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

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Network Sniffing\n",
    "Network sniffing refers to using the network interface on a system to monitor or capture information sent over a wired or wireless connection. An adversary may place a network interface into promiscuous mode to passively access data in transit over the network, or use span ports to capture a larger amount of data."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Rule Content\n",
    "```\n",
    "- title: Network Sniffing\n",
    "  id: f4d3748a-65d1-4806-bd23-e25728081d01\n",
    "  status: experimental\n",
    "  description: Network sniffing refers to using the network interface on a system\n",
    "    to monitor or capture information sent over a wired or wireless connection. An\n",
    "    adversary may place a network interface into promiscuous mode to passively access\n",
    "    data in transit over the network, or use span ports to capture a larger amount\n",
    "    of data.\n",
    "  author: Timur Zinniatullin, oscd.community\n",
    "  date: 2019/10/21\n",
    "  modified: 2019/11/04\n",
    "  references:\n",
    "  - https://github.com/redcanaryco/atomic-red-team/blob/master/atomics/T1040/T1040.yaml\n",
    "  logsource:\n",
    "    product: linux\n",
    "    service: auditd\n",
    "    category: null\n",
    "  detection:\n",
    "    selection1:\n",
    "      type: execve\n",
    "      a0: tcpdump\n",
    "      a1: -c\n",
    "      a3|contains: -i\n",
    "    selection2:\n",
    "      type: execve\n",
    "      a0: tshark\n",
    "      a1: -c\n",
    "      a3: -i\n",
    "    condition: selection1 or selection2\n",
    "  falsepositives:\n",
    "  - Legitimate administrator or user uses network sniffing tool for legitimate reason\n",
    "  level: low\n",
    "  tags:\n",
    "  - attack.credential_access\n",
    "  - attack.discovery\n",
    "  - attack.t1040\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='(type:\"execve\" AND a1:\"\\-c\" AND ((a0:\"tcpdump\" AND a3.keyword:*\\-i*) OR (a0:\"tshark\" AND a3:\"\\-i\")))')\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
}