9482bda414
* Adding related integrations to ML rules * added adjustments to determine related integrations for ML rules * fixed lint errors * Empty commit * Empty commit * Empty commit --------- Co-authored-by: Apoorva Joshi <apoorvajoshi@Apoorvas-MBP.lan> Co-authored-by: Terrance DeJesus <99630311+terrancedejesus@users.noreply.github.com> Co-authored-by: terrancedejesus <terrance.dejesus@elastic.co> Co-authored-by: Apoorva Joshi <apoorvajoshi@Apoorvas-MBP.fritz.box>
37 lines
1.5 KiB
TOML
37 lines
1.5 KiB
TOML
[metadata]
|
|
creation_date = "2021/04/05"
|
|
integration = ["endpoint", "network_traffic"]
|
|
maturity = "production"
|
|
min_stack_comments = "New fields added: required_fields, related_integrations, setup"
|
|
min_stack_version = "8.3.0"
|
|
updated_date = "2023/07/27"
|
|
|
|
[rule]
|
|
anomaly_threshold = 75
|
|
author = ["Elastic"]
|
|
description = """
|
|
A machine learning job detected an unusually large spike in network traffic. Such a burst of traffic,
|
|
if not caused by a surge in business activity, can be due to suspicious or malicious activity.
|
|
Large-scale data exfiltration may produce a burst of network traffic; this could also be due to unusually
|
|
large amounts of reconnaissance or enumeration traffic. Denial-of-service attacks or traffic floods may
|
|
also produce such a surge in traffic.
|
|
"""
|
|
false_positives = [
|
|
"""
|
|
Business workflows that occur very occasionally, and involve an unusual surge in network traffic,
|
|
can trigger this alert. A new business workflow or a surge in business activity may trigger this alert.
|
|
A misconfigured network application or firewall may trigger this alert.
|
|
""",
|
|
]
|
|
from = "now-30m"
|
|
interval = "15m"
|
|
license = "Elastic License v2"
|
|
machine_learning_job_id = "high_count_network_events"
|
|
name = "Spike in Network Traffic"
|
|
references = ["https://www.elastic.co/guide/en/security/current/prebuilt-ml-jobs.html"]
|
|
risk_score = 21
|
|
rule_id = "b240bfb8-26b7-4e5e-924e-218144a3fa71"
|
|
severity = "low"
|
|
tags = ["Use Case: Threat Detection", "Rule Type: ML", "Rule Type: Machine Learning", ]
|
|
type = "machine_learning"
|