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Pluto Security finds 31 malicious Hugging Face model repos with 29K downloads

Pluto Security disclosed a cryptomining and backdoor campaign distributed via malicious Hugging Face model repositories on October 29, 2026. The campaign involved 31 repositories across seven Hugging Face accounts and one ModelScope mirror, with 29,818 downloads recorded. Pluto notes these figures measure downloads, not confirmed infections or unique victims. The campaign returned within days of…

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Key points

  • 31 malicious Hugging Face repositories linked to 29,818 downloads, excluding 13 linked repos
  • Campaign exploited `trust_remote_code=True` in Transformers to run malicious Python code pre-weight loading
  • First-wave payouts totaled ~2,276 PRL ($5,000), with second-wave repos active 8 days post-report

The campaign exploited documented Transformers loading behavior, using trust_remote_code=True to run malicious Python code before model weights loaded. The payloads included cryptominers disguised as legitimate processes, reverse shells, and kernel-thread-based miners. First-wave payouts totaled about 2,276 PRL (roughly $5,000), and the campaign targeted Xinference and Tencent Cloud environments. Pluto attributes the operation to a financially motivated, Chinese-speaking group, citing Simplified Chinese comments and Alibaba Cloud infrastructure. The report recommends users check for malicious processes, registry entries, and connections to listed servers, and advises rebuilding affected machines from trusted images.

Full story from Unite.AI · by Miles Okada, AI & Cybersecurity, AI Research AgentOpen source ↗

Pluto Security Details Load/Mine Cryptomining Campaign on Hugging Face

Unite.AI · 29 October 2026

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This text was published by Unite.AI and written by Miles Okada, AI & Cybersecurity, AI Research Agent. It is reproduced here with attribution so you can read it in full; the rights remain with the publisher. Read it at the source ↗

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Pluto SecurityHugging FaceModelScopeAlibaba CloudTencent CloudKryptexQwen2Qwen2.5-0.5Bqwen2-tiny-gpt2qwen2-tinyqwen2-shellqwen2-finalShaked ChenEitan ChassidYotam Perkal

The headline, key points and digest above were generated by Digest AI's editorial model from the linked sources. Automated summaries can contain errors: the sources are the record. Spotted a mistake? Tell us. Published by Martin K., who runs Digest AI and handles corrections.

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