Most of us understand that digital evidence is fragile. What we often underestimate is how fast it gets contaminated, not by attackers, not by accidents, but by the operating system we trusted to run the investigation. The moment you connect a suspect’s hard drive to a Windows or Linux machine; the OS gets to work. It scans file structures, updates last-accessed timestamps, writes indexing records, and logs device activity all in the background, silently, before you’ve even o

In our earlier blogs, we walked through memory forensics with FTK and its role in analyzing volatile data, learned how Autopsy recovers deleted evidence, and also looked at the digital forensics and anti-forensics . Each of these gave us a piece of the bigger puzzle. [ Previous blogs collection: Forensics ] Today, we’ll see how Large Language Models (LLMs) are used or can be used in the landscape of digital forensics. From easing investigation workflows to supporting analys

Hey Everyone! Just like our previous dive into purple teaming, this blog lays the groundwork for understanding both sides of the digital forensics coin: the techniques used to uncover evidence and the tricks used to hide it. What is Digital Forensic? Digital forensics involves collecting, preserving, analyzing, and presenting digital evidence in a legally admissible manner. This evidence can come from various sources, including computers, servers, mobile devices, emails, soci