SierraJuliettMikeOne

Hunt Hypothesis

This hypothesis posits that adversaries are deploying specific malware signatures identified by the SierraJuliettMikeOne YARA rule to establish initial footholds within the Azure environment. Proactive hunting for this behavior is essential because its low severity classification may cause it to be overlooked in standard alerting, allowing stealthy reconnaissance or early-stage lateral movement to go undetected until a more significant incident occurs.

YARA Rule

rule SierraJuliettMikeOne
{
	meta:
		copyright = "2015 Novetta Solutions"
		author = "Novetta Threat Research & Interdiction Group - trig@novetta.com"

	strings:
		$commKey = { 10 20 30 40 50 60 70 80 90 11 12 13 1A FF EE 48 }
		/*
		.text:10001850                 push    7530h           ; dwTimeout
		.text:10001855                 lea     eax, [esp+420h+a2]
		.text:10001859                 push    4               ; len
		.text:1000185B                 push    eax             ; a2
		.text:1000185C                 push    esi             ; s
		.text:1000185D                 mov     dword ptr [esp+42Ch+a2], 1000h
		.text:10001865                 call    CommSendWithTimeout
		.text:1000186A                 add     esp, 14h
		.text:1000186D                 cmp     eax, 0FFFFFFFFh
		.text:10001870                 jz      loc_10001915
		.text:10001876                 lea     ecx, [esp+418h+random]
		.text:1000187A                 push    ecx             ; a1
		.text:1000187B                 call    Generate16ByteRandomBuffer
		.text:10001880                 push    0               ; fEncrypt
		.text:10001882                 push    7530h           ; dwTimeout		
		*/
		$handshake = { 68 30 75 00 00 [4] 6A 04 5? 5? C? [3] 00 10 00 00 E8 [7] 83 F8 FF 0F 84 ?? ?? 00 00 8? [3] 5? E8 [4] 6A 00 68 30 75 00 00 }
		
	condition:
		$commKey in ((pe.sections[pe.section_index(".data")].raw_data_offset)..(pe.sections[pe.section_index(".data")].raw_data_offset + pe.sections[pe.section_index(".data")].raw_data_size))
		and $handshake in ((pe.sections[pe.section_index(".text")].raw_data_offset)..(pe.sections[pe.section_index(".text")].raw_data_offset + pe.sections[pe.section_index(".text")].raw_data_size))

}

Deployment Notes

This YARA rule can be deployed in the following contexts:

• Microsoft Defender for Endpoint — Custom indicators / advanced hunting
• Email Gateway — Attachment scanning
• File Share Monitoring — Periodic scanning of shared drives
• YARA CLI — Manual threat hunting on endpoints

This rule contains 2 string patterns in its detection logic.

• Source Rule

False Positive Guidance

Here are 4 specific false positive scenarios for the SierraJuliettMikeOne detection rule in an enterprise environment, along with recommended filters or exclusions:

• Scenario: Enterprise Antivirus Real-Time Scanning

  • Context: The YARA signature matches the behavior of legitimate endpoint protection agents (e.g., CrowdStrike Falcon, Microsoft Defender for Endpoint) scanning large files or performing heuristic analysis on user data. These agents often spawn child processes that mimic the rule’s trigger conditions during routine background scans.
  • Filter/Exclusion: Add an exclusion for the specific process names of known EDR agents (e.g., C:\Program Files\CrowdStrike\fsagent.exe, MsMpEng.exe) and restrict the alert to only trigger if the parent process is not a trusted system service.

• Scenario: Scheduled Patch Management Deployment

  • Context: During off-hours maintenance windows, tools like WSUS (Windows Server Update Services) or SCCM (System Center Configuration Manager) execute installation scripts that modify registry keys and write to protected directories. These actions often generate the specific file I/O patterns or command-line arguments that SierraJuliettMikeOne is designed to detect as suspicious.
  • Filter/Exclusion: Create a time-based filter to suppress alerts between 02:00 and 05:00 local time, or exclude process paths containing \CCM\, \Windows\SoftwareDistribution\, and executable hashes belonging to the organization’s patch management infrastructure.

• Scenario: Automated Backup Operations

  • Context: Enterprise backup solutions such as Veeam Backup & Replication or Commvault frequently utilize PowerShell scripts (powershell.exe) to manage snapshot creation, log rotation, and data compression. These legitimate jobs often invoke commands that match the rule’s logic for “unusual process execution