Detection: Splunk HTTP Response Splitting Via Rest SPL Command

Updated Date: 2024-10-17 ID: e615a0e1-a1b2-4196-9865-8aa646e1708c Author: Rod Soto, Chase Franklin Type: Hunting Product: Splunk Enterprise Security

Description

The following analytic identifies attempts to exploit an HTTP response splitting vulnerability via the rest SPL command in Splunk. It detects this activity by analyzing audit logs for specific search commands that include REST methods like POST, PUT, PATCH, or DELETE. This behavior is significant because it indicates a potential attempt to access restricted REST endpoints, which could lead to unauthorized access to sensitive information. If confirmed malicious, this activity could allow an attacker to access restricted content, such as password files, by injecting commands into HTTP requests.

1`audit_searches` AND search IN ("*
2|*rest*POST*","*
3|*rest*PUT*","*
4|*rest*PATCH*","*
5|*rest*DELETE*") AND NOT search="*audit_searches*" 
6| table user info has_error_msg search _time  
7| `splunk_http_response_splitting_via_rest_spl_command_filter`

Data Source

Name Platform Sourcetype Source
Splunk Splunk icon Splunk 'splunkd_ui_access' 'splunkd_ui_access.log'

Macros Used

Name Value
audit_searches index=_audit sourcetype=audittrail action=search
splunk_http_response_splitting_via_rest_spl_command_filter search *
splunk_http_response_splitting_via_rest_spl_command_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
T1027.006 HTML Smuggling Defense Evasion
KillChainPhase.EXPLOITAITON
NistCategory.DE_AE
Cis18Value.CIS_10
APT29

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

This detection does not require you to ingest any new data. The detection does require the ability to search the _audit index. This search may assist in detecting possible http response splitting exploitation attemptss.

Known False Positives

This search may have produce false positives as malformed or erroneous requests made to this endpoint may be executed willingly or erroneously by operators.

Associated Analytic Story

Risk Based Analytics (RBA)

Risk Message Risk Score Impact Confidence
Suspicious access by $user$ 25 50 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 audittrail audittrail
Integration ✅ Passing Dataset audittrail audittrail

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: 3