ID | Technique | Tactic |
---|---|---|
T1499 | Endpoint Denial of Service | Impact |
Detection: Splunk Unauthenticated DoS via Null Pointer References
Description
The following hunting search provides information on splunkd crash as a result of a Denial of Service Exploitation via null pointer references which targets 'services/cluster/config' endpoint.
Search
1`splunk_crash_log` "Segmentation fault" "POST /services/cluster/config"
2| stats count min(_time) as firstTime max(_time) as lastTime by host
3| `security_content_ctime(firstTime)`
4| `security_content_ctime(lastTime)`
5| `splunk_unauthenticated_dos_via_null_pointer_references_filter`
Data Source
Name | Platform | Sourcetype | Source |
---|---|---|---|
Splunk | Splunk | 'splunkd_ui_access' |
'splunkd_ui_access.log' |
Macros Used
Name | Value |
---|---|
security_content_ctime | convert timeformat="%Y-%m-%dT%H:%M:%S" ctime($field$) |
splunk_unauthenticated_dos_via_null_pointer_references_filter | search * |
splunk_unauthenticated_dos_via_null_pointer_references_filter
is an empty macro by default. It allows the user to filter out any results (false positives) without editing the SPL.
Annotations
KillChainPhase.ACTIONS_ON_OBJECTIVES
NistCategory.DE_AE
Cis18Value.CIS_10
Sandworm Team
Default Configuration
This detection is configured by default in Splunk Enterprise Security to run with the following settings:
Setting | Value |
---|---|
Disabled | true |
Cron Schedule | 0 * * * * |
Earliest Time | -70m@m |
Latest Time | -10m@m |
Schedule Window | auto |
Creates Risk Event | False |
This configuration file applies to all detections of type hunting.
Implementation
Requires access to internal indexes.
Known False Positives
This is a hunting search and will produce false positives. An operator needs to find proximity and detail of requests targeting cluster config endpoint and subsequent Segmentation fault in splunk crash log.
Associated Analytic Story
Risk Based Analytics (RBA)
Risk Message | Risk Score | Impact | Confidence |
---|---|---|---|
Possible exploitation attack against $host$ | 50 | 100 | 50 |
The Risk Score is calculated by the following formula: Risk Score = (Impact * Confidence/100). Initial Confidence and Impact is set by the analytic author.
References
Detection Testing
Test Type | Status | Dataset | Source | Sourcetype |
---|---|---|---|---|
Validation | ✅ Passing | N/A | N/A | N/A |
Unit | ✅ Passing | Dataset | /opt/splunk/var/log/splunk/crash-*.log |
splunkd_crash_log |
Integration | ✅ Passing | Dataset | /opt/splunk/var/log/splunk/crash-*.log |
splunkd_crash_log |
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: GitHub | Version: 2