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Prose2Policy (P2P): A Practical LLM Pipeline for Translating Natural-Language Access Policies into Executable Rego

arXiv cs.AI / 3/18/2026

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Key Points

  • Prose2Policy (P2P) is an LLM-based tool that translates natural-language access control policies into executable Rego for Open Policy Agent.
  • It provides a modular end-to-end pipeline including policy detection, component extraction, schema validation, linting, compilation, and automatic test generation and execution.
  • On the ACRE dataset, it achieved a 95.3% compile rate for accepted policies, with automated testing achieving an 82.2% positive-test pass rate and a 98.9% negative-test pass rate.
  • The approach targets Zero Trust and compliance-driven environments, prioritizing deployment reliability and auditability of policy-as-code.

Abstract

Prose2Policy (P2P) is a LLM-based practical tool that translates natural-language access control policies (NLACPs) into executable Rego code (the policy language of Open Policy Agent, OPA). It provides a modular, end-to-end pipeline that performs policy detection, component extraction, schema validation, linting, compilation, automatic test generation and execution. Prose2Policy is designed to bridge the gap between human-readable access requirements and machine-enforceable policy-as-code (PaC) while emphasizing deployment reliability and auditability. We evaluated Prose2Policy on the ACRE dataset and demonstrated a 95.3\% compile rate for accepted policies, with automated testing achieving a 82.2\% positive-test pass rate and a 98.9\% negative-test pass rate. These results indicate that Prose2Policy produces syntactically robust and behaviorally consistent Rego policies suitable for Zero Trust and compliance-driven environments.