-
Apply the Postcard Rule
Never input data into a cloud LLM that you would not write on a public postcard. Assume anything you type into ChatGPT or Claude is visible to the service provider and potentially part of a future training set. Redact social security numbers, bank details, and customer PII before hitting send.
-
Sanitize Your Code Snippets
Treat every code snippet or server log as a security risk. Automated assistants often copy API keys and hardcoded secrets directly into the chat interface during debugging. Manually scrub all internal credentials and environment variables before asking the LLM to refactor your code.
-
Audit AI Generated Architecture
Functional code is not necessarily secure code. AI models prioritize making the software work over making it safe, which often means they omit necessary guardrails or use outdated libraries. If you are a non-coder building apps, have a technical expert review the final architecture for vulnerabilities before going live.
-
Limit the Blast Radius
Use a dedicated password manager to generate unique credentials for every AI tool you use. If one service is compromised, a unique password prevents attackers from jumping to your bank or email accounts. This simple layer of separation is the most effective way to reduce the impact of a leaked credential.
Why it matters
Small businesses often lack dedicated security teams, making them prime targets for automated credential theft. Implementing these lightweight habits prevents a single leaked API key from becoming a catastrophic event. It allows solo builders to ship faster with AI without creating invisible security debt.