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

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# NotPetya Ransomware Activity\n",
    "Detects NotPetya ransomware activity in which the extracted passwords are passed back to the main module via named pipe, the file system journal of drive C is deleted and windows eventlogs are cleared using wevtutil"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Rule Content\n",
    "```\n",
    "- title: NotPetya Ransomware Activity\n",
    "  id: 79aeeb41-8156-4fac-a0cd-076495ab82a1\n",
    "  status: experimental\n",
    "  description: Detects NotPetya ransomware activity in which the extracted passwords\n",
    "    are passed back to the main module via named pipe, the file system journal of\n",
    "    drive C is deleted and windows eventlogs are cleared using wevtutil\n",
    "  author: Florian Roth, Tom Ueltschi\n",
    "  references:\n",
    "  - https://securelist.com/schroedingers-petya/78870/\n",
    "  - https://www.hybrid-analysis.com/sample/64b0b58a2c030c77fdb2b537b2fcc4af432bc55ffb36599a31d418c7c69e94b1?environmentId=100\n",
    "  tags:\n",
    "  - attack.execution\n",
    "  - attack.credential_access\n",
    "  - attack.defense_evasion\n",
    "  - attack.t1085\n",
    "  - attack.t1070\n",
    "  - attack.t1003\n",
    "  - car.2016-04-002\n",
    "  logsource:\n",
    "    category: process_creation\n",
    "    product: windows\n",
    "    service: null\n",
    "  detection:\n",
    "    pipe_com:\n",
    "      CommandLine: '*\\AppData\\Local\\Temp\\\\* \\\\.\\pipe\\\\*'\n",
    "    rundll32_dash1:\n",
    "      Image: '*\\rundll32.exe'\n",
    "      CommandLine: '*.dat,#1'\n",
    "    perfc_keyword:\n",
    "    - '*\\perfc.dat*'\n",
    "    condition: 1 of them\n",
    "  fields:\n",
    "  - CommandLine\n",
    "  - ParentCommandLine\n",
    "  falsepositives:\n",
    "  - Admin activity\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:*\\\\AppData\\\\Local\\\\Temp\\\\*\\ \\\\.\\\\pipe\\\\* OR (process_path.keyword:*\\\\rundll32.exe AND process_command_line.keyword:*.dat,#1) OR *\\\\perfc.dat*)')\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()"
   ]
  }
 ],
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 "nbformat": 4,
 "nbformat_minor": 4
}