Introducing Griffeye Analyze DI For Visual Media Investigations

Approximately 200 people joined our “Griffeye 101: A crash course in visual media investigations” webinar to learn how Griffeye Analyze DI Pro can help speed through cases involving massive amounts of pictures and videos.We covered how to process vast amounts of multimedia data collected from multiple sources and forensic tools with pre-categorization, detect critical clues through automated routines and visual navigation, identify relationships between files based on their EXIF, the basics of “Fuzzy hashing,” photo matching in the absence of EXIF data, and object recognition in videos. Thank you to all who attended!

If you weren’t able to join, you can still catch the replay here!

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Quantifying Data Volatility for IoT Forensics With Examples From Contiki OS

Forensic Focus 22nd June 2022 5:00 am

File timestamps are used by forensics practitioners as a fundamental artifact. For example, the creation of user files can show traces of user activity, while system files, like configuration and log files, typically reveal when a program was run. 

Despite timestamps being ubiquitous, the understanding of their exact meaning is mostly overlooked in favor of fully-automated, correlation-based approaches. Existing work for practitioners aims at understanding Windows and is not directly applicable to Unix-like systems. 

In this paper, we review how each layer of the software stack (kernel, file system, libraries, application) influences MACB timestamps on Unix systems such as Linux, OpenBSD, FreeBSD and macOS.

We examine how POSIX specifies the timestamp behavior and propose a framework for automatically profiling OS kernels, user mode libraries and applications, including compliance checks against POSIX.

Our implementation covers four different operating systems, the GIO and Qt library, as well as several user mode applications and is released as open-source.

Based on 187 compliance tests and automated profiling covering common file operations, we found multiple unexpected and non-compliant behaviors, both on common operations and in edge cases.

Furthermore, we provide tables summarizing timestamp behavior aimed to be used by practitioners as a quick-reference.

Learn more: https://dfrws.org/presentation/a-systematic-approach-to-understanding-macb-timestamps-on-unixlike-systems/

File timestamps are used by forensics practitioners as a fundamental artifact. For example, the creation of user files can show traces of user activity, while system files, like configuration and log files, typically reveal when a program was run.

Despite timestamps being ubiquitous, the understanding of their exact meaning is mostly overlooked in favor of fully-automated, correlation-based approaches. Existing work for practitioners aims at understanding Windows and is not directly applicable to Unix-like systems.

In this paper, we review how each layer of the software stack (kernel, file system, libraries, application) influences MACB timestamps on Unix systems such as Linux, OpenBSD, FreeBSD and macOS.

We examine how POSIX specifies the timestamp behavior and propose a framework for automatically profiling OS kernels, user mode libraries and applications, including compliance checks against POSIX.

Our implementation covers four different operating systems, the GIO and Qt library, as well as several user mode applications and is released as open-source.

Based on 187 compliance tests and automated profiling covering common file operations, we found multiple unexpected and non-compliant behaviors, both on common operations and in edge cases.

Furthermore, we provide tables summarizing timestamp behavior aimed to be used by practitioners as a quick-reference.

Learn more: https://dfrws.org/presentation/a-systematic-approach-to-understanding-macb-timestamps-on-unixlike-systems/

YouTube Video UCQajlJPesqmyWJDN52AZI4Q_i0zd7HtluzY

A Systematic Approach to Understanding MACB Timestamps on Unixlike Systems

Forensic Focus 21st June 2022 5:00 am

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