Unmasking the Shapeshifter: Threat Hunting for BianLian Malware

As cyber threats continue to evolve, so do the tactics of malware authors. One such advanced and shapeshifting malware is BianLian, which has gained notoriety for its ability to morph its code to evade detection. As organizations face an ever-growing threat landscape, proactive threat hunting is crucial to identify and neutralize BianLian before it inflicts irreparable damage. In this blog, we will delve into the realm of threat hunting for BianLian malware, featuring real-world examples, Splunk queries, and YARA rules to help organizations strengthen their defenses against this elusive adversary.

BianLian is a polymorphic malware known for its ever-changing code, making it challenging for traditional signature-based detection systems to identify. It often spreads through malicious email attachments, drive-by downloads, or compromised websites. Once inside a network, BianLian can perform a wide range of malicious activities, from stealing sensitive data to launching DDoS attacks.

Let’s explore practical threat hunting examples to detect and respond to BianLian malware:

Example 1: Anomalous Outbound Network Traffic
Hunt for unusual patterns of outbound network traffic.

index=network earliest=-1d | stats count by dest_ip

Investigate any significant spikes in outbound connections to unknown or suspicious IP addresses.

Example 2: Suspicious Process Behaviors
Monitor endpoint activity for abnormal process behaviors, such as unexpected process launches.

index=main sourcetype=”WinEventLog:Microsoft-Windows-Sysmon/Operational” EventCode=1 earliest=-1w

Look for processes attempting to execute from unusual locations or those modifying a large number of files.

YARA rules provide a powerful way to create custom signatures for detecting BianLian malware. Let’s create a YARA rule for BianLian:

rule BianLian_Malware {
meta:
description = “Detects BianLian malware files”
strings:
$magic = { 4D 5A } // MZ (DOS/Windows executable)
$pattern = “BianLian” // Unique string indicative of BianLian
condition:
$magic at 0 and $pattern
}

Leverage Splunk for endpoint and network monitoring to detect potential BianLian infections:

# Endpoint Activity Monitoring
index=main sourcetype=”WinEventLog:Microsoft-Windows-Security-Auditing” EventCode=4688
| search New_Process_Name=”*.exe” OR New_Process_Name=”*.dll”

# Network Activity Monitoring
index=network earliest=-1w
| rex field=_raw “Host=(?<dest_host>[^\s]+)”
| rex field=_raw “User_Agent=(?<user_agent>[^\s]+)”
| search dest_host=”*.onion” OR user_agent=”BianLian”

Threat hunting is a vital practice in identifying and neutralizing the shapeshifting BianLian malware. By utilizing Splunk queries and YARA rules, organizations can enhance their detection capabilities, identify suspicious activities, and respond swiftly to BianLian attacks. Continuous monitoring and collaboration with the cybersecurity community are essential to stay ahead of BianLian’s rapidly changing tactics. Implementing these strategies will fortify your organization’s cybersecurity defenses, ensuring resilience against BianLian and other sophisticated malware strains. Remember, a vigilant and proactive approach to threat hunting is the key to unmasking the shapeshifter and safeguarding your network from harm. Happy hunting!

(Note: The examples provided in this blog are intended for illustrative purposes only and may require customization based on the specific environment and requirements of individual organizations.)