Files
sigma-rules/rules/ml/ml_high_count_network_events.toml
T
Apoorva Joshi 9482bda414 Adding related integrations to ML rules (#2972)
* Adding related integrations to ML rules

* added adjustments to determine related integrations for ML rules

* fixed lint errors

* Empty commit

* Empty commit

* Empty commit

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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>
2023-08-22 14:39:18 -04:00

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"