This YARA rule detects the presence of a specific malicious binary or script signature, indicating potential unauthorized code execution or fileless malware activity on endpoints. Proactively hunting for this signature in Azure Sentinel allows the SOC team to identify low-severity threats that may serve as initial access vectors or persistence mechanisms before they escalate into more impactful compromises.
rule VxUddy2617
{
meta:
author="malware-lu"
strings:
$a0 = { 2E [5] 2E [5] 2E [3] 8C C8 8E D8 8C [3] 2B [3] 03 [3] A3 [2] A1 [2] A3 [2] A1 [2] A3 [2] 8C C8 2B [3] 03 [3] A3 [2] B8 AB 9C CD 2F 3D 76 98 }
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 developer or system administrator uses a custom Python script to perform bulk file renaming or metadata stripping on a large directory of log files or media assets. The script likely uses os.rename or shutil.move in a tight loop, generating a high volume of Rename events that match the YARA rule’s threshold for rapid file operations.
python.exe or python3.exe and the command line contains arguments like --batch, --rename, or specific script names (e.g., cleanup_logs.py). Alternatively, exclude if the source and destination paths are within the same volume and the operation count is below a higher threshold (e.g., < 500 renames per minute).Scenario: An enterprise backup solution (e.g., Veeam, Commvault, or Rubrik) performs a “deduplication” or “rehydration” task that involves moving temporary chunk files from a staging area to the final repository. This process often triggers a burst of file move/rename events as data blocks are reassembled.
veeam.exe, commvault.exe, rubik-agent.exe) or where the source path contains keywords like \temp\, \staging\, or \dedup\.Scenario: A CI/CD pipeline agent (e.g., Jenkins, GitLab Runner, or Azure DevOps) executes a build step that involves cleaning up workspace artifacts. The clean or purge command often deletes or moves thousands of small build artifacts (JARs, DLLs, logs) in rapid succession, triggering the detection logic for high-frequency file modifications.