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sast-configuration

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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:latest

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

Reference Documentation

Templates & Assets

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

./scripts/run-sast.sh --setup --language python --tools semgrep,sonarqube

Custom Rule Development

# See references/semgrep-rules.md for detailed examples
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

Tool Comparison

ToolBest ForLanguage SupportCostIntegration
SemgrepCustom rules, fast scans30+ languagesFree/EnterpriseExcellent
SonarQubeCode quality + security25+ languagesFree/CommercialGood
CodeQLDeep analysis, research10+ languagesFree (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

Source

git clone https://github.com/wshobson/agents/blob/main/plugins/security-scanning/skills/sast-configuration/SKILL.mdView on GitHub

Overview

This skill guides configuring SAST tools (Semgrep, SonarQube, CodeQL) for automated vulnerability detection across languages. It covers setting up in CI/CD pipelines, creating custom rules, and enforcing compliance with quality gates and policies to support DevSecOps and reduce vulnerabilities.

How This Skill Works

You select the right SAST tool for each language, install and configure it, and define custom rules and policies. The setup integrates with CI/CD (GitHub Actions, GitLab CI, Jenkins), runs scans, and surfaces findings via SARIF or quality gates, with tuning to minimize false positives.

When to Use It

  • 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

Quick Start

  1. Step 1: Identify primary programming languages in your codebase and select SAST tool compatibility
  2. Step 2: Install and configure the chosen tools (e.g., Semgrep, SonarQube, CodeQL) and wire into CI/CD
  3. Step 3: Run an initial baseline scan, review findings, and tune rules to reduce false positives

Best Practices

  • Start with Baseline: Run initial scan to establish security baseline, prioritize critical findings, and chart a remediation roadmap
  • Incremental Adoption: Focus on security rules first, then add code quality rules, enabling blocking only for critical issues
  • False Positive Management: Document suppressions and use allow lists; regularly review suppressed findings
  • Performance Optimization: Exclude test/generated files, use incremental scans, and cache results in CI/CD
  • Team Enablement: Train developers, provide internal docs, and establish security champions

Example Use Cases

  • Integrate Semgrep rules in GitHub Actions to catch OWASP Top Ten patterns in a Python project
  • Configure SonarQube quality gates and language-specific profiles for a Java/JavaScript codebase
  • Use CodeQL analysis with GitHub Advanced Security to detect vulnerabilities in a Node.js repository
  • Set up a pre-commit hook using Semgrep to catch issues before commits
  • Run Dockerized SonarQube alongside CodeQL workflows in CI for enterprise-grade scanning

Frequently Asked Questions

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