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

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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Emotet Process Creation\n",
"Detects all Emotet like process executions that are not covered by the more generic rules"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Rule Content\n",
"```\n",
"- title: Emotet Process Creation\n",
" id: d02e8cf5-6099-48cf-9bfc-1eec2d0c7b18\n",
" status: experimental\n",
" description: Detects all Emotet like process executions that are not covered by\n",
" the more generic rules\n",
" author: Florian Roth\n",
" date: 2019/09/30\n",
" modified: 2019/10/16\n",
" references:\n",
" - https://app.any.run/tasks/e13ab713-64cf-4b23-ad93-6dceaa5429ac/\n",
" - https://app.any.run/tasks/81f3c28c-c686-425d-8a2b-a98198d244e1/\n",
" - https://app.any.run/tasks/97f875e8-0e08-4328-815f-055e971ba754/\n",
" logsource:\n",
" category: process_creation\n",
" product: windows\n",
" service: null\n",
" detection:\n",
" selection:\n",
" CommandLine:\n",
" - '* -e* PAA*'\n",
" - '*JABlAG4AdgA6AHUAcwBlAHIAcAByAG8AZgBpAGwAZQ*'\n",
" - '*QAZQBuAHYAOgB1AHMAZQByAHAAcgBvAGYAaQBsAGUA*'\n",
" - '*kAGUAbgB2ADoAdQBzAGUAcgBwAHIAbwBmAGkAbABlA*'\n",
" - '*IgAoACcAKgAnACkAOwAkA*'\n",
" - '*IAKAAnACoAJwApADsAJA*'\n",
" - '*iACgAJwAqACcAKQA7ACQA*'\n",
" condition: selection\n",
" fields:\n",
" - CommandLine\n",
" - ParentCommandLine\n",
" falsepositives:\n",
" - Unlikely\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-*', 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='process_command_line.keyword:(*\\ \\-e*\\ PAA* OR *JABlAG4AdgA6AHUAcwBlAHIAcAByAG8AZgBpAGwAZQ* OR *QAZQBuAHYAOgB1AHMAZQByAHAAcgBvAGYAaQBsAGUA* OR *kAGUAbgB2ADoAdQBzAGUAcgBwAHIAbwBmAGkAbABlA* OR *IgAoACcAKgAnACkAOwAkA* OR *IAKAAnACoAJwApADsAJA* OR *iACgAJwAqACcAKQA7ACQA*)')\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
}