Data Flow Control: Data Safety Policies for AI Agents
Agents increasingly generate SQL, orchestrate pipelines, and automate data analysis on behalf of users. While recent work improves query correctness, correctness is not safety. A query may be semantically valid yet violate regulatory, privacy, or business constraints that govern how data may be combined and released. We argue that enforcing such constraints is fundamentally a data infrastructure problem. This paper introduces Data Flow Control (DFC), a framework to declaratively specify and guarantee policy enforcement over tuple-level data flows within a DBMS query. A key challenge is defining a policy language that is optimizer-invariant yet efficient to enforce at scale. We formalize d...
| Authors | Charlie Summers, Eugene Wu |
|---|---|
| Primary category | cs.DB |
| Published | 4 June 2026 |
| Last updated at source | 4 June 2026 |
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