Claude Code Security Best Practices Cheat Sheet
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Key Takeaways
- Claude Code has real access — treat it like a developerIt runs code in your shell, reads your files, and uses your credentials. The same guardrails you'd apply to a human developer apply here.
- AI coding assistants introduce five new risk surfacesPrompt and data egress, generated code quality, dependency risk, hallucinations, and agentic tool execution all need dedicated controls.
- Scanners aren't optional — Claude Code isn't a security toolSAST, SCA, IaC scanning, and secrets detection catch what general-purpose AI models miss, including hallucinated packages and insecure code patterns.
Claude Code and other AI coding assistants are changing how fast code ships — but they're also changing what security teams need to watch for.
This practical cheat sheet breaks down the real risk surfaces AI-assisted development introduces, and gives cloud security, AppSec, and platform engineers tactical steps to close the gaps.
Inside, you'll learn how to:
Control what data goes into prompts and what actually gets sent to Anthropic
Prompt for security explicitly to improve the safety of generated code
Defend against slopsquatting and hallucinated-package supply chain attacks
Scope Claude Code's blast radius with least-privilege access and secrets management
Evaluate MCP server trust before connecting new tools
Build deterministic security checks into CI/CD for AI-generated commits
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