Your Logs Leak More Than the Aggregator's: Scrubbing Prompts and Responses From Client-Side Traces on One Key

When you call multiple LLMs through a single API key, the aggregator handles its own security. But your client-side logs—stdout, debuggers, error payloads, and CI logs—often capture raw prompts and responses, creating unintended data exposure. This guide shows how to find and scrub those leaks before they become a liability.

Where Prompts Leak in Client-Side Traces

Developers typically encounter prompt leakage in four places:

• Application logs (stdout/stderr): Debug-level logging often prints full request bodies, including prompts and model responses. In production, these logs may be shipped to centralized systems.
• Request/response debuggers: Tools like HTTP proxies, middleware loggers, or framework debug toolbars capture and display raw API calls.
• Error payloads: Exceptions and stack traces sometimes include serialized request data, which can end up in error trackers or alerting systems.
• CI/CD logs: Test runs that call LLM APIs may log prompts and responses, especially when tests fail or when verbose logging is enabled.

Why Redaction Matters

• Compliance: Regulations like GDPR and CCPA treat prompts as potentially personal data. Unredacted logs can violate data minimization principles.
• Security: Prompts may contain API keys, credentials, or proprietary business logic. Leaked logs become an attack vector.
• Trust: Users expect their inputs to be handled carefully. Logging them indiscriminately erodes trust and may breach terms of service.

Redaction Techniques

1. Avoid Logging Sensitive Fields Entirely

The simplest fix is to never log full request or response bodies. Configure your logging framework to exclude fields like messages, prompt, content, and choices. For example, in Python's logging, use a custom formatter that omits these keys.

2. Use Structured Logging with Field-Level Redaction

Structured logs (JSON) make it easier to apply redaction rules. Implement a middleware that intercepts log records and masks or removes sensitive fields before they are written. Libraries like structlog or pino support processors that can transform events.

3. Sanitize Error Payloads

When catching exceptions, avoid including the full request body in error messages or stack traces. Create sanitized error objects that only include non-sensitive metadata (e.g., status code, error type). If you use error tracking services, configure them to scrub specific fields.

4. Disable Verbose Debugging in Production

Ensure that debug-level logging and request debuggers are disabled in production environments. Use environment variables to control log levels and never enable full request logging unless explicitly needed for a short, controlled debugging session.

5. Redact in CI Pipelines

CI logs are often publicly accessible or retained for long periods. When running tests that call LLM APIs, use environment variables for prompts or mock responses. If real calls are necessary, ensure test code does not log request/response bodies by default. Configure your CI system to mask secrets, but remember that prompts themselves may be sensitive—avoid printing them.

6. Implement a Logging Policy and Retention Limits

Define what can be logged and for how long. Use log rotation and retention policies to automatically delete old logs. Regularly audit your logging configuration to ensure it aligns with your data handling policies.

Practical Implementation

Middleware Example (Conceptual)

• Intercept outgoing API requests and incoming responses.
• Before logging, apply a redaction function that replaces sensitive fields with placeholders like [REDACTED].
• Log only metadata: timestamp, model name, token counts, latency, and status.

Error Handling Best Practices

• Catch exceptions at the API call boundary.
• Log only the error type and a sanitized message.
• Avoid serializing the original request object into the error.

CI Configuration Tips

• Use environment variables to pass prompts, and never echo them.
• Mock LLM responses in tests where possible.
• Review CI provider documentation for secret masking, but do not rely on it for prompt redaction.

Conclusion

Client-side logs are a common but overlooked source of prompt leakage. By applying consistent redaction, disabling verbose logging in production, and sanitizing error and CI output, you can keep sensitive data out of logs while still maintaining observability. Remember: the aggregator secures its side, but your logs are your responsibility.