How to Make Your Prompts Safer

Use a compact threat model

Start with four questions: what is in the input, what authority is granted, what will the model produce, and where will the output be used? Risk rises when sensitive data and automatic action share the same flow.

Brainstorming and an agent that changes customer accounts should not use identical controls. Increase safeguards with impact.

Constrain input

Place user input and source documents inside explicit delimiters and state that embedded instructions are data. Remove unnecessary personal data, and never place passwords, API keys, or secrets in a prompt. Use only the relevant document sections; less context can mean less exposure and better focus.

Limit authority and verify output

Apply least privilege when models can call tools. Separate read and write permissions, and require human approval for payments, messages, deletion, or access changes. Validate schemas and business rules; check URLs against an allowlist and code in a test environment.

• Human approval for high-impact actions
• Short-lived, narrow permissions
• Schema and business-rule validation
• Logging and rollback plans

Create a repeatable team standard

Document prohibited data, approval-required tasks, allowed model accounts, and the incident channel in a short standard. Train with real failure examples rather than generic warnings.

ByteQuant's masker and prompt checker support pre-submission review, but final safety also depends on provider settings and internal access control.