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https://github.com/marcredhat/kql
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marc
33 lines
1.4 KiB
PowerQuery
33 lines
1.4 KiB
PowerQuery
// Rule: 01_anomalous_signin_location_increase
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// Users showing a spike in distinct signin locations vs baseline
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//
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// Source KQL: see ../kql/01_anomalous_signin_location_increase.kql
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//
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// HOW TO RUN
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// curl POST {sdl}/api/powerQuery with this body, OR paste in
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// the SDL console. Set startTime = '2h' (or wider) so the API
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// scans the freshly-ingested epochs that contain the events.
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//
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// Time anchor at export: NOW = 2026-05-31T20:10:05+00:00
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// Recent-window cutoff: 2026-05-31T18:10:05+00:00
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// (`ts_epoch_ms` below is that cutoff expressed in ms.
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// Re-run harness/export_rules.py to refresh after regenerating
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// sample_data/events.jsonl.)
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//
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// Fields referenced: AppDisplayName, Location, LocationCount, LocationList, LogonCount, RECENT_MS, SigninLogs, UserPrincipalName
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//
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// EDITING NOTE
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// Every line that starts with `|` is a pipeline stage. Each `|`
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// is REQUIRED. If you delete one (e.g. while changing a literal
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// on the same line as a stage), SDL re-parses the keyword that
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// follows as a search term and rejects the query with errors
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// like `'estimate_distinct' is a grouping function`.
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event_type='SigninLogs'
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| filter ts_epoch_ms >= 1780251005000
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| group LocationCount = estimate_distinct(Location),
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LocationList = array_agg_distinct(Location),
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LogonCount = count()
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by UserPrincipalName, AppDisplayName
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| filter LocationCount >= 3
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