanner.
# SONAR_ES_BOOTSTRAP_CHECKS_DISABLE skips the Elasticsearch host checks for a local try-out;
# a real deployment needs vm.max_map_count>=524288 and fs.file-max>=131072 on the host instead.
docker run -d --name sonarqube -e SONAR_ES_BOOTSTRAP_CHECKS_DISABLE=true -p 9000:9000 sonarqube:10.8-community

Custom Rule Development

rules:
  - id: hardcoded-jwt-secret
    pattern: jwt.encode($DATA, "...", ...)
    message: JWT secret should not be hardcoded
    severity: ERROR

Compliance Scanning

# PCI-DSS focused scan
semgrep --config p/pci-dss --json -o pci-scan-results.json

Troubleshooting

High False Positive Rate

• Review and tune rule sensitivity
• Add path filters to exclude test files
• Use nostmt metadata for noisy patterns
• Create organization-specific rule exceptions

Performance Issues

• Enable incremental scanning
• Parallelize scans across modules
• Optimize rule patterns for efficiency
• Cache dependencies and scan results

Integration Failures

• Verify API tokens and credentials
• Check network connectivity and proxy settings
• Review SARIF output format compatibility
• Validate CI/CD runner permissions

Related Skills

• [STRIDE Analysis Patterns](../stride-analysis-patterns/SKILL.md)
• [Threat Mitigation Mapping](../threat-mitigation-mapping/SKILL.md)

Tool Comparison

| Tool | Best For | Language Support | Cost | Integration | | --------- | ------------------------ | ---------------- | --------------- | ------------- | | Semgrep | Custom rules, fast scans | 30+ languages | Free/Enterprise | Excellent | | SonarQube | Code quality + security | 25+ languages | Free/Commercial | Good | | CodeQL | Deep analysis, research | 10+ languages | Free (OSS) | GitHub native |

Next Steps

1. Complete initial SAST tool setup 2. Run baseline security scan 3. Create custom rules for organization-specific patterns 4. Integrate into CI/CD pipeline 5. Establish security gate policies 6. Train development team on findings and remediation