Detection: Linux Netcat Outbound Connection

Description

The following analytic detects outbound network connections originating from Netcat or Netcat-like binaries on Linux systems. Netcat is a versatile networking utility that, while legitimate in some contexts, is frequently abused by attackers to establish reverse shells, exfiltrate data, or create persistent backdoor connections to remote systems. This activity is significant because outbound connections from these binaries often indicate an active compromise, where an attacker may be maintaining command-and-control communication or tunneling malicious traffic. If confirmed malicious, this could lead to unauthorized data exfiltration, lateral movement, or persistent remote access to the compromised system.

 1
 2| tstats `security_content_summariesonly`
 3  count min(_time) as firstTime
 4        max(_time) as lastTime
 5
 6from datamodel=Network_Traffic.All_Traffic where
 7
 8All_Traffic.app IN (
 9    "*nc",
10    "*ncat",
11    "*netcat"
12)
13All_Traffic.direction="outbound"
14
15by All_Traffic.src All_Traffic.dest All_Traffic.dest_port All_Traffic.transport
16   All_Traffic.process_name All_Traffic.app All_Traffic.user All_Traffic.process_id
17
18
19| `drop_dm_object_name(All_Traffic)`
20
21| `security_content_ctime(firstTime)`
22
23| `security_content_ctime(lastTime)`
24
25| `linux_netcat_outbound_connection_filter`

Data Source

Name Platform Sourcetype Source
Sysmon for Linux EventID 3 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_netcat_outbound_connection_filter search *
linux_netcat_outbound_connection_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
T1059.004 Unix Shell Execution
Installation
DE.AE
CIS 10

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 Finding (Notable) No
Creates Intermediate Finding (Risk Event) Yes
Anomaly detections generate Intermediate Findings (Risk Events). They do not generate a Finding (Notable) directly.

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 network connection events including the source, destination, port, and process context. 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 Network_Traffic data model. Use the Splunk Common Information Model (CIM) to normalize the field names and speed up the data modeling process.

Known False Positives

Legitimate system administrators or developers may use netcat for troubleshooting, port scanning, or testing network connectivity. Filter based on known administrative activity or authorized users.

Associated Analytic Story

Intermediate Findings

Message Entity Field Entity Type Risk Score
Netcat outbound connection detected on [$dest$] dest system 20

Threat Objects

Field Type
dest ip_address

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: 1