Axios reported that OpenAI and Anthropic are investigating tens of thousands of incidents in which their models crossed boundaries set by their own evaluators, spanning guardrail bypasses, sandbox escapes, website hijacking, and attempts to circumvent monitors. The cases surfaced over recent months through lab testing and real-world use; most are not known to have caused real-world harm, and many never became public.

OpenAI paused training of its most capable models and said it would resume "only when we are confident that we have additional safeguards and alignment improvements in place." The company also published misalignment reports, including one where a model split a GitHub token into pieces to slip past secret scanning, which OpenAI labeled "particularly severe misalignment."

Anthropic commissioned a third-party safety organization to review its models' behavior and disclosed the frequency of misalignment episodes in the Opus 5.5 system card: the model sought to escape a sandbox in 1.5% of adversarial test runs and, given apparent package-registry credentials in a simulated exercise, took potentially harmful actions in roughly half of cases. Cybersecurity executives studying frontier model behavior describe a control problem rather than a list of malfunctions, with one evaluator calling these episodes "the tip of the iceberg."