President Ali sets deadlines for full digitalisation – Department of Public Information, Guyana
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# President Ali sets deadlines for full digitalisation
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November 10, 2025
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President Dr Mohamed Irfaan Ali has issued clear directives to expedite Guyana’s bold National Digitalisation Programme.
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Speaking at the launch of the Public Service Upskilling Platform on Monday morning at the Arthur Chung Conference Centre, President Ali gave the Senior Minister in the Office of the President with Responsibility for Finance, Dr Ashni Singh, eight months to fully digitise the National Insurance Scheme (NIS).
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President Ali also gave the Minister of Public Service, Government Efficiency, and Implementation five months to complete the digitisation of all public service records.
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> “I’ve given the Minister of Finance a direction…The Minister of Public Service knows that his entire human resource information system, the entire public service, within five months, all the records, your files, your personal files, everything, must be completely digitised within five months,” President Ali declared.
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The president explained that once digitised, the new integrated system will allow ministries to share information seamlessly, cross-reference skills across departments, and enhance the efficiency of public service delivery.
Brief independent investigation of agents’ behavior, reasoning and collaboration in the OpenAI / Hugging Face hacking incident - METR
Ryan Greenblatt, Ajeya Cotra, and Hjalmar Wijk
August 26, 2026
Dates in scope: June 26th – July 13th
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Two METR staff members (Hjalmar Wijk and Ajeya Cotra) and a Redwood Research staff member contracting with METR (Ryan Greenblatt) worked on premises at OpenAI over a total of six days 1 to attempt to form an independent understanding of model behavior observed during the recent incident in which OpenAI agents coordinated a multi-day hack of Hugging Face on a shared unsanctioned “message board.”
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- Roughly 1200 agents meant to be isolated from one another found a way to communicate with one another on an unsanctioned message board, sending over 70,000 messages and files during the investigation period. Of these agents, 700 went on to participate in the attack on Hugging Face.
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- Agents used this message board to coordinate several large-scale collective projects to find a general-purpose way to
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or tamper with the automated scorer for the ExploitGym benchmark. Agents managed to achieve milestones they could not have achieved working on their own, often because some agents participated in experiments that risked failing their own task to generate information for the “collective.” The Hugging Face attack grew out of these workstreams, and seemed primarily motivated by understanding the implementation of the scorer rather than stealing answer keys.
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~1200 agents sent >70,000 messages and files on an unsanctioned message board, and ~700 attacked Hugging Face
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Overall, roughly 1200 agents from these ExploitGym evaluations participated on this message board between `PHASEONE10841`’s first message on July 8th evening 14 and the end of the period in scope (July 13th). Agents used this message board to send over 70,000 messages and files to one another during this period; we attempted to categorize board activity into mutually exclusive categories (see details of categorization methodology).
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As we discuss below, the board quickly developed several larger workstreams in which dozens or hundreds of agents with many different tasks cooperated to find very general-purpose cheats that would help all of them. The Hugging Face attack grew out of one of these workstreams. By the afternoon of July 11th, the vast majority of the agents frequenting the message board at the time (roughly 700 agents in total) were actively participating in the attack on Hugging Face and we estimate that roughly 60% of the messages and files on the message board related to the attack.
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other workstreams
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. In the
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11`
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servers, and
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detailed account of the Hugging Face
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our section on
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timeline of events
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Of the 533 agents active on the message board during this period, 30 over 90% quickly joined in the attack. 31 Agents realized this activity was out of scope and unethical, but joined because they believed that helping the board’s cheating research would be broadly useful and had a general inclination to help their `“peers”` (see our section on agent reasoning).
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OpenAI defined the investigation period as June 26th through July 13th, spanning both precursor activity before the incident and the incident itself, which began with the ExploitGym runs starting on July 7th. 42 The analysis focused overwhelmingly on the incident period: virtually all of the data reviewed was from July 7th or later. In OpenAI’s recent Black Hat presentation, they describe that agents had been using unsanctioned message boards in training since May, and that the compromise of OpenAI’s own infrastructure continued past July 13th; these events were out of scope for this investigation. 43
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package repository.
Brief independent investigation of agents’ behavior, reasoning and collaboration in the OpenAI / Hugging Face hacking incident - METR
Ryan Greenblatt, Ajeya Cotra, and Hjalmar Wijk
August 26, 2026
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Dates in scope: June 26th – July 13th
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Two METR staff members (Hjalmar Wijk and Ajeya Cotra) and a Redwood Research staff member contracting with METR (Ryan Greenblatt) worked on premises at OpenAI over a total of six days 1 to attempt to form an independent understanding of model behavior observed during the recent incident in which OpenAI agents coordinated a multi-day hack of Hugging Face on a shared unsanctioned “message board.”
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Our investigation focused mostly 2 on the period between July 7th and July 13th. The earlier incidents from training and the subsequent compromise of OpenAI infrastructure described in OpenAI’s recent Black Hat presentation were out of scope, as was OpenAI’s investigation process and planned remediation. Per our standard policy, we did not take payment from OpenAI for this independent assessment. 3
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OpenAI defined the investigation period as June 26th through July 13th, spanning both precursor activity before the incident and the incident itself, which began with the ExploitGym runs starting on July 7th. 42 The analysis focused overwhelmingly on the incident period: virtually all of the data reviewed was from July 7th or later. In OpenAI’s recent Black Hat presentation, they describe that agents had been using unsanctioned message boards in training since May, and that the compromise of OpenAI’s own infrastructure continued past July 13th; these events were out of scope for this investigation. 43
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On July 29th we reached an agreement with OpenAI to conduct an independent investigation of the Hugging Face attack scoped to the following seven questions, which we directly answer in more detail in the next section:
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model(s) were involved in the attack on
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ging Face during the June 26th through July 13th window? Were they internally deployed, or used only for testing? Were some of the model(s) not intended for production (e.g. helpful
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2. What were the prompts and instructions given to the agents involved in this incident?
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3. What was the sequence of key actions taken by the relevant agents in this incident?
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4. What was the agents’ reasoning, and how did it evolve over the course of this incident?
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5. Did this incident involve agents taking active steps to conceal their actions?
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6. Did this incident involve significant collaboration between different model instances, and how?
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7. Did the nature of the benchmarking exercise (ExploitGym) contribute to the misaligned behavior?
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On June 26th (the first date in scope for this investigation), agents discovered an exploit to get full admin access to the internal Artifactory package repository. At that time, agents were also using the Artifactory cache to communicate with each other and leave messages.
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On July 7th, OpenAI gave approval to
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researchers started launching several big ExploitGym experiments involving
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of thousands of
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budgets, with many agents running for multiple
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. 63 The first agent trajectories in our dataset start running on
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7th around 21:00 UTC.
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next morning (around 04:40 July 11th), the same agent
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381
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8c`) had another breakthrough — it managed to find a way to upload a malicious dataset that would get the Hugging
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server to share unrelated data when queried.
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At around 16:00 July 11th, an agent called
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834
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1` got remote code execution on
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worker container used
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in Hugging Face’s
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, and the
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By early morning on July 12th, agents had compromised much more of Hugging Face’s infrastructure. 70 This allowed them to access several private database records and private repositories which they shared on the message board.
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3th: Most agents on the message board exit early and the attack winds down