In order to guarantee the confidentiality of sensitive information in software systems, strong mechanisms for identifying probable security violations are required. Language-oriented information flow analysis can be a strong mechanism that identifies vulnerabilities resulting from insecure coding techniques, especially web-based applications. To address this issue, we introduce a dependency graph-based framework to identify potential confidentiality violations present in source code. The examination of dependencies is important in a number of software engineering tasks, such as debugging, code optimization, support for component reuse, improving code readability, and, most importantly, protecting information flow. Traditional methods of dependency information extraction are not always precise enough to provide sound security assessments. To counter this limitation, we enhance the analysis process by considering both Direct and Indirect Dependencies. The improved method enables more thorough and precise mapping of dependencies, thus making security assessments more reliable. We validate our method through mathematical proofs. To systematically detect unauthorized information flows, we utilize propositional logic-based formulations corresponding to predetermined security-level constraints. Our research aims to bridge the gap between the existing requirements of secure software development processes and the analytical approaches that are now accessible by utilising this refined approach.