Contextual and Granular Policy Enforcement in Database-backed Applications
This addresses data security and compliance issues for developers and organizations handling sensitive data, offering a practical solution to separate policy from code, though it is incremental in building on existing separation-of-concerns approaches.
The paper tackles the problem of enforcing complex, contextual data access policies in database-backed applications to prevent data breaches from missed checks, presenting Estrela, a framework that allows developers to specify API-specific restrictions with minimal overhead, as demonstrated by retrofitting real-world applications of 1000-80k lines of code.
Database-backed applications rely on inlined policy checks to process users' private and confidential data in a policy-compliant manner as traditional database access control mechanisms cannot enforce complex policies. However, application bugs due to missed checks are common in such applications, which result in data breaches. While separating policy from code is a natural solution, many data protection policies specify restrictions based on the context in which data is accessed and how the data is used. Enforcing these restrictions automatically presents significant challenges, as the information needed to determine context requires a tight coupling between policy enforcement and an application's implementation. We present Estrela, a framework for enforcing contextual and granular data access policies. Working from the observation that API endpoints can be associated with salient contextual information in most database-backed applications, Estrela allows developers to specify API-specific restrictions on data access and use. Estrela provides a clean separation between policy specification and the application's implementation, which facilitates easier auditing and maintenance of policies. Policies in Estrela consist of pre-evaluation and post-evaluation conditions, which provide the means to modulate database access before a query is issued, and to impose finer-grained constraints on information release after the evaluation of query, respectively. We build a prototype of Estrela and apply it to retrofit several real world applications (from 1000-80k LOC) to enforce different contextual policies. Our evaluation shows that Estrela can enforce policies with minimal overheads.