Hugging Face got hacked

1. The evolving landscape of AI security and responsible AI usage.

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Recent incidents like Hugging Face's breach emphasize the need for continuous improvement in AI security measures and responsible AI deployment.

• Adapting to emerging threats and vulnerabilities is essential for safeguarding AI platforms and user data.
• Enhancing AI security protocols and promoting responsible AI practices are critical for industry sustainability.
• Incidents like these drive innovation in AI security and underscore the importance of proactive risk management.

2. Hugging Face faced a significant security breach.

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Wiz research compromised Hugging Face's infrastructure, highlighting the risks of malicious models using pickle for code execution.

• Models using pickle can execute arbitrary code, posing serious security threats.
• Hugging Face introduced safe tensors to mitigate risks and implemented model scanning for unsafe models.
• The breach led to privilege escalations and a complete takeover of Hugging Face's cluster.

3. Hugging Face addressed security vulnerabilities with new measures.

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Implementing safe tensors and model scanning, Hugging Face aims to enhance model safety and prevent malicious code execution.

• Safe tensors restrict the execution of arbitrary code, enhancing overall platform security.
• Model scanning alerts users to unsafe models, providing transparency and risk mitigation.
• The company took steps to secure its infrastructure post-breach, emphasizing user safety.

4. Risks associated with inference APIs and model execution.

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Allowing inference APIs and models using pickle can lead to security vulnerabilities and potential exploitation.

• Insecure model execution can result in privilege escalations and unauthorized access.
• Hugging Face's breach exposed the dangers of unchecked model execution and the need for stricter controls.
• Balancing model functionality with security measures is crucial for platform integrity.

5. The importance of secure model storage and sharing.

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Balancing model accessibility with security, Hugging Face's breach underscores the need for safe storage formats like safe tensors.

• Ensuring secure model sharing is crucial for maintaining platform integrity and user trust.
• Safe tensors offer a compromise between accessibility and security, promoting responsible AI usage.
• Hugging Face's incident highlights the challenges of facilitating model sharing while ensuring safety.

6. Microsoft offers a free course on generative AI for beginners.

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Microsoft's course covers responsible AI use, prompt engineering, chat applications, and more, beneficial even for non-coders.

• Course includes lessons on prompt engineering fundamentals and low code applications.
• Accessible to beginners in generative AI, regardless of coding interest.
• Highlights responsible use of generative AI.

7. Hugging Face introduces a streaming parser for the ggf file format.

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A new library allows streaming parsing of ggf files, crucial for edge inference like in web browsers, avoiding large file downloads.

• Enables reading files in a streaming manner without pre-downloading large files.
• Facilitates efficient file consumption for model files.
• GGF format gaining popularity for sharing model files.