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The Cloud Security Alliance (CSA) has released a report detailing best practices for securing systems that utilize Large Language Models (LLMs). This guidance is particularly aimed at system engineers, architects, and security professionals, addressing the security risks associated with LLMs and providing design patterns to enhance system capabilities. The report emphasizes the need for robust authorization practices to mitigate potential vulnerabilities in AI systems.
Key recommendations include ensuring that authorization decisions are made outside of LLMs and enforcing strict access controls. The report also highlights the importance of continuous verification of identities and permissions, as well as the necessity of human oversight in critical access control decisions. These practices aim to enhance the security of AI systems while leveraging their powerful capabilities.
• CSA outlines essential practices for securing LLM-backed systems.
• Emphasis on external authorization to enhance AI system security.
LLMs are central to the report's focus on security risks and best practices.
The report stresses that authorization decisions should be made outside of LLMs to maintain security.
The report discusses the risks and challenges associated with developing these agents.
CSA's recent report provides critical guidance for securing AI systems using LLMs.
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