Malware targeting Linux-based operating systems, commonly deployed in Internet of Things (IoT) devices, have increased by 35% in 2021 compared to 2020, according to current CrowdStrike threat telemetry, with the top three malware families accounting for 22% of all Linux-based IoT malware in 2021.
Microsoft recently published two critical CVEs related to Active Directory (CVE-2021-42278 and CVE-2021-42287), which when combined by a malicious actor could lead to privilege escalation with a direct path to a compromised domain. In mid-December 2021, a public exploit that combined these two Microsoft Active Directory design flaws (referred also as “noPac”) was released.
During a recent client engagement for a tabletop exercise (TTX), it became apparent that the client did not have a methodology for tracking indicators and building an incident timeline. The CrowdStrike Services team wanted to provide more information to our client on how incidents can and should be tracked, but nothing was available in the public domain.
The TellYouThePass ransomware family was recently reported as a post-exploitation malicious payload used in conjunction with a remote code execution vulnerability in Apache Log4j library, dubbed Log4Shell. TellYouThePass was first reported in early 2019 as a financially motivated ransomware designed to encrypt files and demand payment for restoring them. Targeting both Windows and Linux systems, TellYouThePass ransomware re-emerged in mid-December 2021 along with other ransomware like Khonsari.
It should come as little surprise that when enterprise and IT leaders turned their attention to the cloud, so did attackers. Unfortunately, the security capabilities of enterprises have not always kept up with the threat landscape. Poor visibility, management challenges and misconfigurations combine with other security and compliance issues to make protecting cloud environments a complex endeavor.
Following the Dec. 9, 2021, announcement of the Log4j vulnerability, CVE 2021-44228, CrowdStrike Falcon OverWatch™ has provided customers with unrivaled protection and 24/7/365 vigilance in the face of heightened uncertainty. To OverWatch, Log4Shell is simply the latest vulnerability to exploit — a new access vector among a sea of many others.
CrowdStrike’s goal is to stop breaches — and we do that better than any cybersecurity company in the world. As attackers advance their tactics and techniques, we continually refine our tools and capabilities to stay ahead of them. We recently added a new feature to the CrowdStrike Falcon® sensor: Hardware Enhanced Exploit Detection, which uses hardware capabilities to detect complex attack techniques that are notoriously hard for software alone to detect and prevent.
Note: This post first appeared in r/CrowdStrike. First and foremost: if you’re reading this post, I hope you’re doing well and have been able to achieve some semblance of balance between life and work. It has been, I think we can all agree, a wild December in cybersecurity (again). At this time, it’s very likely that you and your team are in the throes of hunting, assessing and patching implementations of Log4j2 in your environment.
The recently discovered Log4j vulnerability has serious potential to expose organizations across the globe to a new wave of cybersecurity risks as threat actors look to exploit this latest vulnerability to execute their malicious payloads using remote code execution (RCE). An immediate challenge that every organization faces is simply trying to understand exactly where you have applications that are using this very popular Java library — but you are not facing this challenge alone.
Threat hunters and incident responders are under tremendous time pressure to investigate breaches and incidents. While they are collecting and sorting massive quantities of forensic data, fast response is critical to help limit any damage inflected by the adversary. This article and video will provide an overview of Falcon Forensics, and how it streamlines the collection and analysis of point-in-time and historic forensic data.
