Making Splunk Detection Work Faster with Uncoder AI’s Full Summary

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April 17, 2025 · 4 min read
Making Splunk Detection Work Faster with Uncoder AI’s Full Summary

Modern SOC teams dealing with Splunk Detections need to process large volumes of detection logic written in SPL. The challenge? Much of it is complex, verbose, and time-consuming to understand—when working with Splunk content from external sources or Sigma-based rules converted to Splunk format.

Uncoder AI’s Full AI-generated Summary tackles this exact pain point by breaking down what a detection rule is doing and why—without forcing engineers to work through the queries manually.

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The Use Case: Splunk Rule for AD Delegation Abuse

Let’s take a concrete example: SPL query for detecting unconstrained delegation misconfigurations in Active Directory. The SPL logic searches across Windows Event Logs for script blocks matching specific properties (e.g., TrustedForDelegation, msDS-AllowedToDelegateTo, etc.).

This kind of rule is technically accurate, but unless you’re deeply familiar with both PowerShell scripting and AD internals, it takes time to understand what it actually detects.

Input we used (click to show the text)
index=* source=”WinEventLog:*” AND (ScriptBlockText=”*-Properties*TrustedForDelegation*” OR
ScriptBlockText=”*-Properties*TrustedToAuthForDelegation*” OR
ScriptBlockText=”*-Properties*msDS-AllowedToDelegateTo*” OR
ScriptBlockText=”*-Properties*PrincipalsAllowedToDelegateToAccount*” OR
ScriptBlockText=”*-LDAPFilter*(userAccountControl:1.2.840.113556.1.4.803:=524288)*”)
AI Output (click to show the text)

This Splunk query is designed to search for specific Windows Event Log entries that contain indicators of potential Kerberos delegation abuse or configuration changes. Here’s a breakdown of what the query does:

  1. Index and Source Filtering: The query starts by specifying index=* which means it searches across all available indexes in the Splunk environment. It then narrows down the results to only include logs from sources named “WinEventLog:*”, indicating that the focus is on Windows Event Logs.
  2. ScriptBlockText Conditions: The main body of the query uses an AND operator with a series of OR conditions, all related to ScriptBlockText. This implies the search is looking for PowerShell script blocks (code snippets) within these event logs that match certain criteria. Specifically, it’s searching for any mentions of properties or filters related to Kerberos delegation.
    • TrustedForDelegation: This condition searches for instances where a user or computer account has been configured as trusted for delegation. In a Kerberos environment, this setting allows the account to impersonate users and access services on their behalf.
    • TrustedToAuthForDelegation: Similar to the previous condition but specifically related to constrained delegation scenarios where an account is trusted to authenticate for delegation purposes.
    • msDS-AllowedToDelegateTo: This attribute specifies the services to which a user or computer can present delegated credentials. The query looks for modifications or mentions of this attribute in script blocks, indicating possible configuration changes that could affect delegation paths.
    • PrincipalsAllowedToDelegateToAccount: This condition targets configurations where specific principals (users, computers, etc.) are explicitly allowed to delegate their credentials to a particular account, which is another aspect of constrained delegation.
    • LDAPFilter with userAccountControl: The final condition searches for LDAP filters used in script blocks that specifically target accounts with the userAccountControl attribute set to 524288, which corresponds to the “TRUSTED_FOR_DELEGATION” flag. This flag indicates that an account is trusted for delegation, and modifying or searching for this could be part of managing or exploiting Kerberos delegation settings.

    In summary, this Splunk query aims to detect potential security-related activities or misconfigurations within Windows environments related to Kerberos delegation. It looks for indicators in PowerShell script blocks captured in the Windows Event Logs that might suggest changes to trusted delegation settings, which could be used by attackers to move laterally within a network or by administrators to manage and audit their environment’s delegation configurations.

Key Benefits in the Splunk Workflow

  • Rapid Rule Understanding: Especially valuable when pulling Sigma rules into Splunk and needing instant context or working with SPL written by external researchers.
  • Detection Tuning: Helps engineers assess whether filters are too broad or missing conditions.
  • Onboarding: Junior analysts can onboard faster by seeing structured summaries, rather than deciphering raw SPL.
  • Correlation Building: Knowing exactly what a rule detects supports better logic chaining across other rules or datasets.

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Built for Real Security Work

Full AI-generated Summary isn’t just another explainability tool. It’s tuned for detection engineering—bridging Sigma logic and platform-specific queries like SPL, while giving SOC operators real-world, actionable clarity.

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