DeepSeek R1: What Security Teams Need to Know

The release of DeepSeek R1, an open-source AI model from China, has garnered attention due to its potential as an alternative to models like ChatGPT and its impact on stock markets. While open-source models are generally seen as safer than proprietary ones, questions about the security and legal risks of using DeepSeek, particularly given its Chinese origin, are crucial for security teams. Endor Labs provides a methodology for evaluating these risks by analyzing models through a scoring system based on four risk categories: security, activity, popularity, and operational aspects. DeepSeek R1 has an overall Endor Score of 7 out of 10, with individual scores reflecting both positive aspects, such as its MIT license and customizable open-source weights, and concerns like the lack of a dataset and potential risks in example codes. Although the model itself is not inherently unsafe, users are advised to evaluate it within their threat models and organizational policies, especially given security vulnerabilities in its hosted service. The discourse around DeepSeek's open-source status and potential issues with model alignment and licensing highlights the need for ongoing scrutiny as organizations increasingly adopt AI models as critical dependencies in their software ecosystems.

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