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8 changes: 7 additions & 1 deletion contentctl.yml
Original file line number Diff line number Diff line change
Expand Up @@ -92,7 +92,7 @@ apps:
version: 1.3.0
description: description of app
hardcoded_path: https://attack-range-appbinaries.s3.us-west-2.amazonaws.com/splunk-add-on-for-microsoft-iis_130.tgz
- uid: 4242
- uid: 6994
title: CCX Add-on for Suricata
appid: SPLUNK_TA_FOR_SURICATA
version: 1.0.1
Expand Down Expand Up @@ -250,6 +250,12 @@ apps:
version: 0.1.2
description: description of app
hardcoded_path: https://attack-range-appbinaries.s3.us-west-2.amazonaws.com/mcp-ta_012.tgz
- uid: 8574
title: TA-osquery
appid: ta-osquery
version: 1.0.4
description: description of app
hardcoded_path: https://attack-range-appbinaries.s3.us-west-2.amazonaws.com/ta-osquery_104.tgz
githash: d6fac80e6d50ae06b40f91519a98489d4ce3a3fd
test_data_caches:
- base_url: https://media.githubusercontent.com/media/splunk/attack_data/master/
Expand Down
11 changes: 7 additions & 4 deletions data_sources/osquery.yml → data_sources/osquery_results.yml
Original file line number Diff line number Diff line change
@@ -1,7 +1,7 @@
name: osquery
name: Osquery Results
id: 7ec4d7c8-c1d0-423a-9169-261f6adb74c0
version: 2
date: '2025-01-23'
version: 3
date: '2026-04-13'
author: Patrick Bareiss, Splunk
description: Logs system queries performed using osquery, including details about
processes, file access, network activity, and system configurations.
Expand All @@ -13,7 +13,10 @@ mitre_components:
- Application Log Content
source: osquery
sourcetype: osquery:results
supported_TA: []
supported_TA:
- name: TA-osquery
url: https://splunkbase.splunk.com/app/8574
version: 1.0.4
fields:
- _time
- calendarTime
Expand Down
101 changes: 101 additions & 0 deletions detections/endpoint/macos_account_created.yml
Original file line number Diff line number Diff line change
@@ -0,0 +1,101 @@
name: MacOS Account Created
id: 491004ae-694f-453e-b1e0-fc1e65daeea1
version: 1
date: '2026-02-26'
author: Raven Tait, Splunk
status: production
type: Anomaly
description: |-
The following analytic detects the creation of a new local user account on a MacOS system. It leverages osquery logs to identify this activity.
Monitoring the creation of local accounts is crucial for a SOC as it can indicate unauthorized access or lateral movement within the network.
If confirmed malicious, this activity could allow an attacker to establish persistence, escalate privileges, or gain unauthorized access to sensitive systems and data.
data_source:
- Osquery Results
search: |-
| tstats `security_content_summariesonly`
count min(_time) as firstTime
max(_time) as lastTime
from datamodel=Endpoint.Processes where

(
Processes.process = "*sysadminctl"
Processes.process = "*-addUser*"
)
OR
(
Processes.process = "*createhomedir*"
Processes.process = "*-u*"
)
OR
(
Processes.process = "*dseditgroup*"
Processes.process IN (
"*edit*",
"*-a*"
)
)
OR
(
Processes.process = "*dscl*"
Processes.process = "*-create*"
)

by Processes.dest Processes.original_file_name Processes.parent_process_id
Processes.process Processes.process_exec Processes.process_guid
Processes.process_hash Processes.process_id
Processes.process_current_directory Processes.process_name
Processes.process_path Processes.user Processes.user_id
Processes.vendor_product

