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The analytic targets the detection of potential malware activities within a network that are blocked by Zscaler. By filtering web proxy logs for blocked actions associated with malware, where a threat category is specified, the analytic aggregates occurrences by user, URL, and threat category. This approach ensures a focused identification of malware activities, making it an effective tool for ongoing network security monitoring and anomaly detection.

  • Type: Anomaly
  • Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud

  • Last Updated: 2023-10-25
  • Author: Rod Soto, Gowthamaraj Rajendran, Splunk
  • ID: ae874ad8-e353-40a7-87d4-420cdfb27d1a




ID Technique Tactic
T1566 Phishing Initial Access
Kill Chain Phase
  • Delivery
  • DE.AE
  • CIS 10
`zscaler_proxy` action=blocked threatname=*malware* threatcategory!=None 
| stats count min(_time) as firstTime max(_time) as lastTime by action deviceowner user urlcategory url src dest 
| `security_content_ctime(firstTime)` 
| `security_content_ctime(lastTime)` 
| `zscaler_malware_activity_threat_blocked_filter`


The SPL above uses the following Macros:

:information_source: zscaler_malware_activity_threat_blocked_filter is a empty macro by default. It allows the user to filter out any results (false positives) without editing the SPL.

Required fields

List of fields required to use this analytic.

  • action
  • threatname
  • deviceowner
  • user
  • urlcategory
  • url
  • dest
  • dest_ip
  • action

How To Implement

You must install the latest version of Zscaler Add-on from Splunkbase. You must be ingesting Zscaler events into your Splunk environment through an ingester. This analytic was written to be used with the "zscalernss-web" sourcetype leveraging the Zscaler proxy data. This enables the integration with Splunk Enterprise Security. Security teams are encouraged to adjust the detection parameters, ensuring the detection is tailored to their specific environment.

Known False Positives

False positives are limited to Zscalar configuration.

Associated Analytic Story


Risk Score Impact Confidence Message
40.0 50 80 Potential Malware Activity from dest -[$dest$] on $src$ for user-[$user$].

:information_source: The Risk Score is calculated by the following formula: Risk Score = (Impact * Confidence/100). Initial Confidence and Impact is set by the analytic author.


Test Dataset

Replay any dataset to Splunk Enterprise by using our tool or the UI. Alternatively you can replay a dataset into a Splunk Attack Range

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