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Cerber5

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: 2026-07-10T23:00:00Z · Confidence: medium

Hunt Hypothesis

This detection rule identifies anomalous authentication patterns associated with the Cerber5 adversary behavior, which may indicate early-stage reconnaissance or lateral movement attempts within the Azure environment. Proactively hunting for this signal is critical to validate potential false negatives in existing alerting logic and ensure that low-severity indicators are not overlooked before they escalate into significant security incidents.

YARA Rule

rule cerber5{
meta:
  author = "pekeinfo"
  date = "2016-12-02"
  description = "Cerber5"
strings:
  $a = {83 C4 04 A3 ?? ?? ?? 00 C7 45 ?? ?? ?? ?? 00 8B ?? ?? C6 0? 56 8B ?? ?? 5? 68 ?? ?? 4? 00 FF 15 ?? ?? 4? 00 50 FF 15 ?? ?? 4? 00 A3 ?? ?? 4? 00 68 1D 10 00 00 E8 ?? ?? FF FF 83 C4 04 ?? ?? ??}
  
condition:
  1 of them 
}

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 4 specific false positive scenarios for the Cerber5 detection rule in an enterprise environment, including recommended filters and exclusions:

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