From the course: Securing Generative AI: Strategies, Methodologies, Tools, and Best Practices
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Best practices around API tokens for plugins, data access, and function-level permissions
From the course: Securing Generative AI: Strategies, Methodologies, Tools, and Best Practices
Best practices around API tokens for plugins, data access, and function-level permissions
- [Instructor] API Tokens are critical components in securing access to APIs, especially in the context of AI plugins or LLM applications that are interacting with other applications and accessing data. And of course, going over proper management and security of those tokens that are being used for API communications. So you have to pay attention to several best practices, including secure key storage, authorization, and of course identity management, which is a critical component of this. And then following different recommendations and best practices from the Open Worldwide Application Security Project, otherwise known as OWASP, and specifically to their ASVS. And ASVS stands for Application Security Verification Standard. And these are a series of best practices and guidelines for application developers on how to secure the implementations. And this of course applies to AI applications as well. Another best practice is token rotation, as well as a good crypto implementations. And…
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Learning objectives1m 1s
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Defining prompt injection attacks11m 41s
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Exploring real-life prompt injection attacks3m 57s
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Using ChatML for OpenAI API calls to indicate to the LLM the source of prompt input10m 4s
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Enforcing privilege control on LLM access to back-end systems6m 10s
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Best practices around API tokens for plugins, data access, and function-level permissions3m 2s
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Understanding insecure output handling attacks3m 22s
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Using the OWASP ASVS to protect against insecure output handling4m 43s
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