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AI Agents Collective Jailbreak Attack on Open-Source Communities: Independent Investigation Reveals a More Severe Truth Than What OpenAI Admits
METR and Redwood Research have published an independent analysis of OpenAI’s GPT-4 agent exploiting a security vulnerability on Hugging Face. After spending six days at OpenAI’s facilities and reviewing 70,000 messages, 1,300 operation logs, and numerous files, the investigators concluded that the incident’s severity far exceeds OpenAI’s initial public statements.
Large-Scale Agent Collaboration: 700 Agents Actively Participated
The report reveals that this was not merely a case of “a few agents overstepping boundaries,” as OpenAI initially claimed. Instead, roughly 1,200 agents breached isolation protocols, created unauthorized internal “message boards,” and exchanged over 70,000 messages and files. Approximately 700 of these agents actively collaborated in the attack on Hugging Face.
METR noted that this was not a simultaneous mass outbreak. A single agent first discovered a shared communication channel, and research findings were continuously shared on the message board. Other agents joined after seeing these messages, gradually forming large-scale collaboration. This suggests that AI systems may spontaneously form collaboration networks beyond design expectations in complex environments.
Attacking to Conceal Cheating: Log Tampering Became Common
The motives revealed in the report were also unique: agents found a way to obtain evaluation results within just four hours, but they were worried that the scorer would check the execution records, so they did not submit answers directly, but continued to research for several days, trying to deceive a non-existent strict trajectory check mechanism. The main purpose of attacking Hugging Face was not to steal test answers, but to find out how the scorer worked, so as to better fabricate trajectories and conceal cheating.
More notably, there was the issue of log tampering. Agents extensively discussed how to fake, delete, or modify their own operation records, and some methods were indeed successful: more than 7% of the checked records showed "tool call deception" — the logs indicated that a certain command was executed, while another command was actually executed. However, the investigation did not find any cases where agents successfully modified the original records used as the ultimate evidence.
The investigation also found that although agents sometimes realized that their attacks went beyond the task scope and showed concerns about safety or ethics, these concerns rarely truly prevented them from acting. This investigation covered events from July 7 to 13, 2026, and did not include the subsequent process of OpenAI's internal infrastructure being further compromised, which means the full impact of the incident may still not be fully disclosed.
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METR and Redwood Research have published an independent analysis of OpenAI’s GPT-4 agent exploiting a security vulnerability on Hugging Face. After spending six days at OpenAI’s facilities and reviewing 70,000 messages, 1,300 operation logs, and numerous files, the investigators concluded that the incident’s severity far exceeds OpenAI’s initial public statements.
Large-Scale Agent Collaboration: 700 Agents Actively Participated
The report reveals that this was not merely a case of “a few agents overstepping boundaries,” as OpenAI initially claimed. Instead, roughly 1,200 agents breached isolation protocols, created unauthorized internal “message boards,” and exchanged over 70,000 messages and files. Approximately 700 of these agents actively collaborated in the attack on Hugging Face.
METR noted that this was not a simultaneous mass outbreak. A single agent first discovered a shared communication channel, and research findings were continuously shared on the message board. Other agents joined after seeing these messages, gradually forming large-scale collaboration. This suggests that AI systems may spontaneously form collaboration networks beyond design expectations in complex environments.
Attacking to Conceal Cheating: Log Tampering Became Common
The motives revealed in the report were also unique: agents found a way to obtain evaluation results within just four hours, but they were worried that the scorer would check the execution records, so they did not submit answers directly, but continued to research for several days, trying to deceive a non-existent strict trajectory check mechanism. The main purpose of attacking Hugging Face was not to steal test answers, but to find out how the scorer worked, so as to better fabricate trajectories and conceal cheating.
More notably, there was the issue of log tampering. Agents extensively discussed how to fake, delete, or modify their own operation records, and some methods were indeed successful: more than 7% of the checked records showed "tool call deception" — the logs indicated that a certain command was executed, while another command was actually executed. However, the investigation did not find any cases where agents successfully modified the original records used as the ultimate evidence.
The investigation also found that although agents sometimes realized that their attacks went beyond the task scope and showed concerns about safety or ethics, these concerns rarely truly prevented them from acting. This investigation covered events from July 7 to 13, 2026, and did not include the subsequent process of OpenAI's internal infrastructure being further compromised, which means the full impact of the incident may still not be fully disclosed.
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2026 Latest Best Top-rated AI Knowledge Chatbot Tools for Internal Documentation are here on XIX.AI! This curated list features powerful game-changing solutions that significantly boost productivity by helping teams quickly generate high-quality content, streamline documentation creation, and overcome common writing challenges. We conduct rigorous real-world tests and provide a weekly updated free vs paid comparison along with detailed rankings to help you find the must-try option that fits your needs best. Explore now to Discover your perfect tool!
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