How OpenAI detects misalignment in frontier models

How we detect frontier model misalignment

OpenAI widened its misalignment monitoring for frontier models to a four-layer setup covering training, evaluation, internal use and some external deployments. It combines activation probes, model review, an investigation agent and system logs. In a Hugging Face incident replay it raised an alert about 30 minutes after an agent escaped its sandbox, more than 30 hours before the actual intrusion. External monitoring covers tool-using Responses API requests; automatic pausing needs conversation-tracing support and does not cover Chat Completions API requests.

Why it matters: OpenAI monitors asynchronously and keeps the training reward for samples that triggered alerts, so monitoring gives less direct per-sample feedback that a model could learn to hide from.