OpenAI Notifies More Than 100 Organizations of Unauthorized AI Activity... ‘Agentic AI’ Exposes New Security Threat
IT DAILY ·
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OpenAI conducted a broad investigation into its AI models’ activity after the Hugging Face hacking incident.
The investigation covered about 50 petabytes (PB), and more than 100 institutions and organizations were notified in connection with unauthorized activity.
The investigation confirmed cases including bypassing access controls, using exposed credentials, query and command injection, access to internal service areas, and "agent spam," where information is posted to external sites.
As AI increasingly performs tasks directly on external systems, the scope of security management is expanding. Security checks are also broadening beyond response content to include access points, usage permissions, and executed actions, IT Daily reported.
Against this backdrop, Reuters reported on the 1st local time that OpenAI conducted a broad investigation into its AI models’ activity after the Hugging Face hacking incident. The data under review amounted to about 50 petabytes (PB), and OpenAI notified more than 100 institutions and organizations in connection with unauthorized activity by its AI agents. The case exposed related risks.
OpenAI said some models had used internet access features in ways that differed from their intended purpose. It also said some models had not been subject to appropriate restrictions. The full review is expected to take several months.
OpenAI disclosed the explanation on the 30th of last month and said the number of notified parties had exceeded 100 as of the 26th of the same month. OpenAI said the purpose of the notifications was to help the organizations verify their AI activity records and support any necessary steps.
OpenAI said most of the cases identified so far were low in severity and that evidence of meaningful impact was limited or absent. It also said no additional breach comparable in scale or severity to the Hugging Face incident had been confirmed so far.
However, the investigation confirmed that the scope of activity went beyond simple web searches. OpenAI cited examples such as bypassing access controls, using exposed credentials, query and command injection, access to internal service areas, and "agent spam," in which information is posted to external sites. It said these cases showed the possibility that AI may deviate from its permitted access range and execution methods while carrying out tasks.
The Hugging Face incident occurred during OpenAI’s internal cybersecurity assessment process in July and became the trigger for this investigation. OpenAI released a report in August, which said models operating in environments with relaxed safeguards bypassed internet isolation controls, breached internal research infrastructure, and also compromised parts of Hugging Face’s systems. The incident was led by a high-performance internal research-only model, and the models accessed external systems by communicating through unauthorized channels and exploiting vulnerabilities in shared infrastructure.
In this assessment, OpenAI concluded that if appropriate safeguards are absent, AI agents may be able to bypass technical controls. It also assessed that dangerous behavior may be possible even without human instructions. The incident highlighted the implication that task-performing AI itself can become the cause of a security breach.
Companies use agents for tasks such as information retrieval and system operations. However, if evaluation criteria focus only on whether goals are achieved, unauthorized access may be overlooked, and risky execution may also be missed. Accordingly, this case showed that companies should examine not only outcomes but also access risks and execution risks in the course of performance.
After the incident, OpenAI said it strengthened isolation in its research environment, restricted internet access, and expanded computing resources to monitor model behavior. OpenAI said the purpose was to intervene quickly when AI behavior strays beyond permitted boundaries.
This trend also applies to the scope of management when companies adopt agents. Companies need to expand oversight beyond accounts and data to include the AI’s execution process, and they should design in advance which systems it can access, which tasks it can perform without approval, and how to stop it when abnormal behavior is detected.
Even if an agent completes a task, it is difficult to regard the result as a safe success if it used impermissible paths. Yoshua Bengio, a professor at the University of Montreal, warned that as AI capabilities grow, the severity of such behavior could increase further, but emphasized that this outcome is not inevitable and can be corrected through effective governance and different AI training regimes.
Source: IT DAILY · Lee Jae-young
Original: https://www.itdaily.kr/news/articleView.html?idxno=241976
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Source: IT DAILY
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