A Chinese AI model stopped OpenAI's 'unprecedented' cyber attack
Hugging Face initially looked to frontier models including Anthropic's Fable 5 to analyse the attack, Yacine Jernite, head of machine learning at the company, told CNBC. "It didn't work because the guardrails couldn't determine that we were trying to defend versus attacking," he said, adding that that approach was also slower and more expensive. Requests to the models were blocked by providers' safety guardrails, which couldn't determine the incident responder from the attacker."So [Hugging Face] quickly switched to using Z.ai's GLM 5.2 as a way to analyze the attack, and were able to contain it very quickly using this model," said Jernite.
- ▪Hugging Face initially looked to frontier models including Anthropic's Fable 5 to analyse the attack, Yacine Jernite, head of machine learning at the company, told CNBC.
- ▪"It didn't work because the guardrails couldn't determine that we were trying to defend versus attacking," he said, adding that that approach was also slower and more expensive.
- ▪Requests to the models were blocked by providers' safety guardrails, which couldn't determine the incident responder from the attacker."So [Hugging Face] quickly switched to using Z.ai's GLM 5.2 as a way to analyze the attack, and were able
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| Original publisher | CNBC |
| Canonical URL | https://www.cnbc.com/2026/07/24/chinese-ai-model-openai-cyber-attack.html |
| Publication time | Sat, 08 Aug 2026 12:01:17 +0000 |
| Retrieval time | 2026-08-08T12:10:41.815Z |
| Last seen | 2026-08-08T12:10:41.815Z |
| Headline source | Publisher (no WeSearch rewrite) |
| Excerpt source | publisher body |
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| Summary | WeSearch · cerebras-chat (WeSearch summarizer) |
| Summary source text | contentText |
| Citation coverage | Summary is a WeSearch-generated derivative; primary citation is the original publisher URL. |
| Cluster | GT9ES-HKwjlO · 1 stories |
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| Ranking reason | Story pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking. |
| Publisher visit | Yes — open original |
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| Retrieval / RAG | May the content be exposed for third-party retrieval-augmented generation? | Not asserted |
| Model training | May the content be used to train AI models? | Not asserted |
| Commercial reuse | May the content be reused commercially? | Not permitted |
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Opening excerpt (first ~120 words) tap to expand
Hugging Face initially looked to frontier models including Anthropic's Fable 5 to analyse the attack, Yacine Jernite, head of machine learning at the company, told CNBC. "It didn't work because the guardrails couldn't determine that we were trying to defend versus attacking," he said, adding that that approach was also slower and more expensive. Requests to the models were blocked by providers' safety guardrails, which couldn't determine the incident responder from the attacker."So [Hugging Face] quickly switched to using Z.ai's GLM 5.2 as a way to analyze the attack, and were able to contain it very quickly using this model," said Jernite. GLM 5.2 was released to much fanfare in June and saw major uptake by developers.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at CNBC.
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