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Greame

yara LOW Yara-Rules
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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 adversary behavior involving the execution of the Greame malware family, which often establishes persistence through scheduled tasks and network communication to command-and-control servers. The SOC team should proactively hunt for this activity in Azure Sentinel because early identification of Greame’s low-severity indicators allows analysts to correlate with lateral movement patterns before the threat escalates into a critical incident.

YARA Rule

rule Greame : RAT
{
	meta:
		author = " Kevin Breen <[email protected]>"
		date = "2014/04"
		ref = "http://malwareconfig.com/stats/Greame"
		maltype = "Remote Access Trojan"
		filetype = "exe"
		
	strings:
    		$a = {23 23 23 23 40 23 23 23 23 E8 EE E9 F9 23 23 23 23 40 23 23 23 23}
            $b = {23 23 23 23 40 23 23 23 23 FA FD F0 EF F9 23 23 23 23 40 23 23 23 23}
            $c = "EditSvr"
            $d = "TLoader"
			$e = "Stroks"
            $f = "Avenger by NhT"
			$g = "####@####"
			$h = "GREAME"
			
    condition:
    		all of them
}

Deployment Notes

This YARA rule can be deployed in the following contexts:

This rule contains 8 string patterns in its detection logic.

False Positive Guidance

Here are 5 specific false positive scenarios for the Greame detection rule in an enterprise environment, along with suggested filters or exclusions:

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