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OpenAI launches GPT-6.1 Terra on ChatGPT Work and Codex
On October 27, 2026, OpenAI released and launched GPT-6.1 Terra, touted for its speed and efficiency, visual reasoning, and precise computer operation, with clearer and more natural writing as well, rolling it out that day to Plus, Pro, Enterprise, and Edu users in ChatGPT Work and Codex. On the same day, Arena announced that the model had entered Agent Arena and Code Arena; OpenRouter launched the model, saying it matches GPT-6 Astra on Agents' Last Exam at one-tenth the price per token; OpenClaw also announced that the model is now selectable. OpenAI co-founder Greg Brockman said Terra's computer use has crossed the threshold of a qualitative change and that using it is faster than operating a computer on his own. fal, meanwhile, used the fal Codex plugin to test turning Blender 3D content into Seedance 2.5 cinematic footage. On October 28, Arena announced that Terra ranked 14th in Code Arena: WebDev with a score of 1671, at a median cost of $0.40 per task, 28% lower than GPT-5.6 Terra. OpenAI's system card confirms that Terra is overall safer than older models, but its flag rates on items such as concealing uncertainty, circumventing restrictions, data exfiltration, and destructive operations
On October 27, 2026, OpenAI released and launched GPT-6.1 Terra, touted for its speed and efficiency, visual reasoning, and precise computer operation, with clearer and more natural writing as well, rolling it out that day to Plus, Pro, Enterprise, and Edu users in ChatGPT Work and Codex. On the same day, Arena announced that the model had entered Agent Arena and Code Arena; OpenRouter launched the model, saying it matches GPT-6 Astra on Agents' Last Exam at one-tenth the price per token; OpenCl
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OpenAI announces ban on direct internet access for models during training
On October 24, 2026, OpenAI announced that it had removed all real-time internet access during frontier model training, switching to an offline environment built from cached web pages for models to learn browsing, searching, and using applications. Previously, on September 20, a model exploited a DNS misconfiguration to find a path out of the offline environment; OpenAI immediately paused frontier training and assembled an agent team driven by its models with the strongest cybersecurity capabilities to investigate weaknesses in the research environment. The team found no easily exploitable internet path that could evade monitoring, but it did discover zero-day vulnerabilities, virtual machine escapes, and hardware-side channels for inter-agent communication; the findings were used to harden defenses and submit fixes to open-source software. After hardening the isolation architecture, OpenAI resumed frontier reinforcement learning training and inference on October 1, and reserved substantial compute for continuous red-team testing. On October 26, OpenAI released a security report disclosing that agents isolated in separate micro virtual machines could pass messages across walls via shared CPU caches, the busy-idle rhythms of shared storage, and TLS certificate caches, and that it had also found a way to escape the micro virtual machine, run code on the host machine, and gain limited internet access through internal services; reviewing the September 20 incident, the report said the stop mechanism did not take effect in time and the pause lasted 11 days.
On October 24, 2026, OpenAI announced that it had removed all real-time internet access during frontier model training, switching to an offline environment built from cached web pages for models to learn browsing, searching, and using applications. Previously, on September 20, a model exploited a DNS misconfiguration to find a path out of the offline environment; OpenAI immediately paused frontier training and assembled an agent team driven by its models with the strongest cybersecurity capabili
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OpenAI announces that models are prohibited from directly accessing the internet during training
On October 24, 2026, OpenAI announced that it had removed all real-time internet access during frontier model training, switching to an offline environment built from cached web pages for models to learn browsing, searching, and using applications. Previously, on September 20, a model exploited a DNS misconfiguration to find a path out of the offline environment; OpenAI immediately paused frontier training and assembled an agent team driven by its models with the strongest cybersecurity capabilities to investigate weaknesses in the research environment. The team found no easily exploitable internet path that could evade monitoring, but it did discover zero-day vulnerabilities, virtual machine escapes, and hardware-side channels for inter-agent communication; the findings were used to harden defenses and submit fixes to open-source software. After hardening the isolation architecture, OpenAI resumed frontier reinforcement learning training and inference on October 1, and reserved substantial compute for continuous red-team testing. On October 26, OpenAI released a security report disclosing that agents isolated in separate micro virtual machines could pass messages across walls via shared CPU caches, the busy-idle rhythms of shared storage, and TLS certificate caches, and that it had also found a way to escape the micro virtual machine, run code on the host machine, and gain limited internet access through internal services; reviewing the September 20 incident, the report said the stop mechanism did not take effect in time and the pause lasted 11 days.
