Detection rules › Splunk

HTTP Malware User Agent

Status
production
Severity
medium
Group by
Web.src, Web.url_length, c-uri, c-useragent, cs-host, cs-method, dest, http_user_agent, malware, src, url
Author
Raven Tait, Splunk
Source
github.com/splunk/security_content

This Splunk query analyzes web logs to identify and categorize user agents, detecting various types of malware. This activity can signify possible compromised hosts on the network.

Known false positives

  • Filtering may be required in some instances depending on legacy system usage, filter as needed.

MITRE ATT&CK coverage

Rule body

name: HTTP Malware User Agent
id: 8c4866e4-f488-4253-8537-7dc4f954c292
version: 5
creation_date: '2026-01-06'
modification_date: '2026-05-13'
author: Raven Tait, Splunk
status: production
type: TTP
description: This Splunk query analyzes web logs to identify and categorize user agents, detecting various types of malware. This activity can signify possible compromised hosts on the network.
data_source:
    - Suricata
search: |-
    | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Web
      WHERE Web.http_user_agent != null
      BY Web.http_user_agent Web.http_method, Web.url,
         Web.url_length Web.src, Web.dest
    | `drop_dm_object_name("Web")`
    | lookup malware_user_agents malware_user_agent AS http_user_agent OUTPUT malware
    | where isnotnull(malware)
    | stats count min(firstTime) as first_seen max(lastTime) as last_seen
      BY malware url http_user_agent
         src dest
    | `security_content_ctime(first_seen)`
    | `security_content_ctime(last_seen)`
    | `http_malware_user_agent_filter`
how_to_implement: To successfully implement this search, you need to be ingesting web or proxy logs, or ensure it is being filled by a proxy like device, into the Web Datamodel. For additional filtering, allow list private IP space or restrict by known good.
known_false_positives: Filtering may be required in some instances depending on legacy system usage, filter as needed.
references:
    - https://github.com/mthcht/awesome-lists/blob/main/Lists/suspicious_http_user_agents_list.csv
finding:
    title: A known malware user agent $http_user_agent$ was performing a request from $src$.
    entity:
        field: src
        type: system
        score: 50
threat_objects:
    - field: http_user_agent
      type: http_user_agent
analytic_story:
    - Lokibot
    - Lumma Stealer
    - Meduza Stealer
    - Crypto Stealer
    - RedLine Stealer
    - Suspicious User Agents
asset_type: Network
mitre_attack_id:
    - T1071.001
product:
    - Splunk Enterprise
    - Splunk Enterprise Security
    - Splunk Cloud
category: network
security_domain: network

Stages and Predicates

Stage 1: tstats

| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Web
  WHERE Web.http_user_agent != null
  BY Web.http_user_agent Web.http_method, Web.url,
     Web.url_length Web.src, Web.dest

Stage 2: search

| `drop_dm_object_name("Web")`

Stage 3: lookup

| lookup malware_user_agents malware_user_agent AS http_user_agent OUTPUT malware
Lookup table
malware_user_agents
Key field
malware_user_agent as http_user_agent
Output columns
['malware', 'malware']

Stage 4: where

| where isnotnull(malware)

Stage 5: stats

| stats count min(firstTime) as first_seen max(lastTime) as last_seen
  BY malware url http_user_agent
     src dest

Stage 6: search

| `security_content_ctime(first_seen)`

Stage 7: search

| `security_content_ctime(last_seen)`

Stage 8: search

| `http_malware_user_agent_filter`

Indicators

These rows show field, operator, and value matches.