Avoiding Excessive Data Exposure Through Microservice APIs

Abstract

Data transfer and exchange of information through APIs are essential for each microservice architecture. Since these transfers often include private or sensitive data, potential data leaks, either accidentally or through malicious attacks, provide a high-security risk. While there are different techniques, like using data encryption or authentication protocols to secure the data exchange, only a few strategies are known to reduce the damage when an actual data breach happens. Our work presents a novel approach to identifying the optimal amount of data attributes that need to be exchanged between APIs and minimizes the damage in case of a potential breach. Our method relies only on static source code analysis and easy-to-calculate architectural metrics, making it well suited to be used in continuous integration and deployment processes. We further verified and validated the feasibility of our approach by conducting two case studies on open-source microservice systems.