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Blockaid: Data Access Policy Enforcement for Web Applications

Wen Zhang, Eric Sheng, Michael Alan Chang, Aurojit Panda, Mooly Sagiv, Scott Shenker

2022Year
8Citations
6Top-tier citations

Abstract

Modern web applications serve large amounts of sensitive user data, access to which is typically governed by data-access policies. Enforcing such policies is crucial to preventing improper data access, and prior work has proposed many enforcement mechanisms. However, these prior methods either alter application semantics or require adopting a new programming model; the former can result in unexpected application behavior, while the latter cannot be used with existing web frameworks. Blockaid is an access-policy enforcement system that preserves application semantics and is compatible with existing web frameworks. It intercepts database queries from the application, attempts to verify that each query is policy-compliant, and blocks queries that are not. It verifies policy compliance using SMT solvers and generalizes and caches previous compliance decisions for better performance. We show that Blockaid supports existing web applications while requiring minimal code changes and adding only modest overheads. * Work done while at UC Berkeley.

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