{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Access to ADMIN$ Share\n", "Detects access to $ADMIN share" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Rule Content\n", "```\n", "- title: Access to ADMIN$ Share\n", " id: 098d7118-55bc-4912-a836-dc6483a8d150\n", " description: Detects access to $ADMIN share\n", " tags:\n", " - attack.lateral_movement\n", " - attack.t1077\n", " status: experimental\n", " author: Florian Roth\n", " logsource:\n", " product: windows\n", " service: security\n", " definition: The advanced audit policy setting \"Object Access > Audit File Share\"\n", " must be configured for Success/Failure\n", " category: null\n", " detection:\n", " selection:\n", " EventID: 5140\n", " ShareName: Admin$\n", " filter:\n", " SubjectUserName: '*$'\n", " condition: selection and not filter\n", " falsepositives:\n", " - Legitimate administrative activity\n", " level: low\n", "\n", "```" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Querying Elasticsearch" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Import Libraries" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "from elasticsearch import Elasticsearch\n", "from elasticsearch_dsl import Search\n", "import pandas as pd" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Initialize Elasticsearch client" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "es = Elasticsearch(['http://helk-elasticsearch:9200'])\n", "searchContext = Search(using=es, index='logs-endpoint-winevent-security-*', doc_type='doc')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Run Elasticsearch Query" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "s = searchContext.query('query_string', query='((event_id:\"5140\" AND share_name:\"Admin$\") AND (NOT (user_name.keyword:*$)))')\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 }