Microsoft has released comprehensive guidance to empower developers in building and deploying secure Large Language Model (LLM) applications. This essential advice recognizes the unique attack surface introduced by generative AI, urging developers to integrate security considerations from the initial design phase.
The guidance addresses critical areas vital for mitigating risks in an evolving threat landscape:
- Prompt Injection Prevention: Strategies to counter malicious inputs designed to manipulate an LLM’s behavior or extract sensitive information.
- AI Model Supply Chain Security: Recommendations for verifying the provenance, integrity, and dependencies of AI models to prevent compromise.
- Data Privacy: Best practices for handling sensitive user data, ensuring its protection and preventing inadvertent exposure or misuse by the LLM.
- Robust Authentication Mechanisms: Guidelines for implementing strong access controls to safeguard LLM applications from unauthorized access and interactions.
By adopting these best practices, developers can build more resilient, trustworthy, and secure LLM-powered solutions, effectively navigating the complexities of AI security.
