← Back to SOC feed Coverage →

HotelAlfa

yara LOW Yara-Rules
community
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: 2026-07-04T11:00:00Z · Confidence: medium

Hunt Hypothesis

This detection targets adversary behavior associated with the HotelAlfa malware family, specifically identifying its unique code signatures within endpoint processes to uncover potential initial footholds or lateral movement activities. Proactively hunting for this indicator in Azure Sentinel is critical because early identification of these low-severity artifacts allows the SOC team to correlate them with broader threat intelligence before they escalate into significant data exfiltration incidents.

YARA Rule

rule HotelAlfa
{
	meta:
		copyright = "2015 Novetta Solutions"
		author = "Novetta Threat Research & Interdiction Group - trig@novetta.com"
		Source = "58dab205ecb1e0972027eb92f68cec6d208e5ab5.ex_"

	strings:
	
	$resourceHTML = "RSRC_HTML"
	/*
		8A 0C 18  mov     cl, [eax+ebx]
		80 F1 63  xor     cl, 63h
		88 0C 18  mov     [eax+ebx], cl
		8B 4D 00  mov     ecx, [ebp+0]
		40        inc     eax
		3B C1     cmp     eax, ecx
		72 EF     jb      short loc_4010B4
	*/

	$rscsDecoderLoop = {8A [2] 80 F1 ?? 88 [2] 8B [2] 40 3B ?? 72 EF}

	condition:
		$resourceHTML and $rscsDecoderLoop in ((pe.sections[pe.section_index(".text")].raw_data_offset)..(pe.sections[pe.section_index(".text")].raw_data_offset + pe.sections[pe.section_index(".text")].raw_data_size))
}

Deployment Notes

This YARA rule can be deployed in the following contexts:

This rule contains 2 string patterns in its detection logic.

False Positive Guidance

Here are 5 specific false positive scenarios for the HotelAlfa detection rule in an enterprise environment, including suggested filters and exclusions:

Original source: https://github.com/Yara-Rules/rules/blob/main/malware/Operation_Blockbuster/HotelAlfa.yara