Inferring and securing software configurations using automated reasoning

Abstract

Software configurability opens the door to misconfiguration vulnerabilities, invalid settings that expose software weaknesses. Misconfiguration is one the top ten most critical security risks and the most common. This paper envisions a world without misconfiguration vulnerabilities through the use of automated reasoning techniques to infer and secure software configurations. Real-world software, however, often lacks an explicit specification of secure configurations, relying on hand-validation by users. Real-world systems comprise many individual highly-configurable software components, making the space of possible configurations for the whole system enormous. To realize our vision and overcome these challenges, we aim to create a rigorous definition of configuration specifications, use formal methods to mechanize the inference and generation of valid configurations, and develop algorithms to automatically secure against misconfiguration.