Detection: Splunk Improperly Formatted Parameter Crashes splunkd

EXPERIMENTAL DETECTION

This detection status is set to experimental. The Splunk Threat Research team has not yet fully tested, simulated, or built comprehensive datasets for this detection. As such, this analytic is not officially supported. If you have any questions or concerns, please reach out to us at research@splunk.com.

Updated Date: 2024-05-14 ID: 08978eca-caff-44c1-84dc-53f17def4e14 Author: Chase Franklin, Rod Soto, Splunk Type: TTP Product: Splunk Enterprise Security

Description

The following analytic detects the execution of improperly formatted INGEST_EVAL parameters in Splunk Enterprise, which can crash the splunkd service. It leverages the Splunk_Audit.Search_Activity datamodel to identify ad-hoc searches containing specific keywords. This activity is significant because it can disrupt Splunk operations, leading to potential data loss and service downtime. If confirmed malicious, an attacker could exploit this to cause a denial of service, impacting the availability and reliability of the Splunk environment.

Search

1
2| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Splunk_Audit.Search_Activity where (Search_Activity.search="*makeresults*"AND Search_Activity.search="*ingestpreview*transforms*") Search_Activity.search_type=adhoc Search_Activity.search!="*splunk_improperly_formatted_parameter_crashes_splunkd_filter*" Search_Activity.user!=splunk-system-user by Search_Activity.search, Search_Activity.info, Search_Activity.total_run_time, Search_Activity.user, Search_Activity.search_type 
3| `drop_dm_object_name(Search_Activity)` 
4| `security_content_ctime(firstTime)` 
5| `security_content_ctime(lastTime)` 
6| `splunk_improperly_formatted_parameter_crashes_splunkd_filter`

Data Source

Name	Platform	Sourcetype	Source	Supported App
N/A	N/A	N/A	N/A	N/A

Macros Used

Name	Value
security_content_ctime	`convert timeformat="%Y-%m-%dT%H:%M:%S" ctime($field$)`
splunk_improperly_formatted_parameter_crashes_splunkd_filter	`search *`

splunk_improperly_formatted_parameter_crashes_splunkd_filter is an empty macro by default. It allows the user to filter out any results (false positives) without editing the SPL.

Annotations

- MITRE ATT&CK

+ Kill Chain Phases

+ NIST

+ CIS

- Threat Actors

ID	Technique	Tactic
T1499	Endpoint Denial of Service	Impact

KillChainPhase.ACTIONS_ON_OBJECTIVES

NistCategory.DE_CM

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 Notable	Yes
Rule Title	`%name%`
Rule Description	`%description%`
Notable Event Fields	user, dest
Creates Risk Event	True

This configuration file applies to all detections of type TTP. These detections will use Risk Based Alerting and generate Notable Events.

Implementation

Requires access to audittrail and use of Splunk_Audit.Search_Activity datamodel.

Known False Positives

This is a hunting search it should be focused on affected products, otherwise it is likely to produce false positives.

Associated Analytic Story

Splunk Vulnerabilities

Risk Based Analytics (RBA)

Risk Message	Risk Score	Impact	Confidence
An attempt to exploit ingest eval parameter was detected from $user$	100	100	100

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

https://www.splunk.com/en_us/product-security.html

Detection Testing

Test Type	Status	Dataset	Source	Sourcetype
Validation	Not Applicable	N/A	N/A	N/A
Unit	❌ Failing	N/A	`N/A`	`N/A`
Integration	❌ Failing	N/A	`N/A`	`N/A`

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