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The software supply chain faces significant risks, particularly with open-source AI software. Investigations into Hugging Face revealed up to one hundred potentially malicious models, highlighting vulnerabilities that can catch development teams off guard. This situation underscores the need for heightened awareness and security measures in acquiring machine learning models and datasets.
The rise of large language models (LLMs) has intensified concerns over supply chain security, necessitating proactive measures from cybersecurity leaders. Vulnerabilities specific to LLMs, such as prompt injection and hallucination, can lead to the introduction of insecure code and new types of supply chain attacks. Implementing strategies like Zero Trust and utilizing tools such as digital signatures and watermarks can help mitigate these risks.
• Hugging Face revealed vulnerabilities in open-source AI models.
• LLM-specific vulnerabilities can lead to significant supply chain risks.
LLMs are advanced AI models that process and generate human-like text, raising security concerns in software supply chains.
Prompt injection is a vulnerability that allows adversaries to manipulate LLMs through crafted inputs, potentially corrupting outputs.
Zero Trust is a security model that requires strict verification for all users and devices, crucial for safeguarding AI systems.
Hugging Face is a platform for sharing AI models and datasets, recently highlighted for hosting potentially malicious models.
Facebook developed PyTorch, an open-source ML library, which has raised concerns about security vulnerabilities in AI applications.
Isomorphic Labs, the AI drug discovery platform that was spun out of Google's DeepMind in 2021, has raised external capital for the first time. The $600
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Sam Altman today revealed that OpenAI will release an open weight artificial intelligence model in the coming months. "We are excited to release a powerful new open-weight language model with reasoning in the coming months," Altman wrote on X.
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