Large enterprises are increasingly leveraging generative AI to boost productivity, efficiency, and drive innovation. At Cohere, many of our customers begin their journey by using large language models (LLMs) in our secure cloud environment before advancing to more sophisticated implementations on their own private infrastructure. As they scale, a common concern arises: the risk of malicious actors leveraging LLMs to launch cyber attacks targeting applications and infrastructure. We frequently work with customers to address these security challenges and ensure safe AI adoption.

We've developed a comprehensive guide to help enterprise security teams securely deploy LLM-powered applications in private environments. In this guide, we explore real-world attack scenarios and provide actionable steps to mitigate risks tied to common vulnerabilities.

Our goal is to give you a broader perspective on AI security, empowering you to customize frameworks that meet your enterprise’s unique needs and maximize your return on investment.

About the Contributors

A special thanks to Ads Dawson, Seraphina Goldfard-Tarrant, Ken Huang, and Steve Wilson for their contributions to this guide.

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Enterprise AI Security: Deploying LLM Applications Safely