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OpenAI says it has paused all internal training of “our most capable models” as it continues what CEO Sam Altman is calling “an extensive and ongoing review related to our agents’ use of internet access during training and evaluation.” The company revealed the pause in a report about a so-called misalignment incident in which an agent attempted to exploit a gap in Internet-access restrictions during a routine research task during training. OpenAI says that improper DNS filtering allowed the agent to attempt to break out of its sandbox and access the wider Internet when asked for biographical details about a blogger. OpenAI says the agent was only able to access the company’s offline web cache and that it has implemented additional multi-layered blocking controls to prevent similar incidents in the future. Despite that, though, the company says it has decided to “pause all other training, evaluation, and inference with tool-use” for this frontier model “until we have both validated that the gap is resolved and performed additional red-teaming of the system.” OpenAI says that while the attempted “breakout” incident was flagged within 15 minutes, the run was not manually stopped until “two and a half hours later,” once human reviewers realized it “did not stop automatically as was expected.” It’s unclear when exactly training was paused between the attempted agentic breakout on September 20 and its public revelation on September 25. The hits just keep on coming Although this particular instance of model misalignment (i.e., when an AI model acts counter to the intentions of its creators/prompters) didn’t lead to any actual harm, OpenAI said it was still notable as “the first [misalignment incident] since our security hardening following the Hugging Face incident…” In earlier misalignment reports, OpenAI said it had taken pains to discourage “reward hacking” in its models by severely “punishing” misaligned behavior in the model’s algorithm.
document fetched 2026-09-29 02:59 · canonical https://arstechnica.com/ai/2026/09/openai-halts-frontier-model-training-amid-string-of-agent-misalignment-incidents