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

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Antivirus Exploitation Framework Detection\n",
    "Detects a highly relevant Antivirus alert that reports an exploitation framework"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Rule Content\n",
    "```\n",
    "- title: Antivirus Exploitation Framework Detection\n",
    "  id: 238527ad-3c2c-4e4f-a1f6-92fd63adb864\n",
    "  description: Detects a highly relevant Antivirus alert that reports an exploitation\n",
    "    framework\n",
    "  date: 2018/09/09\n",
    "  modified: 2019/01/16\n",
    "  author: Florian Roth\n",
    "  references:\n",
    "  - https://www.nextron-systems.com/2018/09/08/antivirus-event-analysis-cheat-sheet-v1-4/\n",
    "  tags:\n",
    "  - attack.execution\n",
    "  - attack.t1203\n",
    "  - attack.command_and_control\n",
    "  - attack.t1219\n",
    "  logsource:\n",
    "    product: antivirus\n",
    "    service: null\n",
    "    category: null\n",
    "  detection:\n",
    "    selection:\n",
    "      Signature:\n",
    "      - '*MeteTool*'\n",
    "      - '*MPreter*'\n",
    "      - '*Meterpreter*'\n",
    "      - '*Metasploit*'\n",
    "      - '*PowerSploit*'\n",
    "      - '*CobaltSrike*'\n",
    "      - '*Swrort*'\n",
    "      - '*Rozena*'\n",
    "      - '*Backdoor.Cobalt*'\n",
    "    condition: selection\n",
    "  fields:\n",
    "  - FileName\n",
    "  - User\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='signature.keyword:(*MeteTool* OR *MPreter* OR *Meterpreter* OR *Metasploit* OR *PowerSploit* OR *CobaltSrike* OR *Swrort* OR *Rozena* OR *Backdoor.Cobalt*)')\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
}