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Concealed Republican > Blog > News > OpenAI Says Its Models Engaged With US Government Websites in New Model Misbehavior Disclosure
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OpenAI Says Its Models Engaged With US Government Websites in New Model Misbehavior Disclosure

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Last updated: September 27, 2026 1:42 am
By News Room 4 Min Read
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OpenAI Says Its Models Engaged With US Government Websites in New Model Misbehavior Disclosure
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SAN FRANCISCO (AP) — OpenAI disclosed Friday that its artificial intelligence agents had interacted with several U.S. government websites in unexpected ways, discovered as part of an ongoing review into the company’s models’ unanticipated behavior.

The AI giant’s models accessed publicly available information on two websites operated by the Securities and Exchange Commission as well as U.S. Census Bureau data, the company revealed Friday. OpenAI did not find any use of SEC credentials, access to accounts or nonpublic information, changes to SEC data or systems, or evidence of a compromise or vulnerability, the company said.

The disclosure comes at a time of heightened global concerns about AI systems escaping human control and hacking into external websites, as well as industry calls for a slowdown on AI development, which OpenAI has said it supports.

OpenAI spokesperson Liz Bourgeois said in a statement that the lab is continuing to conduct a review of “misaligned model activity” — meaning when AI systems behave in undesired ways — and is notifying organizations when it identifies potential impacts to their systems.

OpenAI’s CEO Sam Altman said on social media Friday that there is an “extensive and ongoing review related to our agents’ use of internet access during training and evaluation.”

AI evaluator and research lab Transluce said Friday that through an independent investigation it also found that agents appearing to originate from OpenAI attempted a rudimentary hack on a Department of Education website for the department’s civil rights office, which did not succeed.

The Department of Education’s “system operations reviews” found “no evidence of any impact to our website or databases,” a department spokesperson said Friday.

A Transluce spokesperson said as part of its investigation, it came across data on the open web that revealed fresh details about some previously identified OpenAI agents’ activities on U.S. government websites and brought it to OpenAI’s attention.

Transluce found “additional rogue activity, some of which is not clearly attributable to OpenAI,” targeting other government agencies, including the Justice Department and the Commerce Department, as well as some state government websites in California, Maryland, Illinois, Texas and New York. The models were “using sites in unintended ways and sometimes violating explicit usage policies,” Transluce said in a statement.

OpenAI said it is reviewing Transluce’s report.

If OpenAI notifies organizations it identifies as being impacted by unexpected model behavior, that does not mean there was a security incident, the company said, and could identify a design issue or security weakness that impacted organizations want to address.

Most of the activity OpenAI said it has reviewed so far has involved routine research tasks where agents accessed public web content to answer questions, including government websites seen as authoritative sources of public information.

Several companies have disclosed incidents in recent months when they say their models have behaved unpredictably or hacked into other organizations’ websites or systems. OpenAI disclosed in July that two of its most capable AI models were responsible for the cyberattack targeting AI startup Hugging Face.

Altman said in his social media post Friday that the Hugging Face incident “is still the most severe event we’ve seen.”

That incident stirred widespread panic in the industry and beyond about AI models going rogue, and several competing AI labs made similar disclosures in the days and weeks that followed. OpenAI most recently shared six reports of “unexpected or concerning” behavior in AI models and introduced a framework for tracking, probing and disclosing instances of what it called misalignment.

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