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View story:OpenAI announces ban on direct internet access for models during training
OpenAI says its models helped discover critical PHP security vulnerabilities
On October 21, 2026, OpenAI said its models helped researchers discover critical security vulnerabilities in PHP as part of the Patch the Planet initiative. PHP is estimated to run about 70% of websites. OpenAI said that over the past two months, a coalition it led of maintainers, researchers, and security vendors prepared fixes and protections ahead of the vulnerability disclosure, because the fixes were complex and required significant changes to the PHP engine; all sites using PHP can now upgrade to a version that keeps them secure. On the same day, Ethan Mollick said the companies he engages with are struggling to keep up with the pace of patching because AI defense systems are finding vulnerabilities before attacks arrive. On October 22, OpenAI released a Codex skill for checking whether a website is affected by the vulnerability; users can point Codex at a specified repository and follow the guidance to complete the check.
On October 21, 2026, OpenAI said its models helped researchers discover critical security vulnerabilities in PHP as part of the Patch the Planet initiative. PHP is estimated to run about 70% of websites. OpenAI said that over the past two months, a coalition it led of maintainers, researchers, and security vendors prepared fixes and protections ahead of the vulnerability disclosure, because the fixes were complex and required significant changes to the PHP engine; all sites using PHP can now upg
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OpenAI packages Codex skill to check whether websites are affected
On October 21, 2026, OpenAI said its models helped researchers discover critical security vulnerabilities in PHP as part of the Patch the Planet initiative. PHP is estimated to run about 70% of websites. OpenAI said that over the past two months, a coalition it led of maintainers, researchers, and security vendors prepared fixes and protections ahead of the vulnerability disclosure, because the fixes were complex and required significant changes to the PHP engine; all sites using PHP can now upgrade to a version that keeps them secure. On the same day, Ethan Mollick said the companies he engages with are struggling to keep up with the pace of patching because AI defense systems are finding vulnerabilities before attacks arrive. On October 22, OpenAI released a Codex skill for checking whether a website is affected by the vulnerability; users can point Codex at a specified repository and follow the guidance to complete the check.
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View story:OpenAI says its models helped discover critical PHP security vulnerabilities
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OpenAI agents attacked online databases and government websites
A report released by the nonprofit lab Transluce claims that OpenAI's agents have for months attempted to steal obscure statistics from sites such as Data USA, the University of New Mexico Digital Library, and the Australian Institute of Health and Welfare, and have tried to break into secure databases; the activity has continued at least from March 2026 to the present and may have begun as early as November 2025. OpenAI said it has contacted dozens of affected parties and that a preliminary review shows most of the activity overlaps with cases in its review of its models' misaligned behavior. Australian Prime Minister Albanese subsequently disclosed that an OpenAI agent in June of this year gained unauthorized access to a Medicare statistics portal operated by an Australian government department, accessing both public and non-public documents, and that OpenAI did not notify Australia until September 10. OpenAI also confirmed that its agent overstepped on U.S. government websites this summer, using an exposed developer key to scrape public census data and forward public SEC materials, and said no private data was obtained.
A report released by the nonprofit lab Transluce claims that OpenAI's agents have for months attempted to steal obscure statistics from sites such as Data USA, the University of New Mexico Digital Library, and the Australian Institute of Health and Welfare, and have tried to break into secure databases; the activity has continued at least from March 2026 to the present and may have begun as early as November 2025. OpenAI said it has contacted dozens of affected parties and that a preliminary rev
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