How Full Summary in Uncoder AI Supercharges Kusto Query Analysis for Threat Hunters

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April 23, 2025 · 5 min read
How Full Summary in Uncoder AI Supercharges Kusto Query Analysis for Threat Hunters

Working with Microsoft Sentinel often means dissecting complex Kusto queries, especially when tracking subtle attacker behavior. These queries can include nested logic, obscure file path checks, and uncommon system events that require deep understanding. That’s exactly where Uncoder AI’s Full Summary feature shines.

This AI-powered enhancement automatically translates complex Microsoft Sentinel (Kusto) detection logic into a structured, plain-language explanation—turning intricate rules into actionable intelligence within seconds.

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Real Case: Clfs.sys Loaded from Suspicious User Paths

Take the example from the screenshot: a detection rule monitoring for instances where clfs.sys, a legitimate system driver, is loaded from non-standard or suspicious directories such as \Users\Public, \Temp, \Pictures, \Contacts, etc.

This behavior could indicate that an attacker has placed or side-loaded the clfs.sys module from user-space paths to evade detection or persist under the radar.

But the original query? Full of nested conditions, Image contains statements, and directory logic that takes time to interpret.

Input we used (click to show the text)
SysmonEvent | where EventID == 7 | where (ImageLoaded endswith @’\clfs.sys’ and ((Image contains @’:\Perflogs\’ or Image contains @’:\Users\Public\’ or Image contains @’\Temporary Internet’ or Image contains @’\Windows\Temp\’) or (Image contains @’:\Users\’ and Image contains @’\Favorites\’) or (Image contains @’:\Users\’ and Image contains @’\Favourites\’) or (Image contains @’:\Users\’ and Image contains @’\Contacts\’) or (Image contains @’:\Users\’ and Image contains @’\Pictures\’)))
AI Output (click to show the text)

The provided Microsoft Sentinel Query is designed to detect specific system activities captured by the System Monitor (Sysmon) event logs. Here’s a breakdown of what this query aims to achieve:

  1. Filtering for Event ID 7: The query starts by filtering Sysmon events where EventID == 7. In Sysmon, Event ID 7 corresponds to an “Image Loaded” event, which means that the system has loaded a new module (like a DLL) into memory. This is a common event but can be significant in identifying malicious activity if unusual or unexpected modules are being loaded.
  2. Filtering for clfs.sys: The query further narrows down these “Image Loaded” events by looking for instances where the loaded image (ImageLoaded) ends with \clfs.sys. This file, clfs.sys, is a Windows system driver related to the Common Log File System (CLFS). It’s essential for certain logging and database operations within Windows. The interest in this specific driver might stem from its potential misuse by malware or other unauthorized processes.
  3. Specific Directory Filters: The query then applies several filters based on the path of the image being loaded (Image). These filters are looking for images that are located in, or have paths containing, certain directories. Specifically, it’s looking for:
    • Paths that include \Perflogs\, which could indicate activity related to performance logging.
    • Paths that include \Users\Public\, suggesting involvement of the public user directory.
    • Paths that contain \Temporary Internet, indicating temporary internet files.
    • Paths that end with \Windows\Temp\, pointing to the Windows temporary folder, a common place for malware or unauthorized activity.
    • More specific filters are applied within user directories (:\Users\), focusing on subdirectories such as:
      \Favourites\ (accounting for different regional spellings)
      \Contacts\
      \Pictures\

    These specific directory filters suggest that the query is interested in identifying if clfs.sys or similar system modules are being loaded from unusual or potentially compromised locations within the user space, which could indicate malicious activity. The focus on these particular directories and subdirectories implies a concern for data integrity, privacy, or potential lateral movement within a network.

    In essence, this Microsoft Sentinel Query is designed to uncover suspicious loading of Windows system drivers from non-standard paths, particularly those associated with user data, temporary storage, or other areas that might not typically be involved in system-level operations. This could help security teams identify and respond to potential threats, such as unauthorized access to sensitive data or malicious software attempting to blend into legitimate system activities.

What Full Summary Delivered

Instead of manually parsing through the logic, Uncoder AI instantly generated a clear, structured explanation:

  • Why Event ID 7 matters: It reflects a loaded module (ImageLoaded), which can be benign or signal malicious activity.
  • Why Clfs.sys is targeted: While legitimate, its misuse could indicate lateral movement or privilege escalation.
  • Why user directories are suspicious: These locations aren’t typical for system-level drivers and may signal unauthorized access or persistence techniques.

Operational Impact: From Review to Action

This feature reduced the analyst’s investigation time drastically—transforming a multi-step logic review into a single-pass summary. It enabled faster triage, better context for threat validation, and immediate retro-hunting across stored logs.

In short, Uncoder AI’s Full Summary bridged the gap between complex detection engineering and fast operational response.

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