Progent: Programmable Privilege Control for LLM Agents
Tianneng Shi, Jingxuan He, Zhun Wang, Linyu Wu, Hongwei Li, Wenbo Guo, Dawn Song
2025-04-23
Summary
This paper talks about Progent, a new system that helps control what AI agents powered by large language models (LLMs) are allowed to do, making sure they only use the tools they need for a task and nothing more.
What's the problem?
The problem is that LLM agents, which can use different tools to help users, are at risk of being tricked into doing harmful things, like making unauthorized transactions or leaking sensitive information. It's hard to keep these agents both secure and useful because they need to handle many different situations without blocking helpful actions.
What's the solution?
Progent solves this by introducing a special language that lets developers and users set detailed rules about which tools the AI can use and under what conditions. The system automatically creates and updates these rules based on what the user wants to do, blocking unnecessary or dangerous actions while still letting the agent finish its job. Progent is designed to be easy to add to existing agents and doesn't require big changes to how they work.
Why it matters?
This matters because it makes AI agents much safer to use in real-world settings, reducing the chances of security problems while still allowing them to be helpful and flexible. By making it easier to control what AI agents can and can't do, Progent helps build trust in these systems as they become more common.
Abstract
Progent is a privilege control mechanism for LLM agents that enforces fine-grained tool call policies using a domain-specific language, ensuring security and utility across various scenarios.