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

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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# SAM Dump to AppData\n",
"Detects suspicious SAM dump activity as cause by QuarksPwDump and other password dumpers"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Rule Content\n",
"```\n",
"- title: SAM Dump to AppData\n",
" id: 839dd1e8-eda8-4834-8145-01beeee33acd\n",
" status: experimental\n",
" description: Detects suspicious SAM dump activity as cause by QuarksPwDump and other\n",
" password dumpers\n",
" tags:\n",
" - attack.credential_access\n",
" - attack.t1003\n",
" author: Florian Roth\n",
" logsource:\n",
" product: windows\n",
" service: system\n",
" definition: The source of this type of event is Kernel-General\n",
" category: null\n",
" detection:\n",
" selection:\n",
" EventID: 16\n",
" keywords:\n",
" Message:\n",
" - '*\\AppData\\Local\\Temp\\SAM-*.dmp *'\n",
" condition: all of them\n",
" falsepositives:\n",
" - Penetration testing\n",
" level: high\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-system-*', 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:\"16\" AND Message.keyword:(*\\\\AppData\\\\Local\\\\Temp\\\\SAM\\-*.dmp\\ *))')\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
}