Analyzing Identity and Access Management (IAM) Misconfigurations in Cloud Databases

Enterprises are more inclined towards cloud adaptation for services including cloud databases, but there is persistent concern about data security. One of the major data security vulnerabilities arises from misconfigurations in authorization and authentication mechanisms of data management system. Identity and Access Management (IAM) serves as a general framework for security configuration in cloud database services, yet its manual and static policy administration results in misconfigurations, which include excessive rights, policy drift, illegal access, and so on. Thus, comprehensive reporting and a deeper understanding of the efficacy of alternative IAM security procedures in reducing security risks are needed. This study adopts a systematic process that looks at common IAM misconfiguration patterns in cloud database systems and examines relevant studies published between 2016 and 2026 to assess the effectiveness of automated IAM configurations. The literature advocates that manual IAM configurations significantly contribute to privilege escalation and security violations in cloud database services, whereas automated IAM approaches provide stronger protection through continuous enforcement, real-time monitoring, and improved visibility into access behaviors. Furthermore, the study identifies critical research gaps in real-time remediation and DBaaS-aware automation, which are necessary to mitigate security risks faced by enterprises, reduce IAM-related vulnerabilities, and enhance confidence in adopting cloud database services.