MIC: Memory analysis of IndexedDB data on Chromium-based applications

As Chromium-based applications continue to gain popularity, it is necessary for forensic investigators to obtain a comprehensive understanding of how they store and manage browsing artifacts from both filesystem and memory perspectives. In particular, the incognito mode developed in the current version of Chromium uses only physical memory to manage data related to active sessions. Therefore, handling physical memory is essential for tracking a user’s browsing behaviour in incognito mode. This paper provides an in-depth examination of Lev- elDB, a lightweight key-value database utilized as Chromium’s implementation for IndexedDB. In particular, we delve into the details of how IndexedDB data is managed through LevelDB, taking into account its low-level database file format. Furthermore, we thoroughly explore the possibility of residual data, both complete and incomplete, being retained as applications create and initialize IndexedDB-related data. Based on our research findings, we propose a systematic methodology for inspecting the internal structures of LevelDB-related C++ classes, carving these structures from binary streams, and interpreting the data for forensic analysis. In addition, we develop a proof-of-concept tool based on our approach and demonstrate its performance and effectiveness through case studies.