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Sakula v1.3

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 detection rule identifies potential lateral movement or reconnaissance activities associated with the Sakula v1.3 framework by monitoring specific low-severity telemetry patterns within Azure Sentinel. Proactively hunting for this behavior allows the SOC team to establish a baseline of normal operations and detect subtle deviations that may indicate early-stage adversary presence before they escalate into high-impact incidents.

YARA Rule

rule sakula_v1_3: RAT
{
    meta:
        description = "Sakula v1.3"
        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 = "cmd.exe /c rundll32 \"%s\""

        $v1_3 = { 81 3E 78 03 00 00 75 57  8D 54 24 14 52 68 0C 05 41 00 68 01 00 00 80 FF  15 00 F0 40 00 85 C0 74 10 8B 44 24 14 68 2C 31  41 00 50 FF 15 10 F0 40 00 8B 4C 24 14 51 FF 15  24 F0 40 00 E8 0F 09 00 }

        $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 5 string patterns in its detection logic.

False Positive Guidance

Here are 5 specific false positive scenarios for the Sakula v1.3 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