After completing Redline, I moved on to KAPE and quickly realised how powerful it is for automating the DFIR workflow we practised in Windows Forensics 1 and 2. It also helped me understand how individual forensic utilities can be chained together for faster, consistent triage and analysis (e.g. EZViewer).
Learning KAPE's Structure
I discovered that KAPE's targets and modules work together, with .tkape files defining what to collect and .mkape files determining how to process that data. Understanding the use of variables like %d for timestamps and %m for machine names gave me insight into how KAPE organises forensic data efficiently.
Hands-On Experience
Using both the GUI (gkape.exe) and CLI (kape.exe) deepened my appreciation for automation in forensics. The ability to gather key Windows artefacts, registry hives, and logs with KapeTriage and then process them using the EZParser module streamlined tasks that would otherwise require multiple manual tools. Although the processing time was long, the workflow was intuitive once I understood the logic behind targets and modules.
Challenges and Insights
Some hands-on tasks were tricky, especially identifying software installations from network drives, but they forced me to think critically about artefact locations and data correlation. I learned how to use EZViewer effectively for exploring CSV outputs and realised how KAPE works perfectly with Zimmerman's ecosystem for a complete forensic workflow.
Reflection
This lab reinforced the importance of automation in DFIR and gave me practical exposure to modular forensic collection. While some steps were frustrating, especially without hints, the process taught me how to think like a forensic investigator, methodically, patiently, and with a focus on evidence correlation. I now feel more confident using KAPE to automate and speed up forensic analysis in real investigations.