mirror of https://github.com/infosecn1nja/HELK.git
136 lines
3.4 KiB
Plaintext
136 lines
3.4 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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"# Emotet Process Creation\n",
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"Detects all Emotet like process executions that are not covered by the more generic rules"
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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: Emotet Process Creation\n",
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" id: d02e8cf5-6099-48cf-9bfc-1eec2d0c7b18\n",
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" status: experimental\n",
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" description: Detects all Emotet like process executions that are not covered by\n",
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" the more generic rules\n",
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" author: Florian Roth\n",
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" date: 2019/09/30\n",
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" modified: 2019/10/16\n",
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" references:\n",
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" - https://app.any.run/tasks/e13ab713-64cf-4b23-ad93-6dceaa5429ac/\n",
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" - https://app.any.run/tasks/81f3c28c-c686-425d-8a2b-a98198d244e1/\n",
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" - https://app.any.run/tasks/97f875e8-0e08-4328-815f-055e971ba754/\n",
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" logsource:\n",
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" category: process_creation\n",
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" product: windows\n",
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" service: null\n",
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" detection:\n",
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" selection:\n",
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" CommandLine:\n",
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" - '* -e* PAA*'\n",
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" - '*JABlAG4AdgA6AHUAcwBlAHIAcAByAG8AZgBpAGwAZQ*'\n",
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" - '*QAZQBuAHYAOgB1AHMAZQByAHAAcgBvAGYAaQBsAGUA*'\n",
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" - '*kAGUAbgB2ADoAdQBzAGUAcgBwAHIAbwBmAGkAbABlA*'\n",
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" - '*IgAoACcAKgAnACkAOwAkA*'\n",
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" - '*IAKAAnACoAJwApADsAJA*'\n",
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" - '*iACgAJwAqACcAKQA7ACQA*'\n",
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" condition: selection\n",
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" fields:\n",
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" - CommandLine\n",
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" - ParentCommandLine\n",
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" falsepositives:\n",
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" - Unlikely\n",
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" level: critical\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='process_command_line.keyword:(*\\ \\-e*\\ PAA* OR *JABlAG4AdgA6AHUAcwBlAHIAcAByAG8AZgBpAGwAZQ* OR *QAZQBuAHYAOgB1AHMAZQByAHAAcgBvAGYAaQBsAGUA* OR *kAGUAbgB2ADoAdQBzAGUAcgBwAHIAbwBmAGkAbABlA* OR *IgAoACcAKgAnACkAOwAkA* OR *IAKAAnACoAJwApADsAJA* OR *iACgAJwAqACcAKQA7ACQA*)')\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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