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[DRAFT] [ML Package] Privileged Access Detection #11577

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6 changes: 6 additions & 0 deletions packages/privileged_access/changelog.yml
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# newer versions go on top
- version: "0.0.1"
changes:
- description: Initial release of the package
type: enhancement
link: https://github.com/elastic/integrations/pull/####
15 changes: 15 additions & 0 deletions packages/privileged_access/docs/README.md
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# Privileged Access Detection

<!-- TODO: Overview -->

## Installation

## Anomaly Detection Jobs

| Job | Description |
|---------------------------------------------------|-------------------------------------------------------------------------------------------------| |


## Licensing

Usage in production requires that you have a license key that permits use of machine learning features.
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- name: host.name
type: keyword
- name: user.name
type: keyword
- name: privilege_type
type: keyword
- name: event.action
type: keyword
- name: event.code
type: keyword
- name: event.category
type: keyword
- name: '@timestamp'
type: date
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source:
index: "logs-*"
query:
bool:
filter:
- range:
'@timestamp':
gte: now-1M
- exists:
field: winlog.event_data.PrivilegeList
- terms:
'host.os.type': ["windows","Windows"]
- terms:
'event.action': ["logged-in-special","privileged-service-called","privileged-operation"]
- terms:
'winlog.event_data.PrivilegeList': ["SeDebugPrivilege","SeTakeOwnershipPrivilege","SeBackupPrivilege", "SeRestorePrivilege","SeImpersonatePrivilege","SeAssignPrimaryTokenPrivilege"]
dest:
index: ml_privilege_type_ped-0.0.1
aliases:
- alias: ml_privilege_type_ped.latest
move_on_creation: true
- alias: ml_privilege_type_ped.all
move_on_creation: false
description: This transform runs hourly and collects special privileges assigned to an user in Windows events for Privilege Escalation Detection package.
frequency: 1h
pivot:
aggregations:
'@timestamp':
max:
field: '@timestamp'
group_by:
'host.name':
terms:
field: host.name
'user.name':
terms:
field: user.name
'privilege_type':
terms:
field: winlog.event_data.PrivilegeList
'event.action':
terms:
field: event.action
'event.category':
terms:
field: event.category
'event.code':
terms:
field: event.code
settings:
# This is required to prevent the transform from clobbering the Fleet-managed mappings.
deduce_mappings: false
unattended: true
sync:
time:
delay: 60s
field: '@timestamp'
_meta:
fleet_transform_version: 0.0.1
run_as_kibana_system: false
4 changes: 4 additions & 0 deletions packages/privileged_access/img/icon-machine-learning.svg
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