Apoorva Joshi
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]
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creation_date = "2021/04/05"
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integration = ["endpoint", "network_traffic"]
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maturity = "production"
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min_stack_comments = "New fields added: required_fields, related_integrations, setup"
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min_stack_version = "8.3.0"
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updated_date = "2023/07/27"
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[rule]
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anomaly_threshold = 75
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author = ["Elastic"]
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description = """
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A machine learning job detected an unusually large spike in network traffic that was
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denied by network access control lists (ACLs) or firewall rules. Such a burst of denied traffic is usually caused by
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either 1) a mis-configured application or firewall or 2) suspicious or malicious activity.
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Unsuccessful attempts at network transit, in order to connect to command-and-control (C2),
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or engage in data exfiltration, may produce a burst of failed connections. This could also
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be due to unusually large amounts of reconnaissance or enumeration traffic. Denial-of-service
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attacks or traffic floods may also produce such a surge in traffic.
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"""
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false_positives = [
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"""
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A misconfgured network application or firewall may trigger this alert. Security scans or test cycles may trigger this alert.
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""",
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]
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from = "now-30m"
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interval = "15m"
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license = "Elastic License v2"
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machine_learning_job_id = "high_count_network_denies"
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name = "Spike in Firewall Denies"
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references = ["https://www.elastic.co/guide/en/security/current/prebuilt-ml-jobs.html"]
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risk_score = 21
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rule_id = "eaa77d63-9679-4ce3-be25-3ba8b795e5fa"
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severity = "low"
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tags = ["Use Case: Threat Detection", "Rule Type: ML", "Rule Type: Machine Learning", ]
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type = "machine_learning"
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