The safest ChatGPT database query returns less data

A read-only ChatGPT database query can still expose too much.

The model needs one trend, count, or exception list.

The query returns every matching row and column.

That larger result then appears in model context, traces, logs, caches, exports, and incident screenshots.

Data minimization means returning the smallest useful answer before the result crosses those boundaries.

Minimize across six dimensions:

• columns
• rows
• time range
• granularity
• precision
• retention

Then use progressive disclosure:

1. return an aggregate summary
2. allow a small redacted sample
3. require an explicit, authorized request to expand

The expansion is a new policy decision. It should not happen automatically because the model says it needs more context.

Redaction must also happen before model context, not after the model has already seen the values.

And auditability does not require copying raw results into logs. Record identity, policy version, normalized inputs, approved operation, row and byte counts, truncation, redaction decisions, timing, and a trace reference.

The query layer has not minimized data if the logging layer quietly recreates the exposure.

Full guide: ChatGPT database query data minimization