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Sakula v1.1

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: 2026-07-14T11:00:00Z · Confidence: medium

Hunt Hypothesis

This hypothesis posits that adversaries are executing initial reconnaissance or lateral movement activities characterized by the specific behavioral patterns defined in the Sakula v1.1 rule. Proactively hunting for these indicators within Azure Sentinel is essential to identify subtle, low-severity anomalies before they escalate into significant security incidents.

YARA Rule

rule sakula_v1_1: RAT
{
    meta:
        description = "Sakula v1.1"
        date = "2015-10-13"
        author = "Airbus Defence and Space Cybersecurity CSIRT - Yoann Francou"
    strings:
        $m1 = "%d_of_%d_for_%s_on_%s"
        $m2 = "/c ping 127.0.0.1 & del /q \"%s\""
        $m3 = "=%s&type=%d"
        $m4 = "?photoid="
        $m5 = "iexplorer"
                $m6 = "net start \"%s\""
        $v1_1 = "MicroPlayerUpdate.exe"
        $MZ = "MZ"
    condition:
        $MZ at 0 and 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 Sakula v1.1 detection rule in an enterprise environment, including suggested filters and exclusions:

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