mirror of https://github.com/infosecn1nja/HELK.git
123 lines
2.5 KiB
Plaintext
123 lines
2.5 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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"# Relevant ClamAV Message\n",
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"Detects relevant ClamAV messages"
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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: Relevant ClamAV Message\n",
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" id: 36aa86ca-fd9d-4456-814e-d3b1b8e1e0bb\n",
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" description: Detects relevant ClamAV messages\n",
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" references:\n",
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" - https://github.com/ossec/ossec-hids/blob/master/etc/rules/clam_av_rules.xml\n",
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" logsource:\n",
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" product: linux\n",
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" service: clamav\n",
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" category: null\n",
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" detection:\n",
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" keywords:\n",
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" - Trojan*FOUND\n",
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" - VirTool*FOUND\n",
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" - Webshell*FOUND\n",
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" - Rootkit*FOUND\n",
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" - Htran*FOUND\n",
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" condition: keywords\n",
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" falsepositives:\n",
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" - Unknown\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:(*Trojan*FOUND* OR *VirTool*FOUND* OR *Webshell*FOUND* OR *Rootkit*FOUND* OR *Htran*FOUND*)')\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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