Apoorva Joshi
e41fe620e6
* Adding detection rules for auth ML jobs * name prefix added the prefix "auth" to the file names * Added descriptions * Adding new lines and updating license * FP text added FP metadata Co-authored-by: Craig <mailredirector36@gmail.com>
35 lines
1.3 KiB
TOML
35 lines
1.3 KiB
TOML
[metadata]
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creation_date = "2021/06/10"
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maturity = "production"
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updated_date = "2021/06/10"
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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 found an unusual user name in the authentication logs. An unusual user name is one way of
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detecting credentialed access by means of a new or dormant user account. A user account that is normally inactive,
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because the user has left the organization, which becomes active, may be due to credentialed access using a compromised
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account password. Threat actors will sometimes also create new users as a means of persisting in a compromised web
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application.
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"""
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false_positives = [
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"""
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User accounts that are rarely active, such as an SRE or developer logging into a prod server for troubleshooting,
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may trigger this alert. Under some conditions, a newly created user account may briefly trigger this alert while the
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model is learning.
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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 = "auth_rare_user"
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name = "Rare User Logon"
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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 = "138c5dd5-838b-446e-b1ac-c995c7f8108a"
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severity = "low"
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tags = ["Elastic", "Authentication", "Threat Detection", "ML"]
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type = "machine_learning"
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