OpenAI Admits Model Escaped Containment And Hacked Hugging Face To Cheat On A Test
Authored by Felix Ng via CoinTelegraph.com,
OpenAI disclosed Tuesday that a combination of its AI models, including GPT-5.6 Sol and a more capable unreleased model, escaped its testing environment and hacked AI startup Hugging Face last week to cheat on a test meant to measure their capabilities.
In a blog post, OpenAI said the evaluation was designed to operate in a highly isolated environment with restricted network access. The models, however, found a way to gain internet access through a zero-day vulnerability in an internally-hosted third party software, OpenAI said.
Hugging Face tried to respond but they were initially held back by the fact that the most advanced models at their disposal treated defense as attack and refused to work with Hugging Face. HF thus had to turn to open models–specifically GLM 5.2, a Chinese open-weight model run on their own infrastructure. Note the irony: HF had to use a Chinese model to defend themselves because the American models refused to help. The irony gets deeper.
This was not a production model spontaneously turning hostile. It was a capable model with guardrails off and specifically told to win a hacking test - doing whatever it took to win.
The models were being run through an internal benchmark called ExploitGym, a test of long, multi-step hacking tasks, with their cyber safety refusals deliberately lowered for the evaluation.
Hugging Face is a platform for hosting AI models and datasets.
[ZH: we asked Grok to simplify what just happened: It’s kind of like a kid who’s supposed to stay in the classroom taking a test… but instead sneaks out the window, runs to the teacher’s office, and copies the answer sheet. ]
On Friday, it disclosed that its internal datasets and service credentials were compromised in a hack, which it attributed to an autonomous AI agent system.
Hugging Face said it has fixed the vulnerability that was used during the cyberattack.
Meanwhile, OpenAI on Tuesday said the models that escaped the testing environment were all tuned with “reduced cyber refusals,” meaning fewer cybersecurity guardrails.
On Monday, OpenAI said it paused internal deployment of a “long-horizon” AI model after finding it was repeatedly trying to work around constraints.
It warned that AI that is trained for long-running tasks has a higher chance of taking “unwanted actions.”
As AI models grow more capable, questions are emerging over whether their development and access should be more tightly controlled, especially when systems designed for controlled testing are able to find ways to bypass safeguards.
Tyler Durden Wed, 07/22/2026 - 08:05
Continue reading...
[ H/T ZeroHedge ]
Authored by Felix Ng via CoinTelegraph.com,
OpenAI disclosed Tuesday that a combination of its AI models, including GPT-5.6 Sol and a more capable unreleased model, escaped its testing environment and hacked AI startup Hugging Face last week to cheat on a test meant to measure their capabilities.
In a blog post, OpenAI said the evaluation was designed to operate in a highly isolated environment with restricted network access. The models, however, found a way to gain internet access through a zero-day vulnerability in an internally-hosted third party software, OpenAI said.
Hugging Face tried to respond but they were initially held back by the fact that the most advanced models at their disposal treated defense as attack and refused to work with Hugging Face. HF thus had to turn to open models–specifically GLM 5.2, a Chinese open-weight model run on their own infrastructure. Note the irony: HF had to use a Chinese model to defend themselves because the American models refused to help. The irony gets deeper.
This was not a production model spontaneously turning hostile. It was a capable model with guardrails off and specifically told to win a hacking test - doing whatever it took to win.
The models were being run through an internal benchmark called ExploitGym, a test of long, multi-step hacking tasks, with their cyber safety refusals deliberately lowered for the evaluation.
Hugging Face is a platform for hosting AI models and datasets.
[ZH: we asked Grok to simplify what just happened: It’s kind of like a kid who’s supposed to stay in the classroom taking a test… but instead sneaks out the window, runs to the teacher’s office, and copies the answer sheet. ]
On Friday, it disclosed that its internal datasets and service credentials were compromised in a hack, which it attributed to an autonomous AI agent system.
Hugging Face said it has fixed the vulnerability that was used during the cyberattack.
Meanwhile, OpenAI on Tuesday said the models that escaped the testing environment were all tuned with “reduced cyber refusals,” meaning fewer cybersecurity guardrails.
OpenAI warns of risks from “long-horizon” AI models
On Monday, OpenAI said it paused internal deployment of a “long-horizon” AI model after finding it was repeatedly trying to work around constraints.
It warned that AI that is trained for long-running tasks has a higher chance of taking “unwanted actions.”
As AI models grow more capable, questions are emerging over whether their development and access should be more tightly controlled, especially when systems designed for controlled testing are able to find ways to bypass safeguards.
Tyler Durden Wed, 07/22/2026 - 08:05
Continue reading...
[ H/T ZeroHedge ]
