{ "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 }