This rule detects the presence of specific file signatures associated with the FSGv133 YARA pattern, which may indicate the deployment of a low-severity tool or script used for initial access or data staging. Proactively hunting for this signature allows the SOC team to identify dormant or overlooked artifacts in the Azure Sentinel environment before they are leveraged for further lateral movement or privilege escalation.
rule FSGv133
{
meta:
author="malware-lu"
strings:
$a0 = { BE A4 01 40 00 AD 93 AD 97 AD 56 96 B2 80 A4 B6 80 FF 13 73 }
condition:
$a0 at pe.entry_point
}
This YARA rule can be deployed in the following contexts:
This rule contains 1 string patterns in its detection logic.
Scenario: A security team or DevOps engineer runs a YARA scanner (e.g., yara CLI, YARA-Lib, or a commercial tool like ClamAV with YARA support) against a large directory of application binaries or configuration files to verify known good signatures. The scanner process itself loads the YARA rule file (containing the string “FSGv133”) into memory or reads it from disk, triggering the detection.
yara.exe, yara64.exe, clamscan.exe) or where the file path matches common YARA rule directories (e.g., C:\YaraRules\, C:\SecurityTools\yara\).Scenario: An IT administrator performs a manual audit or backup of the security detection rule repository. They open the YARA rule file FSGv133.yar in a text editor (e.g., Notepad++, VS Code, Sublime Text) or copy it to a shared network drive for documentation purposes. The file content contains the literal string “FSGv133”, triggering the rule if it scans file contents or memory.
.yar or .yara and the parent process is a text editor or file management tool (e.g., notepad++.exe, code.exe, explorer.exe). Additionally, exclude paths under C:\SecurityRules\ or \\fileserver\security\yara\.Scenario: A CI/CD pipeline or scheduled job (e.g., via Task Scheduler or cron) executes a script that validates YARA rules before deployment. The script uses a Python library like