  Cloud computing services provide scalable and cost-effective solutions for
data storage, processing, and collaboration. Alongside their growing
popularity, concerns related to their security vulnerabilities leading to data
breaches and sophisticated attacks such as ransomware are growing. To address
these, first, we propose a generic framework to express relations between
different cloud objects such as users, datastores, security roles, to model
access control policies in cloud systems. Access control misconfigurations are
often the primary driver for cloud attacks. Second, we develop a PDDL model for
detecting security vulnerabilities which can for example lead to widespread
attacks such as ransomware, sensitive data exfiltration among others. A planner
can then generate attacks to identify such vulnerabilities in the cloud.
Finally, we test our approach on 14 real Amazon AWS cloud configurations of
different commercial organizations. Our system can identify a broad range of
security vulnerabilities, which state-of-the-art industry tools cannot detect.
