mlsanityData to 14 Oct 2026

Language-Based Agent Control

arXiv 2605.12863 ↗First posted 13 May 2026cs.PL cs.AI cs.CRcited by 1

On the map: LLM agents and tool use → Agent threats, guardrails and governance

Abstract (arXiv)

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.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Placed in Agent threats, guardrails and governance, one of 16 directions in LLM agents and tool use. Builds on 7 of its 30 references that are in the map. First posted on arXiv 13 May 2026.

Builds on

7 of 30 references.

References · 7

  1. 2023AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversationcited by 1,988
  2. 2025Securing AI Agents with Information-Flow Controlcited by 121
  3. 2025Contextual Agent Security: A Policy for Every Purposecited by 59
  4. 2026An AI Agent Execution Environment to Safeguard User Datacited by 4
  5. 2017Linear Haskell: practical linearity in a higher-order polymorphic languagecited by 2
  6. 2019Resource-Guided Program Synthesiscited by 2
  7. 2022Flux: Liquid Types for Rustcited by 2

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 1.

1 paper.

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  1. 2026Turn: A Language for Agentic Computation
  2. 2026SecureClaw: Clawing Back Control of LLM Agents
  3. 2025Architecting Resilient LLM Agents: A Guide to Secure Plan-then-Execute Implementations
  4. 2026Agentao: A Policy-Governed Runtime Harness for Embeddable Tool-Using LLM Agents
  5. 2026SafeAgent: A Runtime Protection Architecture for Agentic Systems
  6. 2026Toward Secure LLM Agents: Threat Surfaces, Attacks, Defenses, and Evaluation
  7. 2026AgentFlow: A Flow-Centric Policy Language and Framework for Securing LLM Agent Systems
  8. 2025Please Don't Kill My Vibe: Empowering Agents with Data Flow Control