{
 "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
}