SAST Scanning

Identify security vulnerabilities in source code through static analysis.

When to Use This Skill

Use this skill when:

• Implementing secure SDLC practices
• Adding security gates to CI/CD
• Automating code security reviews
• Finding vulnerabilities before deployment
• Meeting compliance requirements

Prerequisites

• Source code access
• CI/CD pipeline
• SAST tool installation

Tool Comparison

Semgrep

Installation

# Install via pip
pip install semgrep

# Or via Homebrew
brew install semgrep

Basic Usage

# Run with default rules
semgrep --config auto .

# Run specific rulesets
semgrep --config p/security-audit .
semgrep --config p/owasp-top-ten .
semgrep --config p/ci .

# Scan specific languages
semgrep --config p/python .
semgrep --config p/javascript .

# Output formats
semgrep --config auto --json -o results.json .
semgrep --config auto --sarif -o results.sarif .

Custom Rules

# .semgrep/custom-rules.yaml
rules:
  - id: hardcoded-password
    patterns:
      - pattern-either:
          - pattern: password = "..."
          - pattern: PASSWORD = "..."
          - pattern: passwd = "..."
    message: Hardcoded password detected
    severity: ERROR
    languages: [python, javascript, java]
    metadata:
      cwe: "CWE-798"
      owasp: "A3:2017"

  - id: sql-injection
    patterns:
      - pattern: |
          $QUERY = "..." + $USER_INPUT + "..."
          $DB.execute($QUERY)
    message: Potential SQL injection
    severity: ERROR
    languages: [python]
    metadata:
      cwe: "CWE-89"

  - id: insecure-random
    pattern: random.random()
    message: Use secrets module for security-sensitive randomness
    severity: WARNING
    languages: [python]
    fix: secrets.token_hex()

CI Configuration

# .github/workflows/semgrep.yml
name: Semgrep

on:
  push:
    branches: [main]
  pull_request:

jobs:
  semgrep:
    runs-on: ubuntu-latest
    container:
      image: returntocorp/semgrep
    steps:
      - uses: actions/checkout@v4

      - name: Run Semgrep
        run: semgrep ci
        env:
          SEMGREP_APP_TOKEN: ${{ secrets.SEMGREP_APP_TOKEN }}

CodeQL

Setup

# .github/workflows/codeql.yml
name: CodeQL Analysis

on:
  push:
    branches: [main]
  pull_request:
    branches: [main]
  schedule:
    - cron: '0 0 * * 0'

jobs:
  analyze:
    runs-on: ubuntu-latest
    permissions:
      security-events: write
      actions: read
      contents: read

    strategy:
      matrix:
        language: ['javascript', 'python']

    steps:
      - uses: actions/checkout@v4

      - name: Initialize CodeQL
        uses: github/codeql-action/init@v3
        with:
          languages: ${{ matrix.language }}
          queries: +security-and-quality

      - name: Autobuild
        uses: github/codeql-action/autobuild@v3

      - name: Perform CodeQL Analysis
        uses: github/codeql-action/analyze@v3
        with:
          category: "/language:${{ matrix.language }}"

Custom Queries

// queries/sql-injection.ql
/**
 * @name SQL Injection
 * @description User input in SQL query
 * @kind path-problem
 * @problem.severity error
 * @security-severity 9.0
 * @precision high
 * @id py/sql-injection
 * @tags security
 */

import python
import semmle.python.dataflow.new.DataFlow
import semmle.python.dataflow.new.TaintTracking
import semmle.python.security.dataflow.SqlInjectionQuery

from SqlInjectionConfiguration config, DataFlow::PathNode source, DataFlow::PathNode sink
where config.hasFlowPath(source, sink)
select sink.getNode(), source, sink, "SQL injection from $@.", source.getNode(), "user input"

SonarQube

Docker Setup

# docker-compose.yml
version: '3.8'

services:
  sonarqube:
    image: sonarqube:lts-community
    ports:
      - "9000:9000"
    environment:
      - SONAR_JDBC_URL=jdbc:postgresql://db:5432/sonar
      - SONAR_JDBC_USERNAME=sonar
      - SONAR_JDBC_PASSWORD=sonar
    volumes:
      - sonarqube_data:/opt/sonarqube/data
      - sonarqube_logs:/opt/sonarqube/logs
    depends_on:
      - db

  db:
    image: postgres:15

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