Detection: Linux Iptables Firewall Modification

Description

The following analytic detects suspicious command-line activity that modifies the iptables firewall settings on a Linux machine. It leverages data from Endpoint Detection and Response (EDR) agents, focusing on specific command patterns that alter firewall rules to accept traffic on certain TCP ports. This activity is significant as it can indicate malware, such as CyclopsBlink, modifying firewall settings to allow communication with a Command and Control (C2) server. If confirmed malicious, this could enable attackers to maintain persistent access and exfiltrate data, posing a severe security risk.

 1
 2| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process = "*iptables *" AND Processes.process = "* --dport *" AND Processes.process = "* ACCEPT*" AND Processes.process = "*&>/dev/null*" AND Processes.process = "* tcp *" AND NOT(Processes.parent_process_path IN("/bin/*", "/lib/*", "/usr/bin/*", "/sbin/*")) by Processes.process_name Processes.process Processes.process_id Processes.parent_process_id Processes.process_guid Processes.dest _time span=10s Processes.user Processes.parent_process_name Processes.parent_process_path Processes.process_path 
 3| rex field=Processes.process "--dport (?<port>3269
 4|636
 5|989
 6|994
 7|995
 8|8443)" 
 9| stats values(Processes.process) as processes_exec values(port) as ports values(Processes.process_guid) as guids values(Processes.process_id) as pids dc(port) as port_count count by Processes.process_name Processes.parent_process_name Processes.parent_process_id Processes.dest Processes.user Processes.parent_process_path Processes.process_path 
10| where port_count >=3 
11| `drop_dm_object_name(Processes)` 
12| `security_content_ctime(firstTime)` 
13| `security_content_ctime(lastTime)` 
14| `linux_iptables_firewall_modification_filter`

Data Source

Name Platform Sourcetype Source
Sysmon for Linux EventID 1 Linux icon Linux 'sysmon:linux' 'Syslog:Linux-Sysmon/Operational'

Macros Used

Name Value
security_content_ctime convert timeformat="%Y-%m-%dT%H:%M:%S" ctime($field$)
linux_iptables_firewall_modification_filter search *
linux_iptables_firewall_modification_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
T1562.004 Disable or Modify System Firewall Defense Evasion
T1562 Impair Defenses Defense Evasion
KillChainPhase.EXPLOITAITON
NistCategory.DE_AE
Cis18Value.CIS_10
APT38
Carbanak
Dragonfly
Kimsuky
Lazarus Group
Magic Hound
Moses Staff
Rocke
TeamTNT
ToddyCat
Magic Hound

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 True
This configuration file applies to all detections of type anomaly. These detections will use Risk Based Alerting.

Implementation

The detection is based on data that originates from Endpoint Detection and Response (EDR) agents. These agents are designed to provide security-related telemetry from the endpoints where the agent is installed. To implement this search, you must ingest logs that contain the process GUID, process name, and parent process. Additionally, you must ingest complete command-line executions. These logs must be processed using the appropriate Splunk Technology Add-ons that are specific to the EDR product. The logs must also be mapped to the Processes node of the Endpoint data model. Use the Splunk Common Information Model (CIM) to normalize the field names and speed up the data modeling process.

Known False Positives

administrator may do this commandline for auditing and testing purposes. In this scenario filter is needed.

Associated Analytic Story

Risk Based Analytics (RBA)

Risk Message Risk Score Impact Confidence
A process name - $process_name$ that may modify iptables firewall on $dest$ 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 Syslog:Linux-Sysmon/Operational sysmon:linux
Integration ✅ Passing Dataset Syslog:Linux-Sysmon/Operational sysmon:linux

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: 5