| `drop_dm_object_name(Processes)`
| `security_content_ctime(firstTime)`
| `security_content_ctime(lastTime)`
| `macos_account_created_filter`
how_to_implement: |-
This detection uses osquery and endpoint security on MacOS. Follow the link in references, which describes how to setup process auditing in MacOS with endpoint security and osquery.
Also the [TA-OSquery](https://splunkbase.splunk.com/app/8574) must be deployed across your indexers and universal forwarders in order to have the osquery data populate the data models.
known_false_positives: |-
Creating new accounts after initial endpoint management should be rare in most environments. Investigate and tune as needed.
references:
- https://osquery.readthedocs.io/en/stable/deployment/process-auditing/
Comment thread
RavenTait marked this conversation as resolved.
- https://ss64.com/mac/sysadminctl.html
- https://ss64.com/mac/dseditgroup.html
- https://ss64.com/mac/dscl.html
drilldown_searches:
- name: View the detection results for - "$user$" and "$dest$"
search: '%original_detection_search% | search user = "$user$" dest = "$dest$"'
earliest_offset: $info_min_time$
latest_offset: $info_max_time$
- name: View risk events for the last 7 days for - "$user$" and "$dest$"
search: '| from datamodel Risk.All_Risk | search normalized_risk_object IN ("$user$", "$dest$") starthoursago=168 | stats count min(_time) as firstTime max(_time) as lastTime values(search_name) as "Search Name" values(risk_message) as "Risk Message" values(analyticstories) as "Analytic Stories" values(annotations._all) as "Annotations" values(annotations.mitre_attack.mitre_tactic) as "ATT&CK Tactics" by normalized_risk_object | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)`'
earliest_offset: $info_min_time$
latest_offset: $info_max_time$
rba:
message: New local account created on $dest$ by $user$ via $process$
risk_objects:
- field: user
type: user
score: 20
- field: dest
type: system
score: 20
threat_objects:
- field: process
type: process
tags:
analytic_story:
- MacOS Persistence Techniques
asset_type: Endpoint
mitre_attack_id:
- T1136
product:
- Splunk Enterprise
- Splunk Enterprise Security
- Splunk Cloud
security_domain: endpoint
tests:
- name: True Positive Test
attack_data:
- data: https://media.githubusercontent.com/media/splunk/attack_data/master/datasets/attack_techniques/T1136/osquery_account_creation/osquery.log
source: osquery
sourcetype: osquery:results
Original file line number Diff line number Diff line change
@@ -1,32 +1,42 @@
name: MacOS AMOS Stealer - Virtual Machine Check Activity
id: 4e41ad21-9761-426d-8aa1-083712ff9f30
version: 5
date: '2026-03-10'
version: 6
date: '2026-04-13'
author: Nasreddine Bencherchali, Splunk, Alex Karkins
status: production
type: Anomaly
description: |
The following analytic detects AMOS Stealer VM check activity on macOS. It leverages osquery to monitor process events and identifies the execution of the "osascript" command along with specific commandline strings. This activity is significant
as AMOS stealer was seen using this pattern in order to check if the host is a Virtual Machine or not. If confirmed malicious, this behavior indicate that the host is already infected by the AMOS stealer, which could allow attackers to execute arbitrary code, escalate privileges, steal information, or persist within the environment, posing a significant security risk.
The following analytic detects AMOS Stealer VM check activity on macOS. It leverages osquery to monitor process events and identifies the execution of the "osascript" command along with specific commandline strings.
This activity is significant as AMOS stealer was seen using this pattern in order to check if the host is a Virtual Machine or not.
If confirmed malicious, this behavior indicate that the host is already infected by the AMOS stealer, which could allow attackers to execute arbitrary code, escalate privileges, steal information, or persist within the environment, posing a significant security risk.
data_source:
- osquery
- Osquery Results
search: |
`osquery_macro` name=es_process_events
columns.cmdline="*osascript*" AND columns.cmdline="* -e *" AND columns.cmdline="*set*" AND columns.cmdline="*system_profiler*" AND columns.cmdline IN ("*VMware*", "*QEMU*")
`osquery_macro`
name=es_process_events
columns.cmdline="*osascript*"
columns.cmdline="* -e *"
columns.cmdline="*set*"
columns.cmdline="*system_profiler*"
columns.cmdline IN ("*VMware*", "*QEMU*")

