Detection rules › Splunk
HTTP Malware User Agent
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
| Tactic | Techniques |
|---|---|
| Command & Control |
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
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.
| Field | Kind | Values | Search |
|---|---|---|---|
Web.http_user_agent | ne |
| field:"c-useragent" kind:ne value:"null" |
malware | is_not_null | field:"malware" kind:is_not_null |