StreamDivert: Relaying (specific) network connections

Author: Jelle Vergeer The first part of this blog will be the story of how this tool found its way into existence, the problems we faced and the thought process followed. The second part will be a more technical deep dive into the tool itself, how to use it, and how it works. Storytime About … Continue reading StreamDivert: Relaying (specific) network connections

Machine learning from idea to reality: a PowerShell case study

Detecting both ‘offensive’ and obfuscated PowerShell scripts in Splunk using Windows Event Log 4104 Author: Joost Jansen This blog provides a ‘look behind the scenes’ at the RIFT Data Science team and describes the process of moving from the need or an idea for research towards models that can be used in practice. More specifically, … Continue reading Machine learning from idea to reality: a PowerShell case study

A Second Look at CVE-2019-19781 (Citrix NetScaler / ADC)

Authors: Rich Warren of NCC Group FSAS & Yun Zheng Hu of Fox-IT, in close collaboration with Fox-IT’s RIFT. About the Research and Intelligence Fusion Team (RIFT): RIFT leverages our strategic analysis, data science, and threat hunting capabilities to create actionable threat intelligence, ranging from IOCs and detection capabilities to strategic reports on tomorrow’s threat … Continue reading A Second Look at CVE-2019-19781 (Citrix NetScaler / ADC)

WastedLocker: A New Ransomware Variant Developed By The Evil Corp Group

Authors: Nikolaos Pantazopoulos, Stefano Antenucci (@Antelox) Michael Sandee and in close collaboration with NCC’s RIFT. About the Research and Intelligence Fusion Team (RIFT):RIFT leverages our strategic analysis, data science, and threat hunting capabilities to create actionable threat intelligence, ranging from IOCs and detection capabilities to strategic reports on tomorrow's threat landscape. Cyber security is an … Continue reading WastedLocker: A New Ransomware Variant Developed By The Evil Corp Group

In-depth analysis of the new Team9 malware family

Author: Nikolaos Pantazopoulos Co-author: Stefano Antenucci (@Antelox) And in close collaboration with NCC's RIFT. 1. Introduction Publicly discovered in late April 2020, the Team9 malware family (also known as ‘Bazar [1]’) appears to be a new malware being developed by the group behind Trickbot. Even though the development of the malware appears to be recent, … Continue reading In-depth analysis of the new Team9 malware family

LDAPFragger: Command and Control over LDAP attributes

Written by Rindert Kramer Introduction A while back during a penetration test of an internal network, we encountered physically segmented networks. These networks contained workstations joined to the same Active Directory domain, however only one network segment could connect to the internet. To control workstations in both segments remotely with Cobalt Strike, we built a … Continue reading LDAPFragger: Command and Control over LDAP attributes

Detecting random filenames using (un)supervised machine learning

Combining both n-grams and random forest models to detect malicious activity. Author: Haroen Bashir An essential part of Managed Detection and Response at Fox-IT is the Security Operations Center. This is our frontline for detecting and analyzing possible threats. Our Security Operations Center brings together the best in human and machine analysis and we continually … Continue reading Detecting random filenames using (un)supervised machine learning

Office 365: prone to security breaches?

Author: Willem Zeeman "Office 365 again?". At the Forensics and Incident Response department of Fox-IT, this is heard often.  Office 365 breach investigations are common at our department. You’ll find that this blog post actually doesn’t make a case for Office 365 being inherently insecure – rather, it discusses some of the predictability of Office … Continue reading Office 365: prone to security breaches?

Using Anomaly Detection to find malicious domains

Applying unsupervised machine learning to find ‘randomly generated domains. Authors: Ruud van Luijk and Anne Postma At Fox-IT we perform a variety of research and investigation projects to detect malicious activity to improve the service of  our Security Operations Center. One of these areas is applying data science techniques to real world data in real … Continue reading Using Anomaly Detection to find malicious domains