| rename columns.* as *

| stats min(_time) as firstTime max(_time) as lastTime
values(cmdline) as cmdline,
values(pid) as pid,
values(parent) as parent,
values(path) as path,
values(signing_id) as signing_id,
by username host

| rename
username as user,
cmdline as process,
parent as parent_process,
path as process_path,
host as dest

| `security_content_ctime(firstTime)`
| `security_content_ctime(lastTime)`
| `macos_amos_stealer___virtual_machine_check_activity_filter`
Expand Down
88 changes: 88 additions & 0 deletions detections/endpoint/macos_data_chunking.yml
Original file line number Diff line number Diff line change
@@ -0,0 +1,88 @@
name: MacOS Data Chunking
id: 7f1c8bed-9bd4-40b0-a1df-c262cbade0fc
version: 1
date: '2026-02-26'
author: Raven Tait, Splunk
status: production
type: Anomaly
description: |-
The following analytic detects suspicious data chunking activities that involve the use of split or dd, potentially indicating an attempt to evade detection by breaking large files into smaller parts.
Attackers may use this technique to bypass size-based security controls, facilitating the covert exfiltration of sensitive data.
By monitoring for unusual or unauthorized use of these commands, this analytic helps identify potential data exfiltration attempts, allowing security teams to intervene and prevent the unauthorized transfer of critical information from the network.
data_source:
- Osquery Results
search: |-
| tstats `security_content_summariesonly`
count min(_time) as firstTime
max(_time) as lastTime

from datamodel=Endpoint.Processes where

(
Processes.process = "dd *"
Processes.process = "* if=*"
)
OR
(
Processes.process = "*split *"
Processes.process="* -b *"
)

by Processes.dest Processes.original_file_name Processes.parent_process_id
Processes.process Processes.process_exec Processes.process_guid
Processes.process_hash Processes.process_id
Processes.process_current_directory Processes.process_name
Processes.process_path Processes.user
Processes.user_id Processes.vendor_product

| `drop_dm_object_name(Processes)`
| `security_content_ctime(firstTime)`
| `security_content_ctime(lastTime)`
| `macos_data_chunking_filter`
how_to_implement: |-
This detection uses osquery and endpoint security on MacOS. Follow the link in references, which describes how to setup process auditing in MacOS with endpoint security and osquery.
Also the [TA-OSquery](https://splunkbase.splunk.com/app/8574) must be deployed across your indexers and universal forwarders in order to have the osquery data populate the data models.
known_false_positives: |-
Administrator or network operator can use this application for automation purposes. Please update the filter macros to remove false positives.
references:
- https://osquery.readthedocs.io/en/stable/deployment/process-auditing/
Comment thread
RavenTait marked this conversation as resolved.
- https://ss64.com/mac/dd.html
- https://ss64.com/mac/split.html
drilldown_searches:
- name: View the detection results for - "$user$" and "$dest$"
search: '%original_detection_search% | search user = "$user$" dest = "$dest$"'
earliest_offset: $info_min_time$
latest_offset: $info_max_time$
- name: View risk events for the last 7 days for - "$user$" and "$dest$"
search: '| from datamodel Risk.All_Risk | search normalized_risk_object IN ("$user$", "$dest$") starthoursago=168 | stats count min(_time) as firstTime max(_time) as lastTime values(search_name) as "Search Name" values(risk_message) as "Risk Message" values(analyticstories) as "Analytic Stories" values(annotations._all) as "Annotations" values(annotations.mitre_attack.mitre_tactic) as "ATT&CK Tactics" by normalized_risk_object | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)`'
earliest_offset: $info_min_time$
latest_offset: $info_max_time$
rba:
message: A file was split on $dest$ by $user$ via $process$
risk_objects:
- field: user
type: user
score: 20
- field: dest
type: system
score: 20
threat_objects:
- field: process
type: process
tags:
analytic_story:
- MacOS Post-Exploitation
asset_type: Endpoint
mitre_attack_id:
- T1030
product:
- Splunk Enterprise
- Splunk Enterprise Security
- Splunk Cloud
security_domain: endpoint
tests:
- name: True Positive Test
attack_data:
- data: https://media.githubusercontent.com/media/splunk/attack_data/master/datasets/attack_techniques/T1030/osquery_data_chunking/osquery.log
source: osquery
sourcetype: osquery:results
89 changes: 89 additions & 0 deletions detections/endpoint/macos_gatekeeper_bypass.yml
Original file line number Diff line number Diff line change
@@ -0,0 +1,89 @@
name: MacOS Gatekeeper Bypass
id: 2c9346f3-bbeb-48ce-8411-fc13d09d83a5
version: 1
date: '2026-02-26'
author: Raven Tait, Splunk
status: production
type: Anomaly
description: |-
Detects known MacOS security bypass techniques that may be used to enable malicious code execution.
Specifically monitors for attempts to remove the com.apple.quarantine attribute using xattr, or to disable Gatekeeper protections via spctl --master-disable, both of which can allow untrusted or malicious applications to execute without standard system safeguards.
data_source:
- Osquery Results
search: |-
| tstats `security_content_summariesonly`
count min(_time) as firstTime
max(_time) as lastTime

