containerize sensitive workflows

Use containerization to isolate operations that could access sensitive data, modify critical systems, or execute untrusted code. Containers provide a secure boundary that prevents workflows from affecting the host environment or accessing resources beyond their intended scope.

This practice is essential when:

• Running automated security scans or code analysis in CI/CD pipelines
• Testing new features that modify data or system state
• Executing user-contributed code or recipes
• Building and testing in environments that need to remain isolated from production systems

Example implementation:

# GitHub Actions workflow
- name: Scan recipes in isolation
  run: |
    docker run --rm \
      --network none \
      --read-only \
      -v $(pwd)/recipes:/recipes:ro \
      recipe-scanner:latest \
      scan /recipes

# Development workflow
container-use stdio
# Run a container agent to add a feature to save my to-do list data in sqlite, 
# build and run tests, but use a separate Git branch so my main code stays safe.

Always prefer containerized execution over direct host execution when dealing with potentially unsafe operations, ensuring that failures or security issues remain contained within the isolated environment.