:warning: THIS IS A EXPERIMENTAL DETECTION

This detection has been marked experimental by the Splunk Threat Research team. This means we have not been able to test, simulate, or build datasets for this detection. Use at your own risk. This analytic is NOT supported.

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Description

The following hunting analytic is designed to monitor and detect potential exploitation attempts targeting a PaperCut NG server by analyzing its debug log data. By focusing on public IP addresses accessing the PaperCut NG instance, this analytic aims to identify unauthorized or suspicious access attempts. Furthermore, it searches for specific URIs that have been discovered in the proof of concept code, which are associated with known exploits or vulnerabilities. The analytic is focused on the user admin. Regex is used mainly because the log is not parsed by Splunk and there is no TA for this debug log.

  • Type: Hunting

  • Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud

  • Last Updated: 2023-05-15
  • Author: Michael Haag, Splunk
  • ID: 395163b8-689b-444b-86c7-9fe9ad624734

Annotations

ATT&CK

ATT&CK

ID Technique Tactic
T1190 Exploit Public-Facing Application Initial Access
T1133 External Remote Services Persistence, Initial Access
Kill Chain Phase
  • Delivery
  • Installation
NIST
  • DE.AE
CIS20
  • CIS 10
CVE 


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`papercutng` (loginType=Admin OR userName=admin) 
| eval uri_match=if(match(_raw, "(?i)(\/app\?service=page\/SetupCompleted
|\/app
|\/app\?service=page\/PrinterList
|\/app\?service=direct\/1\/PrinterList\/selectPrinter&sp=l1001
|\/app\?service=direct\/1\/PrinterDetails\/printerOptionsTab\.tab)"), "URI matches", null()) 
| eval ip_match=if(match(_raw, "(?i)((25[0-5]
|2[0-4][0-9]
|[01]?[0-9][0-9]?)\.(25[0-5]
|2[0-4][0-9]
|[01]?[0-9][0-9]?)\.(25[0-5]
|2[0-4][0-9]
|[01]?[0-9][0-9]?)\.(25[0-5]
|2[0-4][0-9]
|[01]?[0-9][0-9]?))") AND NOT match(_raw, "(?i)(10\.(25[0-5]
|2[0-4][0-9]
|[01]?[0-9][0-9]?)\.(25[0-5]
|2[0-4][0-9]
|[01]?[0-9][0-9]?)\.(25[0-5]
|2[0-4][0-9]
|[01]?[0-9][0-9]?))
|(172\.(1[6-9]
|2[0-9]
|3[0-1])\.(25[0-5]
|2[0-4][0-9]
|[01]?[0-9][0-9]?)\.(25[0-5]
|2[0-4][0-9]
|[01]?[0-9][0-9]?))
|(192\.168\.(25[0-5]
|2[0-4][0-9]
|[01]?[0-9][0-9]?)\.(25[0-5]
|2[0-4][0-9]
|[01]?[0-9][0-9]?))"), "IP matches", null()) 
| where  (isnotnull(uri_match) OR isnotnull(ip_match)) 
| stats sparkline, count, values(uri_match) AS uri_match, values(ip_match) AS ip_match latest(_raw) BY host, index, sourcetype 
| `papercut_ng_suspicious_behavior_debug_log_filter`

Macros

The SPL above uses the following Macros:

:information_source: papercut_ng_suspicious_behavior_debug_log_filter is a empty macro by default. It allows the user to filter out any results (false positives) without editing the SPL.

Required fields

List of fields required to use this analytic.

  • uri_match
  • ip_match
  • index
  • sourcetype
  • host

How To Implement

Debug logs must be enabled and shipped to Splunk in order to properly identify behavior with this analytic.

Known False Positives

False positives may be present, as this is based on the admin user accessing the Papercut NG instance from a public IP address. Filter as needed.

Associated Analytic Story

RBA

Risk Score Impact Confidence Message
64.0 80 80 Behavior related to exploitation of PaperCut NG has been identified on $host$.

:information_source: The Risk Score is calculated by the following formula: Risk Score = (Impact * Confidence/100). Initial Confidence and Impact is set by the analytic author.

Reference

Test Dataset

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 | version: 1