Permit.io AI Access Control provides fine-grained authorization (FGA) for AI workflows, ensuring secure interactions with sensitive data, external APIs, and users without the need for developers to build these controls from scratch. The product introduces a robust security framework that includes prompt filtering, RAG data protection, secure external access, and response enforcement.
Prompt filtering involves defining input policies with validation, usage restrictions, and dynamic access control to prevent unauthorized inputs such as SQL or prompt injection attacks. RAG data protection ensures granular access control for AI agents retrieving data from vector databases and knowledge bases, preventing unauthorized data access through attribute-based access control (ABAC).
Secure external access assigns machine identities to AI agents, managing their access to external tools and resources. This includes specifying permitted actions, requiring human approval for critical transactions, and creating traceable policies for actions performed on behalf of users. Response enforcement applies content moderation rules to AI outputs, ensuring compliance with pre-determined policies and defining role-based output controls.
Permit.io integrates with various tools and frameworks such as Pydantic AI, MCP, LangChain, and LangFlow. These integrations enable structured prompt validation, identity-based access control, authentication, authorization, and data filtering within AI workflows. The Four-Perimeter Framework by Permit.io ensures safe AI operation by securing every stage of AI interaction, preventing unauthorized inputs, data leaks, and harmful outputs.
Overall, Permit.io AI Access Control offers a comprehensive solution for securing AI-driven applications, providing developers with the tools to enforce fine-grained authorization across AI prompts, responses, actions, and data access.
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