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Description

The analytic is devised to detect likely phishing attempts within a network blocked by Zscaler. By leveraging Splunk search functionality, it evaluates web proxy logs for blocked actions correlated with phishing threats, specifically those tagged as HTML.Phish. Critical data points such as the user, threat name, URL, and hostname are analyzed to accentuate possible phishing activities. This anomaly-type detection serves as an early warning system, facilitating prompt investigation and mitigation of phishing threats, thereby bolstering network security.

  • Type: Anomaly

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

  • Last Updated: 2023-10-30
  • Author: Gowthamaraj Rajendran, Rod Soto, Splunk
  • ID: 68d3e2c1-e97f-4310-b080-dea180b48aa9

Annotations

ATT&CK

ATT&CK

ID Technique Tactic
T1566 Phishing Initial Access
Kill Chain Phase
  • Delivery
NIST
  • DE.AE
CIS20
  • CIS 10
CVE 


1
2
3
4
5



`zscaler_proxy` action=blocked threatname="HTML.Phish*" 
| stats count min(_time) as firstTime max(_time) as lastTime by action deviceowner user threatname url src dest 
| `security_content_ctime(firstTime)` 
| `security_content_ctime(lastTime)` 
| `zscaler_phishing_activity_threat_blocked_filter`

Macros

The SPL above uses the following Macros:

:information_source: zscaler_phishing_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

RBA

Risk Score Impact Confidence Message
16.0 20 80 Potential Phishing 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.

Reference

Test Dataset

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

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