from datamodel=Endpoint.Processes where

(
Processes.process = "*xattr*"
Processes.process = "*com.apple.quarantine*"
)
OR
(
Processes.process = "*spctl*"
Processes.process = "*master-disable*"
)

by Processes.dest Processes.original_file_name Processes.parent_process_id
Processes.process Processes.process_exec Processes.process_guid
Processes.process_hash Processes.process_id
Processes.process_current_directory Processes.process_name
Processes.process_path Processes.user
Processes.user_id Processes.vendor_product

| `drop_dm_object_name(Processes)`
| `security_content_ctime(firstTime)`
| `security_content_ctime(lastTime)`
| `macos_gatekeeper_bypass_filter`
how_to_implement: |-
This detection uses osquery and endpoint security on MacOS. Follow the link in references, which describes how to setup process auditing in MacOS with endpoint security and osquery.
Also the [TA-OSquery](https://splunkbase.splunk.com/app/8574) must be deployed across your indexers and universal forwarders in order to have the osquery data populate the data models.
known_false_positives: |-
Administrators or power users may need to disable Gatekeeper to install unsigned tools.
references:
- https://osquery.readthedocs.io/en/stable/deployment/process-auditing/
Comment thread
RavenTait marked this conversation as resolved.
- https://ss64.com/mac/xattr.html
- https://ss64.com/mac/spctl.html
drilldown_searches:
- name: View the detection results for - "$user$" and "$dest$"
search: '%original_detection_search% | search user = "$user$" dest = "$dest$"'
earliest_offset: $info_min_time$
latest_offset: $info_max_time$
- name: View risk events for the last 7 days for - "$user$" and "$dest$"
search: '| from datamodel Risk.All_Risk | search normalized_risk_object IN ("$user$", "$dest$") starthoursago=168 | stats count min(_time) as firstTime max(_time) as lastTime values(search_name) as "Search Name" values(risk_message) as "Risk Message" values(analyticstories) as "Analytic Stories" values(annotations._all) as "Annotations" values(annotations.mitre_attack.mitre_tactic) as "ATT&CK Tactics" by normalized_risk_object | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)`'
earliest_offset: $info_min_time$
latest_offset: $info_max_time$
rba:
message: Attempt to bypass gatekeeper protections on $dest$ by $user$ via $process$
risk_objects:
- field: user
type: user
score: 20
- field: dest
type: system
score: 20
threat_objects:
- field: process
type: process
tags:
analytic_story:
- MacOS Privilege Escalation
- MacOS Post-Exploitation
- MacOS Persistence Techniques
asset_type: Endpoint
mitre_attack_id:
- T1553.001
product:
- Splunk Enterprise
- Splunk Enterprise Security
- Splunk Cloud
security_domain: endpoint
tests:
- name: True Positive Test
attack_data:
- data: https://media.githubusercontent.com/media/splunk/attack_data/master/datasets/attack_techniques/T1553.001/osquery_gatekeeper/osquery.log
source: osquery
sourcetype: osquery:results
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