Backbone’s Steganography Application Fingerprint Database v3.11 released

Backbone Security has announced the release of Version 3.11 of the Steganography Application Fingerprint Database (SAFDB) which now contains 1,000 steganography applications…Developed in Backbone’s Steganography Analysis and Research Center (SARC), SAFDB is the world’s largest commercially available hash set exclusive to digital steganography applications.

The database is widely used by US and international government and law enforcement agencies, the intelligence community, and private sector digital forensic examiners and network security professionals to detect digital steganography applications on seized digital media or within inbound and outbound network traffic streams.

Discovery of a steganography application during a digital forensics examination is a strong indication the application has been, or will be, used to conceal evidence of criminal activity. Detecting a steganography application in the inbound network traffic stream is a strong indication an insider will use the application to steal sensitive information.

SAFDB is an integral part of the Steganography Analyzer Artifact Scanner (StegAlyzerAS), a digital forensics application, and the Steganography Analyzer Real-Time Scanner (StegAlyzerRTS), a network security appliance that detects the presence or use of steganography in the inbound and outbound network traffic stream in real-time.

Get The Latest DFIR News!

Top DFIR articles in your inbox every month.


Unsubscribe any time. We respect your privacy - read our privacy policy.

Existing customers may download an updated version of StegAlyzerAS and StegAlyzerRTS that contains SAFDB v3.11 by logging into their account on the SARC Customer Portal at http://www.sarc-wv.com/customer_portal/.

For additional information about Backbone’s steganalysis tools, please visit the SARC web site or send email to [email protected]

Leave a Comment

Latest Videos

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

This error message is only visible to WordPress admins

Important: No API Key Entered.

Many features are not available without adding an API Key. Please go to the YouTube Feed settings page to add an API key after following these instructions.

Latest Articles

Share to...