Bobby Filar
9a739b7e4c
* modifying rules assoc w/ deprecation of v2 ML jobs * modified updated_date field * fixed machine_learning_job_id and added min_stack_version * replacing rest of deprecated jobs with new naming convention * Update ml_suspicious_login_activity.toml * removing rules assoc w/ deprecated ML jobs * Update rules/ml/ml_linux_anomalous_compiler_activity.toml Co-authored-by: Justin Ibarra <brokensound77@users.noreply.github.com> * Update rules/ml/ml_linux_anomalous_compiler_activity.toml Co-authored-by: Justin Ibarra <brokensound77@users.noreply.github.com> * updated ml job rules to reflect 8.3 changes * updating min_stack_version for ml detection rules Co-authored-by: Craig Chamberlain <randomuserid@users.noreply.github.com> Co-authored-by: Justin Ibarra <brokensound77@users.noreply.github.com> Co-authored-by: Apoorva Joshi <30438249+ajosh0504@users.noreply.github.com>
32 lines
990 B
TOML
32 lines
990 B
TOML
[metadata]
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creation_date = "2020/09/22"
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maturity = "production"
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updated_date = "2022/05/12"
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min_stack_comments = "Supports latest version of ML job introduced in 8.3"
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min_stack_version = "8.3.0"
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[rule]
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anomaly_threshold = 50
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author = ["Elastic"]
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description = """
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Looks for anomalous access to the metadata service by an unusual process. The metadata service may be targeted in order
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to harvest credentials or user data scripts containing secrets.
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"""
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false_positives = [
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"""
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A newly installed program or one that runs very rarely as part of a monthly or quarterly workflow could trigger this
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detection rule.
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""",
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]
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from = "now-45m"
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interval = "15m"
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license = "Elastic License v2"
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machine_learning_job_id = ["v3_linux_rare_metadata_process"]
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name = "Unusual Linux Process Calling the Metadata Service"
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risk_score = 21
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rule_id = "9d302377-d226-4e12-b54c-1906b5aec4f6"
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severity = "low"
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tags = ["Elastic", "Host", "Linux", "Threat Detection", "ML"]
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type = "machine_learning"
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