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sigma-rules/rules/ml/ml_windows_anomalous_process_creation.toml
T
Justin Ibarra 79a0dfefbe Add ECS 1.6.0 schema for validation testing (#220)
* Add ecs 1.6.0 and refresh master ecs (2.0.0)
* update rule metadata to use ecs_version 1.6.0
2020-08-27 11:54:49 -05:00

36 lines
1.5 KiB
TOML

[metadata]
creation_date = "2020/03/25"
ecs_version = ["1.6.0"]
maturity = "production"
updated_date = "2020/03/25"
[rule]
anomaly_threshold = 50
author = ["Elastic"]
description = """
Identifies unusual parent-child process relationships that can indicate malware execution or persistence mechanisms.
Malicious scripts often call on other applications and processes as part of their exploit payload. For example, when a
malicious Office document runs scripts as part of an exploit payload, Excel or Word may start a script interpreter
process, which, in turn, runs a script that downloads and executes malware. Another common scenario is Outlook running
an unusual process when malware is downloaded in an email. Monitoring and identifying anomalous process relationships is
a method of detecting new and emerging malware that is not yet recognized by anti-virus scanners.
"""
false_positives = [
"""
Users running scripts in the course of technical support operations of software upgrades could trigger this alert. A
newly installed program or one that runs rarely as part of a monthly or quarterly workflow could trigger this alert.
""",
]
from = "now-45m"
interval = "15m"
license = "Elastic License"
machine_learning_job_id = "windows_anomalous_process_creation"
name = "Anomalous Windows Process Creation"
references = ["https://www.elastic.co/guide/en/security/current/prebuilt-ml-jobs.html"]
risk_score = 21
rule_id = "0b29cab4-dbbd-4a3f-9e8e-1287c7c11ae5"
severity = "low"
tags = ["Elastic", "ML", "Windows"]
type = "machine_learning"