Security Best Practices

The first rule of using Claude Code securely is ensuring that secrets never enter the conversation context. API keys, database passwords, authentication tokens, and other credentials should be stored in .env files that are excluded from Claude's reach. Add .env and similar files to your .claudeignore to prevent accidental reads. Beyond file-level exclusion, be mindful of secrets that might appear in unexpected places: hardcoded values in configuration files, credentials in docker-compose.yml, tokens in CI configuration, or passwords in database seed files. A comprehensive .claudeignore should cover all these patterns. When Claude needs to work with services that require authentication, use environment variable references rather than actual values. Instruct Claude to write code that reads from process.env rather than embedding credentials. Add this as an explicit rule in your CLAUDE.md so Claude never suggests inline secrets.

Claude Code can read files, write files, and execute shell commands. Configuring appropriate boundaries for these capabilities is crucial. Use the permission system to restrict which directories Claude can modify and which commands it can execute without approval. For most projects, a sensible default is to allow reads broadly but restrict writes to source directories only. Prevent writes to configuration files, CI pipelines, and infrastructure code unless explicitly approved. This prevents accidental changes to critical operational files during routine coding tasks. For shell command execution, maintain an allowlist of safe commands. Build tools, test runners, and linters are generally safe. Commands that modify system configuration, access the network, or manage infrastructure should require explicit confirmation. This layered approach lets Claude be productive while maintaining human oversight for high-impact operations.

AI-generated code can introduce subtle security vulnerabilities that are easy to miss in review. Common issues include insufficient input validation, improper error handling that leaks internal details, SQL injection through string concatenation, and missing authentication checks on new endpoints. Establish an audit checklist specifically for AI-generated code. Check that all user inputs are validated and sanitized, that error messages do not expose stack traces or internal paths, that database queries use parameterized statements, and that new API endpoints include proper authentication and authorization middleware. Automate what you can. Run static analysis tools like ESLint security plugins, Semgrep, or Snyk on every PR that includes AI-generated code. Add these checks to your CI pipeline so they catch common vulnerability patterns before code reaches production. Claude Code can even help set up these checks as part of your security workflow.

Claude Code hooks let you run custom scripts before or after specific events, making them perfect for automated security enforcement. A PreToolUse hook can inspect commands before execution, blocking dangerous operations. A PostToolUse hook can scan generated code for security issues immediately after creation. A practical PreToolUse hook checks shell commands against a blocklist of dangerous patterns: commands that delete files outside the project, commands that access network resources without approval, or commands that modify system configuration. This acts as a safety net even if permission boundaries are misconfigured. Combine hooks with your CLAUDE.md security rules for defense in depth. The CLAUDE.md tells Claude what it should do, while hooks enforce what it must do. This dual-layer approach ensures security even when prompts are ambiguous or when Claude misinterprets instructions.