This detection identifies potential malicious activity by analyzing original code signatures using the Hatman YARA rule to uncover known threat patterns within Azure Sentinel. Proactive hunting for this behavior is essential to validate the accuracy of low-severity alerts and ensure that subtle indicators of compromise are not overlooked before they escalate into larger incidents.
rule hatman_origcode : hatman {
meta:
id = "75acf3a2-0e9b-5280-8830-211c0f46737f"
strings:
$ocode_be = { 3c 00 00 03 60 00 a0 b0 7c 09 03 a6 4e 80 04 20 }
$ocode_le = { 03 00 00 3c b0 a0 00 60 a6 03 09 7c 20 04 80 4e }
condition:
$ocode_be or $ocode_le
}
This YARA rule can be deployed in the following contexts:
This rule contains 2 string patterns in its detection logic.
Here are 3-5 specific false positive scenarios for the hatman_origcode detection rule, including suggested filters and exclusions tailored for an enterprise environment:
Scenario: Automated Build Pipeline Execution
Jenkins, GitHub Actions Runner) and restrict detection to non-build directories (excluding paths like /var/lib/jenkins/workspace or C:\build\artifacts).Scenario: Scheduled Antivirus Definition Updates
origcode folder during scheduled maintenance windows.C:\Program Files\CrowdStrike\fsqa.exe, MsMpEng.exe) and limit rule triggering to business hours only, or exclude known update paths like C:\ProgramData\McAfee.Scenario: Enterprise Software Patching via Configuration Management
origcode hash that mimics a potential tampering event.