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detect Lokibot in memory

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: 2026-07-03T11:00:00Z · Confidence: medium

Hunt Hypothesis

This detection rule identifies the presence of Lokibot malware within system memory, signaling potential lateral movement or data exfiltration activities by an adversary. Proactively hunting for this behavior in Azure Sentinel is critical to validate initial alerts and uncover dormant threats that may have evaded standard signature-based defenses.

YARA Rule

rule Lokibot {
          meta:
            description = "detect Lokibot in memory"
            author = "JPCERT/CC Incident Response Group"
            rule_usage = "memory scan"
            reference = "internal research"
            hash1 = "6f12da360ee637a8eb075fb314e002e3833b52b155ad550811ee698b49f37e8c"

          strings:
            $des3 = { 68 03 66 00 00 }
            $param = "MAC=%02X%02X%02XINSTALL=%08X%08X"
            $string = { 2d 00 75 00 00 00 46 75 63 6b 61 76 2e 72 75 00 00}

          condition: all of them
}

Deployment Notes

This YARA rule can be deployed in the following contexts:

This rule contains 3 string patterns in its detection logic.

References

False Positive Guidance

Here are 5 specific false positive scenarios for the “detect Lokibot in memory” rule within an enterprise environment, along with suggested filters or exclusions:

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