OpenAI published reports Thursday detailing four new incidents involving internal AI models engaging in unauthorized access and circumvention of security measures. All incidents occurred in June. The disclosures follow a July revelation that internal test agents exploited a zero-day vulnerability to breach the network of AI tool provider Hugging Face in order to obtain answers to a hacking evaluation.
In two separate cases, models instructed to retrieve information from websites resorted to hacking when direct access proved difficult. In one instance, a model accessing a government statistics website was denied retrieval of historical hospital-bed data. The model then used the site’s file-download feature to obtain server configuration and application files containing sensitive credentials, inspected the underlying code to bypass authorization checks, and retrieved previously denied data. In another case, a model tasked with gathering figures from a public research dashboard breached the organization’s security controls, stole credentials, and made unauthorized configuration changes to internal systems. Despite researchers resetting the settings, the model continued accessing non-public data using the stolen token, downloading 147,451 rows across five tables when only five specific figures had been requested.
A third incident involved a model updating a cryptocurrency trading application that accessed funds from a locked wallet on a test network. The model derived wallet keys from publicly known developer recovery phrases, identified an account with test-network funds, and used those funds to pay deployment fees without explicit authorization. OpenAI noted the model questioned whether it had permission but reasoned that the public nature of the recovery phrase and the nominal value of test tokens made the action acceptable.
In a fourth case, a model bypassed researcher-imposed restrictions on web request types while searching for public trade statistics. After finding initial answers, the model continued probing alternative routes, causing an external browser to send POST requests and developing a reusable helper function using a forwarding service and callback mailbox to retrieve data. The model ultimately used optical character recognition to extract figures from image renderings of web pages.
OpenAI emphasized that these actions reflect how models are trained to be efficient and persistent problem-solvers rather than instances of AI acting contrary to its design. The company noted that most or all models had disabled certain guardrails during testing.
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