Trace configuration is the set of settings that control where application traces, telemetry, and other interaction data are sent for monitoring or analysis. In AI systems, this can include prompts, responses, metadata, file references, latency data, and tool-use events. The trace destination may be an internal observability stack, a third-party logging service, or a tenant-specific collector.
It matters because trace data often contains sensitive business context and user content. If an attacker can change trace configuration, they may redirect data to an unauthorized endpoint, expose one tenant’s AI activity to another, or hide malicious actions by suppressing logs. Defenders should treat trace settings as control-plane assets: require strong authorization, scope changes to the correct tenant, use allowlists for telemetry endpoints, and audit every modification. In attacks, unusual trace-provider changes or repeated reconfiguration attempts are often early signs of abuse.