Abstract

As technology evolves, so does the threat of cyberattacks – making Digital Forensics crucial for damage control and prevention. This paper aims to address the inefficiencies faced by investigators in a forensic setting by automating the processes necessary for disk and memory image acquisition, forensic artifact parsing, and timeline generation. Leveraging publicly available tools such as: WinPmem, FTK Imager, Volatility 3 (VOL3), and The Sleuth Kit (TSK), the developed Python script is then able to provide for a clearer insight into the series of events that have transpired during a cyber incident through the generation of detailed and cohesively organized timelines, then using the Timsort algorithm for timeline analysis.

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