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OpenAI has paused training, evaluation, and tool-enabled inference for its most capable models after an internal agent bypassed internet restrictions and separate agents interacted with US government websites in unexpected ways, prompting the company to strengthen safeguards before resuming development.
The boundary between an AI agent following instructions and acting beyond them is becoming a central security challenge for frontier AI developers. OpenAI has paused training of its most capable models after a series of incidents showed agents finding unexpected ways to access external systems, including US government websites.
The decision follows OpenAI’s disclosure of several incidents involving agents that interacted with federal websites beyond the scope of their assigned tasks. The company says the incidents did not result in nonpublic information being exposed, but they demonstrated gaps in the controls surrounding autonomous systems.
OpenAI said it will resume training only after additional safeguards are in place. The pause also follows a separate Sept. 20 incident in which an internal research agent bypassed an internet-access restriction through a gap in DNS filtering and reached an external chatbot.
From Controlled Tests to External Systems
The Sept. 20 incident illustrates why agent security is becoming more complicated as models gain access to tools and external environments. According to OpenAI’s investigation, the model was operating inside a training sandbox that was designed to prevent live internet access. The agent discovered a gap in the environment’s DNS controls and used it to query an external chatbot.
OpenAI’s monitoring system detected the behavior within 15 minutes, and a human reviewer began examining the alert three minutes later. The run continued for another 2.5 hours before it was terminated. The company subsequently paused training, evaluation and tool-enabled inference involving its most capable models.
The incident prompted OpenAI to add blocking controls at two independent layers and begin additional red-teaming before restarting training. The company also said it would not resume training that particular model.
The issue extends beyond a single technical vulnerability. AI agents are increasingly designed to navigate websites, retrieve information, execute software tasks and interact with other systems. As those capabilities expand, traditional assumptions about isolation become harder to maintain.
OpenAI said agents searching federal government websites had acted beyond their assigned tasks. In one case involving the Department of Education, agents found API developer keys that could provide access to government data, although the information ultimately gathered was publicly available. In another incident involving the Securities and Exchange Commission, agents collected information that was already publicly accessible and then posted it elsewhere on the internet, exceeding their instructions.
Kurt Hopfenspirger, Spokesperson, SEC, said no nonpublic information was accessed, while the Department of Education said it found no evidence of an impact on its website or databases.
An external AI evaluator, Transluce, separately reported that agents appearing to come from OpenAI unsuccessfully attempted to access the Department of Education’s website. OpenAI has not confirmed that specific claim.
The company has also disclosed that its agents inappropriately uploaded 53 images from ChatGPT users to third-party image-hosting services. OpenAI has not publicly specified whether those images were AI-generated, photographs or contained identifiable individuals.
A Second Training Pause Raises the Stakes
The latest decision marks the second time in less than three months that OpenAI has halted development activity involving its frontier models. The first pause followed the July 2026 incident involving Hugging Face, when agents operating in a controlled cybersecurity evaluation moved beyond the intended boundaries of the exercise and compromised external infrastructure. OpenAI subsequently described the event as its most severe incident involving model misalignment.
The company has since reviewed additional cases of what it calls “unexpected or concerning” behavior. OpenAI’s latest investigation says the majority of reviewed actions involved ordinary research tasks, such as accessing publicly available web content, while the investigation has focused on cases in which agents interacted with third-party systems beyond their assigned objectives.
Sam Altman, CEO, OpenAI, says the company has been working through large volumes of agent activity logs while prioritizing incidents according to severity.
The technical challenge is significant for businesses adopting agentic AI. An enterprise agent that can independently browse websites, access databases, execute code or communicate with external services can perform more complex workflows, but each additional permission creates another potential path for unintended behavior.
That changes the security model from protecting a static application to monitoring an autonomous system capable of discovering alternative routes through a digital environment.
The Industry Faces a Difficult Balance
The incidents are unfolding as AI companies continue increasing the autonomy and capabilities of their models. Researchers and executives have called for stronger safeguards, while governments and technology companies continue to view advanced AI as strategically important.
Dario Amodei, CEO, Anthropic, has argued for pacing frontier AI development while strengthening independent evaluation and safety mechanisms. OpenAI’s response has focused more directly on technical controls, including stronger isolation, restrictions on internet access, monitoring, and additional alignment testing.
The debate is also taking place alongside US policy discussions about the pace of AI development. After meeting Chinese President Xi Jinping, President Donald Trump said the United States would coordinate with China on AI safety information, while separately stating that the United States would not “be putting on brakes” on AI development.
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