Unusual Linux Network Activity
editUnusual Linux Network Activity
editIdentifies Linux processes that do not usually use the network but have unexpected network activity, which can indicate command-and-control, lateral movement, persistence, or data exfiltration activity. A process with unusual network activity can denote process exploitation or injection, where the process is used to run persistence mechanisms that allow a malicious actor remote access or control of the host, data exfiltration, and execution of unauthorized network applications.
Rule type: machine_learning
Rule indices: None
Severity: low
Risk score: 21
Runs every: 15m
Searches indices from: now-45m (Date Math format, see also Additional look-back time)
Maximum alerts per execution: 100
References:
Tags:
- Domain: Endpoint
- OS: Linux
- Use Case: Threat Detection
- Rule Type: ML
- Rule Type: Machine Learning
Version: 103
Rule authors:
- Elastic
Rule license: Elastic License v2
Investigation guide
edit## Triage and analysis ### Investigating Unusual Network Activity Detection alerts from this rule indicate the presence of network activity from a Linux process for which network activity is rare and unusual. Here are some possible avenues of investigation: - Consider the IP addresses and ports. Are these used by normal but infrequent network workflows? Are they expected or unexpected? - If the destination IP address is remote or external, does it associate with an expected domain, organization or geography? Note: avoid interacting directly with suspected malicious IP addresses. - Consider the user as identified by the username field. Is this network activity part of an expected workflow for the user who ran the program? - Examine the history of execution. If this process only manifested recently, it might be part of a new software package. If it has a consistent cadence (for example if it runs monthly or quarterly), it might be part of a monthly or quarterly business or maintenance process. - Examine the process arguments, title and working directory. These may provide indications as to the source of the program or the nature of the tasks it is performing.