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LimaBravo

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 identifies the execution of specific malicious code patterns defined by the LimaBravo YARA signature, which may indicate early-stage adversary activity or benign anomalies within the environment. Proactive hunting for this rule in Azure Sentinel is recommended to validate its relevance against current threat landscapes and refine alert tuning before escalating low-severity findings into confirmed incidents.

YARA Rule

rule LimaBravo
{
	meta:
		copyright = "2015 Novetta Solutions"
		author = "Novetta Threat Research & Interdiction Group - [email protected]"
		Source = "Mwsagent.dll"

	strings:
	/*
		83 C4 34        add     esp, 34h
		83 FD 0A        cmp     ebp, 0Ah
		5D              pop     ebp
		5B              pop     ebx
		7E 12           jle     short loc_1000106F
		57              push    edi             ; Src
		C6 07 4D        mov     byte ptr [edi], 4Dh
		C6 47 01 5A     mov     byte ptr [edi+1], 5Ah
		E8 97 01 00 00  call    ManualImageLoad
	*/

	$a = {83 ?? 34 83 ?? 0A [0-2] 7E ?? 5? C6 ?? 4D C6 [2] 5A E8}

	condition:
		$a 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 1 string patterns in its detection logic.

False Positive Guidance

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

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