mirror of https://github.com/infosecn1nja/HELK.git
129 lines
2.7 KiB
Plaintext
129 lines
2.7 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# NTLM Logon\n",
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"Detects logons using NTLM, which could be caused by a legacy source or attackers"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Rule Content\n",
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"```\n",
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"- title: NTLM Logon\n",
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" id: 98c3bcf1-56f2-49dc-9d8d-c66cf190238b\n",
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" status: experimental\n",
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" description: Detects logons using NTLM, which could be caused by a legacy source\n",
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" or attackers\n",
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" references:\n",
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" - https://twitter.com/JohnLaTwC/status/1004895028995477505\n",
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" - https://goo.gl/PsqrhT\n",
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" author: Florian Roth\n",
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" date: 2018/06/08\n",
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" tags:\n",
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" - attack.lateral_movement\n",
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" - attack.t1075\n",
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" logsource:\n",
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" product: windows\n",
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" service: ntlm\n",
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" definition: Reqiures events from Microsoft-Windows-NTLM/Operational\n",
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" category: null\n",
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" detection:\n",
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" selection:\n",
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" EventID: 8002\n",
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" CallingProcessName: '*'\n",
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" condition: selection\n",
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" falsepositives:\n",
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" - Legacy hosts\n",
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" level: low\n",
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"\n",
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"```"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Querying Elasticsearch"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Import Libraries"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"from elasticsearch import Elasticsearch\n",
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"from elasticsearch_dsl import Search\n",
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"import pandas as pd"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Initialize Elasticsearch client"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"es = Elasticsearch(['http://helk-elasticsearch:9200'])\n",
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"searchContext = Search(using=es, index='logs-*', doc_type='doc')"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Run Elasticsearch Query"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"s = searchContext.query('query_string', query='(event_id:\"8002\" AND process_path.keyword:*)')\n",
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"response = s.execute()\n",
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"if response.success():\n",
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" df = pd.DataFrame((d.to_dict() for d in s.scan()))"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Show Results"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"df.head()"
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]
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}
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],
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"metadata": {},
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"nbformat": 4,
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"nbformat_minor": 4
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}
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