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

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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Execution of Renamed PaExec\n",
"Detects execution of renamed paexec via imphash and executable product string"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Rule Content\n",
"```\n",
"- title: Execution of Renamed PaExec\n",
" id: 7b0666ad-3e38-4e3d-9bab-78b06de85f7b\n",
" status: experimental\n",
" description: Detects execution of renamed paexec via imphash and executable product\n",
" string\n",
" references:\n",
" - sha256=01a461ad68d11b5b5096f45eb54df9ba62c5af413fa9eb544eacb598373a26bc\n",
" - https://summit.fireeye.com/content/dam/fireeye-www/summit/cds-2018/presentations/cds18-technical-s05-att&cking-fin7.pdf\n",
" tags:\n",
" - attack.defense_evasion\n",
" - attack.t1036\n",
" - FIN7\n",
" - car.2013-05-009\n",
" date: 2019/04/17\n",
" author: Jason Lynch\n",
" falsepositives:\n",
" - Unknown imphashes\n",
" level: medium\n",
" logsource:\n",
" category: process_creation\n",
" product: windows\n",
" service: null\n",
" detection:\n",
" selection1:\n",
" Product:\n",
" - '*PAExec*'\n",
" selection2:\n",
" Imphash:\n",
" - 11D40A7B7876288F919AB819CC2D9802\n",
" - 6444f8a34e99b8f7d9647de66aabe516\n",
" - dfd6aa3f7b2b1035b76b718f1ddc689f\n",
" - 1a6cca4d5460b1710a12dea39e4a592c\n",
" filter1:\n",
" Image: '*paexec*'\n",
" condition: (selection1 and selection2) and not filter1\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-*', 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='((file_product.keyword:(*PAExec*) AND hash_imphash:(\"11D40A7B7876288F919AB819CC2D9802\" OR \"6444f8a34e99b8f7d9647de66aabe516\" OR \"dfd6aa3f7b2b1035b76b718f1ddc689f\" OR \"1a6cca4d5460b1710a12dea39e4a592c\")) AND (NOT (process_path.keyword:*paexec*)))')\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
}