LLM Data Leakage: Logging, Redaction, and Secrets Hygiene

LLM systems often collect telemetry for observability. The problem: prompt and completion logs can accidentally store secrets, credentials, or sensitive business data. Once it hits a log or a trace, it’s very difficult to control downstream exposure.

We’ve seen incidents where secrets were leaked into monitoring dashboards, customer support tools, or long-term storage simply because logs were never scrubbed.

Practical steps

• Redact secrets at ingestion using deterministic patterns and contextual scanning.
• Separate security telemetry from developer analytics to reduce exposure.
• Expire and rotate embedding stores that include user-generated text.
• Define retention policies for prompts and completions, and enforce them.

Security and observability can coexist, but only with strict data boundaries and enforcement. Treat LLM logs like sensitive production data — because they usually are.