command_and_control_ml_packetbeat_dns_tunneling.toml

[metadata]
creation_date = "2020/03/25"
maturity = "production"
min_stack_comments = "New fields added: required_fields, related_integrations, setup"
min_stack_version = "8.3.0"
updated_date = "2023/03/06"

[rule]
anomaly_threshold = 50
author = ["Elastic"]
description = """
A machine learning job detected unusually large numbers of DNS queries for a single top-level DNS domain, which is often
used for DNS tunneling. DNS tunneling can be used for command-and-control, persistence, or data exfiltration activity.
For example, dnscat tends to generate many DNS questions for a top-level domain as it uses the DNS protocol to tunnel
data.
"""
false_positives = [
    """
    DNS domains that use large numbers of child domains, such as software or content distribution networks, can trigger
    this alert and such parent domains can be excluded.
    """,
]
from = "now-45m"
interval = "15m"
license = "Elastic License v2"
machine_learning_job_id = "packetbeat_dns_tunneling"
name = "DNS Tunneling"
references = ["https://www.elastic.co/guide/en/security/current/prebuilt-ml-jobs.html"]
risk_score = 21
rule_id = "91f02f01-969f-4167-8f66-07827ac3bdd9"
severity = "low"
tags = ["Elastic", "Network", "Threat Detection", "ML", "Machine Learning", "Command and Control"]
type = "machine_learning"

[[rule.threat]]
framework = "MITRE ATT&CK"
[[rule.threat.technique]]
id = "T1572"
name = "Protocol Tunneling"
reference = "https://attack.mitre.org/techniques/T1572/"


[rule.threat.tactic]
id = "TA0011"
name = "Command and Control"
reference = "https://attack.mitre.org/tactics/TA0011/"