ml_windows_anomalous_network_activity.toml

[metadata]
creation_date = "2020/03/25"
integration = ["endpoint", "windows"]
maturity = "production"
updated_date = "2024/05/21"

[rule]
anomaly_threshold = 50
author = ["Elastic"]
description = """
Identifies Windows 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.
"""
false_positives = ["A newly installed program or one that rarely uses the network could trigger this alert."]
from = "now-45m"
interval = "15m"
license = "Elastic License v2"
machine_learning_job_id = ["v3_windows_anomalous_network_activity"]
name = "Unusual Windows Network Activity"
note = """## Triage and analysis

### Investigating Unusual Network Activity
Detection alerts from this rule indicate the presence of network activity from a Windows process for which network activity is very unusual.  Here are some possible avenues of investigation:
- Consider the IP addresses, protocol 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 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.
- Consider the same for the parent process. If the parent process is a legitimate system utility or service, this could be related to software updates or system management. If the parent process is something user-facing like an Office application, this process could be more suspicious.
- If you have file hash values in the event data, and you suspect malware, you can optionally run a search for the file hash to see if the file is identified as malware by anti-malware tools."""
references = ["https://www.elastic.co/guide/en/security/current/prebuilt-ml-jobs.html"]
risk_score = 21
rule_id = "ba342eb2-583c-439f-b04d-1fdd7c1417cc"
severity = "low"
tags = [
    "Domain: Endpoint",
    "OS: Windows",
    "Use Case: Threat Detection",
    "Rule Type: ML",
    "Rule Type: Machine Learning",
]
type = "machine_learning"