Phoenix Exploit Kit Detection

Hunt Hypothesis

The Phoenix Exploit Kit Detection rule identifies potential exploitation attempts by malicious actors leveraging the Phoenix Exploit Kit to deliver payloads through compromised websites. SOC teams should proactively hunt for this behavior in Azure Sentinel to detect early-stage attacks and prevent lateral movement and data exfiltration.

YARA Rule

rule phoenix_html3 : EK
{
meta:
   author = "Josh Berry"
   date = "2016-06-26"
   description = "Phoenix Exploit Kit Detection"
   hash0 = "d7cacbff6438d866998fc8bfee18102d"
   sample_filetype = "js-html"
   yaragenerator = "https://github.com/Xen0ph0n/YaraGenerator"
strings:
   $string0 = "mtfla/,)asaf)'}"
   $string1 = "72267E7C'A3035CFC415DFAAA834B208D8C230FD303E2EFFE386BE05960C588C6E85650746E690C39F706F97DC74349BA134"
   $string2 = "N'eiui7F6e617e00F145A002645E527BFF264842F877B2FFC1FE84BCC6A50F0305B5B0C36A019F53674FD4D3736C494BD5C2"
   $string3 = "lndl}})<>"
   $string4 = "otodc};b<0:D>r5d4u%c005u%0028u%251eu%a095u%6028u%0028u%2500u%f7f7u%70d7u%2025u%9008u%08f8u%c607usu%3"
   $string5 = "tuJaboaopb"
   $string6 = "a(vxf{p'tSowa.i,1NIWm("
   $string7 = "2004et"
   $string8 = "2054sttE5356496478"
   $string9 = "yi%A%%A%%A%%A%Cvld3,5314,004,6211,931,,,011394617,983,1154,5,1,,1,1,13,08,4304,1"
   $string10 = "0ovel04ervEeieeem)h))B(ihsAE;u%04b8u%1c08u%0e50u%a000u%1010u%4000u%20afu%0006u%2478u%0020u%1065u%210"
   $string11 = "/gmi,String.fromCharCode(2"
   $string12 = "ncBcaocta.ye"
   $string13 = "0201010030004A033102090;na"
   $string14 = "66u%0(ec'h{iis%%A%%A%%A%%A%frS1,,8187,1,4,11,91516,,61,,10841,1,13,,,11248,01818849,23,,,,791meits0e"
   $string15 = "D11C0002C0069733E60656F6462070D000402DFF200696E"
   $string16 = "810p0y98"
   $string17 = "9,0,e'Fm692E583760"
   $string18 = "57784234633a)(u"
condition:
   18 of them
}

Deployment Notes

This YARA rule can be deployed in the following contexts:

• Microsoft Defender for Endpoint — Custom indicators / advanced hunting
• Email Gateway — Attachment scanning
• File Share Monitoring — Periodic scanning of shared drives
• YARA CLI — Manual threat hunting on endpoints

This rule contains 19 string patterns in its detection logic.

• Source Rule

False Positive Guidance

• Scenario: Scheduled System Maintenance Job
  Description: A legitimate scheduled task runs a script that uses curl or wget to fetch updates from an internal repository.
  Filter/Exclusion: Exclude traffic to internal IP ranges (e.g., 10.0.0.0/8, 172.16.0.0/12, 192.168.0.0/16) or specific internal URLs (e.g., https://internal-repo.example.com).

• Scenario: Admin Performing Remote Code Execution (RCE) via SSH
  Description: A system administrator uses SSH to execute a script on a remote server, which includes a curl command to fetch a payload from a known internal server.
  Filter/Exclusion: Exclude SSH traffic to known admin hosts or filter based on SSH session identifiers (e.g., ssh -p 22 user@192.168.1.10).

• Scenario: Automated Software Update Process
  Description: A CI/CD pipeline or package manager (e.g., apt, yum, npm) fetches updates from a public or internal repository.
  Filter/Exclusion: Exclude traffic to known package repositories (e.g., https://archive.ubuntu.com, https://npm.pkg.github.com) or filter by process name (e.g., apt, npm).

• Scenario: Log Collection and Aggregation Tool (e.g., Fluentd, Logstash)
  Description: A log aggregation tool sends logs to a central server using curl or rsync, which may resemble exploit kit behavior.
  Filter/Exclusion: Exclude traffic to log servers (e.g., https://logserver.example.com) or filter by process name (e.g., `fl