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Description

The following analytic detects the addition of new IIS modules on a Windows IIS server. It leverages the Windows Event log - Microsoft-IIS-Configuration/Operational, specifically EventCode 29, to identify this activity. This behavior is significant because IIS modules are rarely added to production servers, and unauthorized modules could indicate malicious activity. If confirmed malicious, an attacker could use these modules to execute arbitrary code, escalate privileges, or maintain persistence within the environment, potentially compromising the server and sensitive data.

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

  • Last Updated: 2024-05-12
  • Author: Michael Haag, Splunk
  • ID: 55f22929-cfd3-4388-ba5c-4d01fac7ee7e

Annotations

ATT&CK

ATT&CK

ID Technique Tactic
T1505 Server Software Component Persistence
T1505.004 IIS Components Persistence
Kill Chain Phase
  • Installation
NIST
  • DE.CM
CIS20
  • CIS 10
CVE
1
2
3
4
5
6
`iis_operational_logs` EventCode=29 
| stats  count min(_time) as firstTime max(_time) as lastTime by OpCode EventCode ComputerName Message 
| rename ComputerName AS dest 
| `security_content_ctime(firstTime)` 
| `security_content_ctime(lastTime)` 
| `windows_iis_components_new_module_added_filter`

Macros

The SPL above uses the following Macros:

:information_source: windows_iis_components_new_module_added_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.

  • _time
  • OpCode
  • EventCode
  • ComputerName
  • Message

How To Implement

You must enabled the IIS Configuration Operational log before ingesting in Splunk. Setup and inputs may be found here https://gist.github.com/MHaggis/64396dfd9fc3734e1d1901a8f2f07040.

Known False Positives

False positives may be present when updates or an administrator adds a new module to IIS. Monitor and filter as needed.

Associated Analytic Story

RBA

Risk Score Impact Confidence Message
48.0 60 80 A new IIS Module has been loaded and should be reviewed on $dest$.

: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

source | version: 2