SOURCE-LINKED INTELLIGENCE
Structured Decomposition for Reliable LLM-Generated Access Control Policies
This paper presents an LLM-based system that translates natural-language access control policies (NLACPs) into executable Rego code for Open Policy Agent (OPA). It provides a modular, end-to-end pipeline for policy detection, component extraction, schema validation, linting, compilation, and automated test generation and execution. The system is designed to bridge the gap between human-readable access requirements and machine-enforceable policy-as-code (PaC), with a focus on deployment reliability and security correctness. We evaluate the system on 372 ACRE-complete access control statements w
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-21T03:02:03.000Z
First collected: 2026-09-23T09:51:33.063Z. This is not the publication date.