mirror of https://github.com/infosecn1nja/HELK.git
128 lines
2.7 KiB
Plaintext
128 lines
2.7 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Webshell Detection by Keyword\n",
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"Detects webshells that use GET requests by keyword searches in URL strings"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Rule Content\n",
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"```\n",
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"- title: Webshell Detection by Keyword\n",
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" id: 7ff9db12-1b94-4a79-ba68-a2402c5d6729\n",
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" description: Detects webshells that use GET requests by keyword searches in URL\n",
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" strings\n",
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" author: Florian Roth\n",
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" logsource:\n",
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" category: webserver\n",
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" product: null\n",
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" service: null\n",
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" detection:\n",
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" keywords:\n",
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" - =whoami\n",
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" - =net%20user\n",
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" - =cmd%20/c%20\n",
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" condition: keywords\n",
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" fields:\n",
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" - client_ip\n",
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" - vhost\n",
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" - url\n",
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" - response\n",
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" falsepositives:\n",
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" - Web sites like wikis with articles on os commands and pages that include the os\n",
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" commands in the URLs\n",
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" - User searches in search boxes of the respective website\n",
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" level: high\n",
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"\n",
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"```"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Querying Elasticsearch"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Import Libraries"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"from elasticsearch import Elasticsearch\n",
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"from elasticsearch_dsl import Search\n",
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"import pandas as pd"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Initialize Elasticsearch client"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"es = Elasticsearch(['http://helk-elasticsearch:9200'])\n",
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"searchContext = Search(using=es, index='logs-*', doc_type='doc')"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Run Elasticsearch Query"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"s = searchContext.query('query_string', query='\\*.keyword:(*\\=whoami* OR *\\=net%20user* OR *\\=cmd%20\\/c%20*)')\n",
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"response = s.execute()\n",
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"if response.success():\n",
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" df = pd.DataFrame((d.to_dict() for d in s.scan()))"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Show Results"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"df.head()"
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]
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}
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],
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"metadata": {},
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"nbformat": 4,
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"nbformat_minor": 4
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}
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