Enhancing Cortex XQL Threat Detection with Full Summary in Uncoder AI

As attackers become more creative in bypassing traditional network defenses, analysts need fast, clear insight into the logic behind complex detection rules. That’s where Uncoder AI’s Full Summary feature becomes a game-changer—especially for teams working with Palo Alto Cortex XSIAM Query Language (XQL).

In a recent use case, Uncoder AI helped threat hunters break down an XQL detection rule that flags HTTP requests to low-reputation top-level domains (TLDs) or to suspicious file extensions, often used during the early stages of malware delivery or phishing campaigns.

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The Detection in Focus

The XQL rule performs dual filtering:

1. Low-Reputation TLDs — The query identifies HTTP traffic to domains ending in TLDs like .ru , .su , .party , .xyz , .click , and others commonly linked to spam or malware infrastructure.
   
   
2. Suspicious File Types — It also inspects URL patterns and MIME types for indicators of executable content, such as .exe , .js , .vbs , .ps1 , or application/x-msdownload.

Input we used (click to show the text)

datamodel dataset = *

| filter (host ~= ".*\.bid" or host ~= ".*\.by" or host ~= ".*\.cf" or host ~= ".*\.click" or host ~= ".*\.cm" or host ~= ".*\.ga" or host ~= ".*\.gq" or host ~= ".*\.ir" or host ~= ".*\.kp" or host ~= ".*\.loan" or host ~= ".*\.ml" or host ~= ".*\.mm" or host ~= ".*\.party" or host ~= ".*\.pw" or host ~= ".*\.ru" or host ~= ".*\.su" or host ~= ".*\.sy" or host ~= ".*\.tk" or host ~= ".*\.top" or host ~= ".*\.tv" or host ~= ".*\.ve" or host ~= ".*\.work" or host ~= ".*\.xyz") and ((xdm.network.http.url ~= ".*\.bat" or xdm.network.http.url ~= ".*\.bin" or xdm.network.http.url ~= ".*\.cmd" or xdm.network.http.url ~= ".*\.cpl" or xdm.network.http.url ~= ".*\.dll" or xdm.network.http.url ~= ".*\.dylib" or xdm.network.http.url ~= ".*\.elf" or xdm.network.http.url ~= ".*\.exe" or xdm.network.http.url ~= ".*\.hta" or xdm.network.http.url ~= ".*\.iso" or xdm.network.http.url ~= ".*\.jar" or xdm.network.http.url ~= ".*\.js" or xdm.network.http.url ~= ".*\.lnk" or xdm.network.http.url ~= ".*\.msi" or xdm.network.http.url ~= ".*\.pif" or xdm.network.http.url ~= ".*\.ps1" or xdm.network.http.url ~= ".*\.py" or xdm.network.http.url ~= ".*\.reg" or xdm.network.http.url ~= ".*\.scr" or xdm.network.http.url ~= ".*\.sh" or xdm.network.http.url ~= ".*\.so" or xdm.network.http.url ~= ".*\.vbs" or xdm.network.http.url ~= ".*\.wsf") or resp_mime_types in ("application/vnd.microsoft.portable-executable", "application/x-bat", "application/x-dosexec", "application/x-elf", "application/x-iso9660-image", "application/x-java-archive", "application/x-ms-shortcut", "application/x-msdos-program", "application/x-msdownload", "application/x-python-code", "application/x-sh"))

// name: HTTP Request to Low Reputation TLD or Suspicious File Extension

// uuid: 68c2c604-92ad-468b-bf4a-aac49adad08c

// author: @signalblur, Corelight

// licence: DRL 1.1

But for many analysts, especially under pressure, this kind of query can appear dense and time-consuming to interpret. That’s where Full Summary steps in.

What Full Summary Delivered

Uncoder AI instantly generated a complete and plain-language breakdown of the rule’s logic, intent, and threat context. It not only explained which patterns were being checked, but why—linking specific file types and domain patterns to known adversary tradecraft.

Real Value: Time Saved, Risk Reduced

This isn’t just about translation. It’s about accelerating detection validation and enabling faster response by giving security teams immediate insight into what a query actually detects.

In this case, the team was able to:

• Rapidly confirm that the detection would catch suspicious download attempts tied to known bad TLDs
  
• Identify gaps in their coverage for additional risky MIME types
  
• Confidently roll the rule into production without back-and-forth interpretation
  

Conclusion: Context at the Speed of Threat

By decoding complex Cortex XQL logic, Uncoder AI’s Full Summary bridges the gap between detection logic and operational action. For defenders, especially during fast-paced threat response or purple teaming, this context isn’t just helpful—it’s essential.

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