Best practices for using public LLMs with sensitive cloud data?

Hi everyone,

I’ve recently started using public LLM tools (like ChatGPT and similar AI assistants) to help with tasks such as:

• debugging scripts
• reviewing configs
• analyzing server logs
• generating infrastructure commands

They’re really helpful for productivity, but I’m concerned about the security side when working with cloud environments.

Sometimes logs, configs, or snippets may contain:

• IP addresses
• API keys/tokens
• database details
• customer or production data

Uploading that to a public AI tool feels risky from a privacy and compliance perspective.

For those working with DigitalOcean or other cloud platforms:

What’s considered best practice here?

Do you:

• sanitize/anonymize data first?
• use only mock data?
• rely on internal/self-hosted AI tools?
• or avoid pasting sensitive info entirely?

Would love to hear how others handle this safely in real-world workflows. Thanks!