Password Discovery via Notepad: How Uncoder AI Simplifies SPL Detection Logic

Attackers often use trusted tools like Notepad to discreetly access sensitive files, especially those labeled as password-related. This tactic blends in with regular user behavior but can signal early-stage credential theft or internal reconnaissance.

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A Splunk detection rule recently translated in SOC Prime’s Uncoder AI platform targets exactly this scenario. It focuses on Windows Security log EventCode 4688, triggered when a new process is created. Specifically, the rule detects:

• explorer.exe spawning notepad.exe
  
  
• Command-line arguments pointing to filenames like *password*.txt , *password*.csv , *password*.doc , or *password*.xls

The behavior suggests that a user—or potentially malware—is using Notepad to open files containing passwords, possibly indicating an attempt to harvest credentials in plaintext.

Input we used (click to show the text)

index=* source="WinEventLog:Security" AND EventCode=4688 AND (ParentProcessName="*\\explorer.exe" AND NewProcessName="*\\notepad.exe" AND (CommandLine="*password*.txt" OR CommandLine="*password*.csv" OR CommandLine="*password*.doc" OR CommandLine="*password*.xls"))

Detection Logic Overview

The SPL rule contains multiple layered conditions

Without context, this query may require detailed parsing to understand its purpose—especially for junior analysts or during high-pressure triage.

What Uncoder AI’s Summary Delivered

Uncoder AI’s Short AI-generated Summary immediately surfaces the rule’s intent:

“This Splunk query searches for Windows Security log events where Notepad is launched by Explorer with a command line containing file names related to passwords.”

This concise explanation removes the need to reverse-engineer the query structure. Analysts can validate behavior patterns at a glance and focus on response rather than interpretation.

AI Output (click to show the text)

This Splunk query searches for Windows Security log events where Notepad is launched by Explorer with a command line containing file names related to passwords.

Why This Matters

• Faster Threat Triage: Clear summaries reduce the time spent decoding detection rules, enabling quicker identification of credential access activity.
  
• Improved Rule Transparency: Teams can more easily review and document detection logic when migrating Sigma rules to Splunk or sharing with stakeholders.
  
• Enhanced Security Posture: By accelerating understanding, SOCs can prioritize detections that expose credential theft or insider threat behavior.
  

From SPL Code to Security Insight

Splunk remains a powerful detection platform—but writing and reviewing complex queries can introduce friction. Uncoder AI’s Short AI-generated Summary bridges that gap, translating syntax-heavy logic into operational clarity. In this case, what once looked like a wall of SPL code now instantly reveals a targeted detection for password file access via Notepad—complete with full attack context.

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