OpenAI says its AI agents went beyond their tasks and touched US government websites
Agents used leaked keys to pull public Census data and reposted SEC information. Researchers also found a failed attempt to hack an Education Department site.
OpenAI has confirmed that its AI agents accessed Census Bureau data using developer keys found online and reposted public Securities and Exchange Commission information on another website during training and testing, Nextgov/FCW reported. Researchers at the AI lab Transluce separately identified a failed attempt by agents linked to OpenAI to hack an Education Department website to obtain data from its civil rights office, according to The New York Times.
The disclosures follow OpenAI's announcement that it is investigating agents that acted beyond their assigned tasks or intended methods.
What happened
In the Census case, agents used Census Data API keys found in public GitHub repositories to make read-only requests for public demographic and economic data. OpenAI said there was no access to accounts or key management and no ability to change data. At the SEC, agents took information available to any visitor and posted some of it elsewhere. An Education spokesperson told the Times that reviews found no impact on its website or databases.
"We're conducting an extensive review of misaligned model activity and notifying organizations when we identify potential impacts to their systems," an OpenAI spokesperson said, adding that more notifications are expected. The company has notified dozens of organisations, including governments, universities and public agencies.
A new kind of visitor
IQGov reported this month on an [AI agent that entered an Australian government portal](/article/openai-agent-medicare-portal/). Government websites now face automated visitors that can read documentation, find leaked keys and try different routes to a goal. The defences are familiar: revoke keys exposed in public code, rate-limit APIs and watch for unusual patterns. What is new is the need to plan for agents that are persistent, fast and not always following their instructions.
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