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

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Suspicious WMI execution\n",
    "Detects WMI executing suspicious commands"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Rule Content\n",
    "```\n",
    "- title: Suspicious WMI execution\n",
    "  id: 526be59f-a573-4eea-b5f7-f0973207634d\n",
    "  status: experimental\n",
    "  description: Detects WMI executing suspicious commands\n",
    "  references:\n",
    "  - https://digital-forensics.sans.org/blog/2010/06/04/wmic-draft/\n",
    "  - https://www.hybrid-analysis.com/sample/4be06ecd234e2110bd615649fe4a6fa95403979acf889d7e45a78985eb50acf9?environmentId=1\n",
    "  - https://blog.malwarebytes.com/threat-analysis/2016/04/rokku-ransomware/\n",
    "  author: Michael Haag, Florian Roth, juju4\n",
    "  logsource:\n",
    "    category: process_creation\n",
    "    product: windows\n",
    "    service: null\n",
    "  detection:\n",
    "    selection:\n",
    "      Image:\n",
    "      - '*\\wmic.exe'\n",
    "      CommandLine:\n",
    "      - '*/NODE:*process call create *'\n",
    "      - '* path AntiVirusProduct get *'\n",
    "      - '* path FirewallProduct get *'\n",
    "      - '* shadowcopy delete *'\n",
    "    condition: selection\n",
    "  fields:\n",
    "  - CommandLine\n",
    "  - ParentCommandLine\n",
    "  tags:\n",
    "  - attack.execution\n",
    "  - attack.t1047\n",
    "  - car.2016-03-002\n",
    "  falsepositives:\n",
    "  - Will need to be tuned\n",
    "  - If using Splunk, I recommend | stats count by Computer,CommandLine following for\n",
    "    easy hunting by Computer/CommandLine.\n",
    "  level: medium\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_path.keyword:(*\\\\wmic.exe) AND process_command_line.keyword:(*\\/NODE\\:*process\\ call\\ create\\ * OR *\\ path\\ AntiVirusProduct\\ get\\ * OR *\\ path\\ FirewallProduct\\ get\\ * OR *\\ shadowcopy\\ delete\\ *))')\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
}