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TangoAlfa

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: 2026-07-07T11:00:00Z · Confidence: medium

Hunt Hypothesis

This detection identifies potential adversary activity characterized by specific file patterns defined by the TangoAlfa YARA signature, which may indicate early-stage reconnaissance or benign tooling often missed by high-severity alerts. Proactively hunting for this behavior in Azure Sentinel allows the SOC team to validate these low-fidelity signals against baseline operations, ensuring that subtle indicators of compromise are not overlooked before they escalate into significant incidents.

YARA Rule

rule TangoAlfa
{
	meta:
		copyright = "2015 Novetta Solutions"
		author = "Novetta Threat Research & Interdiction Group - [email protected]"

	strings:
		// $firewall is a shared code string
		$firewall = "%sd.e%sc n%ssh%srewa%s ad%s po%sop%sing T%s %d \"%s\""
		
		$testStatus1 = "*****[Start Test -> %s:%d]" wide
		$testStatus2 = "*****[Relay Connect " wide
		$testStatus3 = "*****[Listen Port %d] - " wide
		$testStatus4 = "*****[Error Socket]" wide
		$testStatus5 = "*****[End Test]" wide

	condition:
		2 of them
}

Deployment Notes

This YARA rule can be deployed in the following contexts:

This rule contains 6 string patterns in its detection logic.

False Positive Guidance

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

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