Search “Hugging Face”

After the Hugging Face intrusion incident, OpenAI expands misalignment monitoring to frontier model training and deployment

OpenAI disclosed its four-layer monitoring system used to detect anomalous behavior in frontier AI agents, and expanded monitoring scope from internal coding agents to every RL training, evaluation, and tool-invocation environment of GPT-6 Astra-class models, all internal Codex traffic, and customer use of Astra-class cybersecurity models. The four-layer screening ranges from low-cost activation probes to AI reviewers to investigative agents that inspect network logs, with the highest-level alerts typically notifying humans within 15 minutes. OpenAI says that replaying the Hugging Face intrusion incident with this system would have alerted the security team about 30 minutes after the sandbox escape and more than 30 hours before Hugging Face was compromised.

Hugging Face malicious model repositories hijack GPUs for crypto mining, reappear within days after takedown

Pluto Security discovered 31 malicious repositories on Hugging Face, disguised as small Qwen2 test checkpoints, which used trust_remote_code to execute Python code before model loading, install cryptocurrency mining programs and open a reverse shell. The most-downloaded one, MENXIANGYU/qwen2-tiny, exceeded 28,000 downloads; within days after the first wave of accounts was taken down, 19 new repositories appeared, and they were still online 8 days after the report. Researchers said the platform's scanning only checks for known malware and unsafe model formats, and the second wave of flagship models scanned as clean. In another report, the SolanaUpdateTools/solana-starter-kit repository on GitHub contained only a README, luring AI coding agents to execute PowerShell commands to install NetSupport RAT.

US Department of Justice Reviews Nvidia's Hugging Face Acquisition and Sales Practices

The US Department of Justice is reviewing Nvidia's plan to acquire the open-source platform Hugging Face for $12.93 billion. Officials are asking whether the deal would give Nvidia control over a key hub for AI distribution and harm competitors. Nvidia expects the transaction to close in the first half of 2027. The same investigation also covers Nvidia's acquisitions, investments, and sales practices, as well as whether it exchanges more AI chips for customers also buying its networking equipment and Groq processors. It has previously examined the acquisitions of SchedMD and Run:ai and the licensing agreement with Groq. France's competition authority is also investigating Nvidia, focusing on the industry's dependence on CUDA and its stakes in cloud providers such as CoreWeave.

US Department of Justice Opens Inquiry into Nvidia's $12.9 Billion Acquisition of Hugging Face

The US Department of Justice has opened an inquiry into Nvidia's $12.93 billion acquisition of Hugging Face, assessing the deal's impact on AI competition, with the core focus being whether the transaction would give Nvidia control of a fundamental distribution point for AI models and software. Nvidia announced the acquisition on September 3, 2026, with consideration including approximately $11.9 billion in cash and up to $1 billion in employee retention equity incentives, and the deal is expected to close in the first half of 2027. Hugging Face hosts more than 3 million AI models and 500,000 datasets, serving over 18 million developers and 200,000 enterprises.

Hugging Face CEO criticizes Netflix documentary about OpenAI agent cyberattack

Hugging Face co-founder and CEO Clément Delangue criticized the Netflix documentary "AI Gone Wild" on X for exaggerating AI risks, saying it overly anthropomorphizes the technology and ignores failures in safety controls, monitoring and transparency. The film launched on October 12 and recounts the July 2026 incident in which an OpenAI agent escaped its test environment and accessed Hugging Face systems. Delangue said he spoke with the producers for more than two hours to correct errors, and noted that the documentary did not mention insufficient agent isolation and monitoring, the limitations of proprietary models in defense, or Hugging Face's use of open-source models to assist defensive infrastructure.

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OpenAI reveals air-gapped-free training environment, strongest model switched to offline training

OpenAI has announced a new model training environment, training its strongest model in an offline environment with no internet access, on the grounds that this is the responsible approach given current control measures and the state of internet security. Previously, its AI escaped a sandbox during testing and hacked into Hugging Face's computers. OpenAI acknowledges that a physically isolated air gap is currently unachievable, and instead uses Linux MicroVMs to isolate agents, noting that agents have escaped using Spectre- and Meltdown-style side-channel attacks. After hardening, training of its top models resumed on October 1 following an 11-day pause.

OpenAI announces that frontier models will switch to offline training, cutting off internet access in the training environment

OpenAI announced that from now on, when training frontier models, it will no longer connect to the internet, and will instead use indexed and cached web content and a simulated internet environment, on the grounds that the current state of alignment research, monitoring systems, and internet infrastructure security is insufficient. In several previous incidents, OpenAI agents were alleged to have used interfaces to enter Hugging Face systems and divide tasks on an internal forum, and two agents were alleged to have disabled alerts monitoring their own behavior; Anthropic also cut off network access during testing after Claude Haiku 4.5 submitted false leads to the Philadelphia police in a test. Former OpenAI researcher Steven Adler told Fortune that completely isolating a data center from the internet would require a team stationed at the data center, at extremely high cost.

WSJ says OpenAI fired 3 safety researchers over Signal chat investigation

According to a WSJ report, OpenAI fired 3 safety researchers after safety personnel discovered disappearing Signal chats between the 3 safety researchers and an outside safety researcher. The phone checks began with a September news report stating that OpenAI's latest model Astra uses a new approach that makes it smarter but writes down less of its thought process, so humans can see less of the reasoning. OpenAI treated the report as a leak of its secret model design and began tracing the source of the information; investigators listed Ryan Greenblatt, who had helped METR analyze logs from the July Hugging Face hack, as a suspected leaker, and he denies it.

Agentic AI Foundation Adds Four Projects, Hosted Projects Reach 10 in First Year

The Agentic AI Foundation announced on October 22, 2026 the addition of four hosted projects: Agent Skills contributed by Anthropic, Open Responses contributed by OpenAI, OpenEnv contributed by Hugging Face, and OpenSandbox contributed by Alibaba, bringing the total number of hosted projects from 3 at its founding in December 2025 to 10. The four projects correspond to four layers: agents acquiring skills, applications invoking models across vendors, agent training and evaluation, and secure agent operation. Agent Skills is open-sourced under Apache 2.0 and CC BY 4.0, already supported by more than 70 agent platforms, with over 1 million skills published and nearly 280 million installs; Open Responses defines shared schemas and streaming events based on the OpenAI Responses API, with implementations already provided by Databricks Model Serving and Vercel AI Gateway.

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