HELK/docker/helk-jupyter/notebooks/sigma/apt_oceanlotus_registry.ipynb

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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# OceanLotus Registry Activity\n",
"Detects registry keys created in OceanLotus (also known as APT32) attacks"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Rule Content\n",
"```\n",
"- title: OceanLotus Registry Activity\n",
" id: 4ac5fc44-a601-4c06-955b-309df8c4e9d4\n",
" status: experimental\n",
" description: Detects registry keys created in OceanLotus (also known as APT32) attacks\n",
" references:\n",
" - https://www.welivesecurity.com/2019/03/20/fake-or-fake-keeping-up-with-oceanlotus-decoys/\n",
" tags:\n",
" - attack.t1112\n",
" author: megan201296\n",
" date: 2019/04/14\n",
" logsource:\n",
" product: windows\n",
" service: sysmon\n",
" category: null\n",
" detection:\n",
" selection:\n",
" EventID: 13\n",
" TargetObject:\n",
" - '*\\SOFTWARE\\Classes\\CLSID\\{E08A0F4B-1F65-4D4D-9A09-BD4625B9C5A1}\\Model'\n",
" - '*\\SOFTWARE\\App\\AppXbf13d4ea2945444d8b13e2121cb6b663\\Application'\n",
" - '*\\SOFTWARE\\App\\AppXbf13d4ea2945444d8b13e2121cb6b663\\DefaultIcon'\n",
" - '*\\SOFTWARE\\App\\AppX70162486c7554f7f80f481985d67586d\\Application'\n",
" - '*\\SOFTWARE\\App\\AppX70162486c7554f7f80f481985d67586d\\DefaultIcon'\n",
" - '*\\SOFTWARE\\App\\AppX37cc7fdccd644b4f85f4b22d5a3f105a\\Application'\n",
" - '*\\SOFTWARE\\App\\AppX37cc7fdccd644b4f85f4b22d5a3f105a\\DefaultIcon'\n",
" condition: selection\n",
" falsepositives:\n",
" - Unknown\n",
" level: critical\n",
"\n",
"```"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Querying Elasticsearch"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Import Libraries"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"from elasticsearch import Elasticsearch\n",
"from elasticsearch_dsl import Search\n",
"import pandas as pd"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Initialize Elasticsearch client"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"es = Elasticsearch(['http://helk-elasticsearch:9200'])\n",
"searchContext = Search(using=es, index='logs-endpoint-winevent-sysmon-*', doc_type='doc')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Run Elasticsearch Query"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"s = searchContext.query('query_string', query='(event_id:\"13\" AND registry_key_path.keyword:(*\\\\SOFTWARE\\\\Classes\\\\CLSID\\\\\\{E08A0F4B\\-1F65\\-4D4D\\-9A09\\-BD4625B9C5A1\\}\\\\Model OR *\\\\SOFTWARE\\\\App\\\\AppXbf13d4ea2945444d8b13e2121cb6b663\\\\Application OR *\\\\SOFTWARE\\\\App\\\\AppXbf13d4ea2945444d8b13e2121cb6b663\\\\DefaultIcon OR *\\\\SOFTWARE\\\\App\\\\AppX70162486c7554f7f80f481985d67586d\\\\Application OR *\\\\SOFTWARE\\\\App\\\\AppX70162486c7554f7f80f481985d67586d\\\\DefaultIcon OR *\\\\SOFTWARE\\\\App\\\\AppX37cc7fdccd644b4f85f4b22d5a3f105a\\\\Application OR *\\\\SOFTWARE\\\\App\\\\AppX37cc7fdccd644b4f85f4b22d5a3f105a\\\\DefaultIcon))')\n",
"response = s.execute()\n",
"if response.success():\n",
" df = pd.DataFrame((d.to_dict() for d in s.scan()))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Show Results"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"df.head()"
]
}
],
"metadata": {},
"nbformat": 4,
"nbformat_minor": 4
}