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PoetRat Doc

yara LOW Yara-Rules
backdoorcommunity
This rule was pulled from an open-source repository and enriched with AI. Validate in a test environment before deploying to production.
View original rule at Yara-Rules →
Retrieved: 2026-07-13T23:00:01Z · Confidence: medium

Hunt Hypothesis

This detection targets adversaries leveraging the PoetRat malware to execute malicious payloads within Microsoft Word documents, a common vector for initial access and lateral movement. Proactively hunting for this behavior in Azure Sentinel is critical because early identification of these low-severity document-based threats can prevent silent data exfiltration before it escalates into a significant incident.

YARA Rule

rule PoetRat_Doc
{
    meta:
        Author = "Nishan Maharjan"
        Description = "A yara rule to catch PoetRat Word Document"
        Data = "6th May 2020"
    strings:
        $pythonRegEx = /(\.py$|\.pyc$|\.pyd$|Python)/  // checking for python strings

        // Python file strings in the word documents
        $pythonFile1 = "launcher.py"
        $zipFile = "smile.zip"
        $pythonFile2 = "smile_funs.py"
        $pythonFile3 = "frown.py"
        $pythonFile4 = "backer.py"
        $pythonFile5 = "smile.py"
        $pythonFile6 = "affine.py" 

        // dlls and cmd strings
        $dlls = /\.dll/
        $cmd = "cmd"
        $exe = ".exe"   
    condition:
    all of them        
}

Deployment Notes

This YARA rule can be deployed in the following contexts:

This rule contains 11 string patterns in its detection logic.

False Positive Guidance

Here are 4 specific false positive scenarios for the PoetRat Doc detection rule in an enterprise environment, including suggested filters and exclusions:

Original source: https://github.com/Yara-Rules/rules/blob/main/malware/RAT_PoetRATDoc.yar