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This paper proposes applying static typing and language-based security to LLM agents: agent-generated programs are type-checked against policies before they run, so access control and information-flow rules cover both agent code and developer scaffolding. The approach is still a research proposal, evaluated through three case studies (filesystem sandboxing, data provenance, information-flow control). For AI readers, the open questions are how much expressiveness survives in practice and how well the type system holds up against real, messy agent behavior.
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Language-Based Agent Control

arXiv2 min de cititArticolul și perspectiva sunt în engleză.

arXiv:2605.12863v2 Announce Type: replace-cross Abstract: This paper introduces language-based agent control (LBAC), a new programming model for agentic applications that brings techniques from programming languages and language-based security to the problem of agent control. In conventional programming, combinations of static typing and runtime enforcement have long been used to guarantee that well-typed programs satisfy user-specified policies, including policies for access control, information flow, data provenance, and more. The key idea behind LBAC is to extend these guarantees to agentic applications by requiring agents to generate programs that are themselves well typed in the context of the surrounding scaffolding code. Unsafe programs are rejected by the type-checker before execution, allowing policies to apply uniformly across the entire application, including both agent-generated behavior and developer-written scaffolding. At the same time, LBAC preserves substantial expressiveness: agents may perform arbitrary side-effect-free computation and recursively invoke subagents, which retain full tool access subject to the same -- or potentially more restrictive -- policies. We demonstrate LBAC with three case studies: I/O sandboxing via filesystem capabilities, data provenance, and information-flow control.

Abstract:This paper introduces language-based agent control (LBAC), a new programming model for agentic applications that brings techniques from programming languages and language-based security to the problem of agent control. In conventional programming, combinations of static typing and runtime enforcement have long been used to guarantee that well-typed programs satisfy user-specified policies, including policies for access control, information flow, data provenance, and more. The key idea behind LBAC is to extend these guarantees to agentic applications by requiring agents to generate programs that are themselves well typed in the context of the surrounding scaffolding code. Unsafe programs are rejected by the type-checker before execution, allowing policies to apply uniformly across the entire application, including both agent-generated behavior and developer-written scaffolding. At the same time, LBAC preserves substantial expressiveness: agents may perform arbitrary side-effect-free computation and recursively invoke subagents, which retain full tool access subject to the same -- or potentially more restrictive -- policies. We demonstrate LBAC with three case studies: I/O sandboxing via filesystem capabilities, data provenance, and information-flow control.

Programming Languages (cs.PL); Artificial Intelligence (cs.AI); Cryptography and Security (cs.CR)

arXiv:2605.12863 [cs.PL]

(or arXiv:2605.12863v2 [cs.PL] for this version)

https://doi.org/10.48550/arXiv.2605.12863 Focus to learn more arXiv-issued DOI via DataCite

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