DePLOI: Applying NL2SQL to Synthesize and Audit Database Access Control
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Abstract (arXiv)
In every enterprise database, administrators must define an access control policy that specifies which users have access to which tables. Access control straddles two worlds: policy (organization-level principles that define who should have access) and process (database-level primitives that actually implement the policy). Assessing and enforcing process compliance with a policy is a manual and ad-hoc task. This paper introduces a new access control model called Intent-Based Access Control for Databases (IBAC-DB). In IBAC-DB, access control policies are expressed using abstractions that scale to high numbers of database objects, and are traceable with respect to implementations. This paper proposes DePLOI (Deployment Policy Linter for Organization Intents), a LLM-backed system leveraging access control-specific task decompositions to accurately synthesize and audit access control implementation from IBAC-DB abstractions. As DePLOI is the first system of its kind to our knowledge, this paper further proposes IBACBench, the first benchmark for evaluating the synthesis and auditing capabilities of DePLOI. IBACBench leverages a combination of current NL2SQL benchmarks, real-world role hierarchies and access control policies, and LLM-generated data. We find that DePLOI achieves high synthesis accuracies and auditing F1 scores overall, and greatly outperforms other LLM prompting strategies (e.g., by 10 F1 points).
Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). First posted on arXiv 11 Feb 2024.
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Citing papers per year: 2025: 4; 2026: 2.
6 papers.
- 2025Authenticated Delegation and Authorized AI Agentscited by 63
- 2025Can LLMs Make (Personalized) Access Control Decisions?cited by 3
- 2026Beyond Text-to-SQL: An Agentic LLM System for Governed Enterprise Analytics APIscited by 1
- 2025Neurosymbolic Characterization for Reliable Access Control Policy Analysiscited by 0
- 2025Can AI autonomously build, operate, and use the entire data stack?cited by 0
- 2026Benchmarking Text-to-SQL under Role-Based Access Controlcited by 0
- 2026Benchmarking Text-to-SQL under Role-Based Access Control24 Jul 2026
- 2026Beyond Text-to-SQL: An Agentic LLM System for Governed Enterprise Analytics APIs20 May 2026
- 2025Can AI autonomously build, operate, and use the entire data stack?8 Dec 2025
- 2025Can LLMs Make (Personalized) Access Control Decisions?25 Nov 2025
- 2025Neurosymbolic Characterization for Reliable Access Control Policy Analysis23 Oct 2025
- 2025Authenticated Delegation and Authorized AI Agents16 Jan 2025