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SentinelSuperProAutomaticProtectionv640Safenet

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: 2026-08-26T11:00:00Z · Confidence: medium

Hunt Hypothesis

This detection identifies potential SafeNet Sentinel SuperPro endpoint protection activities that may indicate an adversary attempting to evade security controls or establish persistence through automated defense mechanisms. SOC teams should proactively hunt for these signals in Azure Sentinel to distinguish between legitimate software updates and anomalous behaviors where attackers mimic trusted security processes to mask malicious operations.

YARA Rule

rule SentinelSuperProAutomaticProtectionv640Safenet
{
      meta:
		author="malware-lu"
strings:
		$a0 = { 68 [4] 6A 01 6A 00 FF 15 [4] A3 [4] FF 15 [4] 33 C9 3D B7 00 00 00 A1 [4] 0F 94 C1 85 C0 89 0D [4] 0F 85 [4] 55 56 C7 05 [4] 01 00 00 00 FF 15 [4] 01 05 [4] FF 15 }

condition:
		$a0 at pe.entry_point
}

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 5 specific false positive scenarios for the SentinelSuperProAutomaticProtectionv640Safenet detection rule, along with recommended filters and exclusions:

Original source: https://github.com/Yara-Rules/rules/blob/main/packers/packer.yar