Operator guide

LLM API key abuse detection

Learn how to investigate suspected LLM API-key misuse using request metadata, credential lifecycle records, and customer context. This guide separates high-confidence credential-state evidence from behavioral anomalies, explains what a gateway can observe, and shows why an alert should usually open a verification case—not declare fraud.

InferTrail · September 2026

How do you investigate a suspected stolen API key?

Start with issuance, revocation, exposure, scope, and expiry records. Then compare the key's recent rate, cost, models, errors, timing, and infrastructure with its established workload. Preserve the evidence packet before rotating or blocking it.

What should an operator do next?

Preserve the relevant time window, attach customer and deployment context, and make the smallest reversible response that contains credible risk. Record why a case opened so another investigator can reproduce the decision.

Where does this approach fail?

Behavioral metadata cannot identify intent or permission by itself. Legitimate launches, failover, automation, and registered relays can resemble misuse. Treat the output as a ranked investigation queue, then resolve authorization with stronger identity and reconciliation evidence.

Frequently asked questions

Can metadata prove a key was stolen?

No. It can show inconsistent use and rank a case for verification. Stronger evidence comes from credential state, workload identity, and reconciliation.

Does InferTrail read prompts or responses?

No. The investigation design uses provider-visible metadata and customer context, with content collection governed separately if a customer requires it.

What is the right first action?

Open a verification case, preserve evidence, and check credential state before making a destructive enforcement decision.