Null Bachaav - May 07 Attack Monitoring workshop.

transcript

Attack Monitoring Using ELK

@Null Bachav

@prajalkulkarni @mehimansu

Workshop agenda

•Overview & Architecture of ELK

•Setting up & configuring ELK

•Filebeat - Setting Up Centralized Logging

•How bad is DDoS?

Workshop agenda

• Understanding Kibana Dashboard

•Internal Alerting And Attack monitoring - osquery

● ELK pre-installed

● Custom scripts/config/plugins

● Nikto, Hping3

What your vm contains?

Elasticsearch

bin: /usr/share/elasticsearch/bin/elasticsearch

config: /etc/elasticsearch/elasticsearch.yml

Logstash

bin: /opt/logstash/bin/logstash

config: /etc/logstash/conf.d/*.conf

Kibana

bin: /opt/kibana/bin/kibana

config: /opt/kibana/config/*

Filebeat

bin: /usr/bin/filebeat/

config: /etc/filebeat/filebeat.yml

Osquery

config: /etc/osquery/osquery.conf

ElastAlert

Python: /home/elk/elastalert-master/elastalert/elastalert.py

Know your VM!

Why ELK?

Why ELK?Old School

● grep/sed/awk/cut/sort

● manually analyze the output

ELK● define endpoints(input/output)

● correlate patterns

● store data(search and visualize)

● Symantec Security Information Manager● Splunk● HP/Arcsight● Tripwire● NetIQ● Quest Software● IBM/Q1 Labs● Novell● Enterprise Security Manager● Alienvault

Other SIEM Market Solutions!

History of ElasticSearch!

- Developed by Shay banon- Version 1 was called as Compass -2004- Fully Developed over apache Lucene!- Necessity to scale Compass resulted in rewriting

most of its code and renaming it to ElasticSearch!- Version 1 was released in 2010

- Raised first Funding in 2014 !

Apache Lucene!

- Free open source search engine library written in java

- Author : Doug Cutting- Were mostly used or still in use by many ecom

websites.- Useful in optimizing speed and performance in

finding relevant docs on every search query.- An index of 10K documents can be queried within

milliseconds

ElasticSearch Installation

$ sudo add-apt-repository -y ppa:webupd8team/java$ sudo apt-get update$ sudo apt-get -y install oracle-java8-installer

$ wget https://download.elasticsearch.org/elasticsearch/release/org/elasticsearch/distribution/deb/elasticsearch/2.2.0/elasticsearch-2.2.0.deb

Overview of Elasticsearch

•Open source search server written in Java, over Apache lucene library.

•Used to index any kind of heterogeneous data

•Enables real-time ability to search through index

•Has a REST API web-interface with JSON output

Terminologies of Elasticsearch!

Cluster

● A cluster is a collection of one or more nodes (servers) that together holds your entire data and provides federated indexing and search capabilities across all nodes

● A cluster is identified by a unique name which by default is "elasticsearch"

● It is an elasticsearch instance (a java process)

● A node is created when a elasticsearch instance is started

● A random Marvel Charater name is allocated by default

● An index is a collection of documents that have somewhat similar characteristics. eg:customer data, product catalog

● Very crucial while performing indexing, search, update, and delete operations against the documents in it

● One can define as many indexes in one single cluster

Document

● It is the most basic unit of information which can be indexed

● It is expressed in json (key:value) pair. ‘{“user”:”nullcon”}’

● Every Document gets associated with a type and a unique id.

● Every index can be split into multiple shards to be able to distribute data.● The shard is the atomic part of an index, which can be distributed over the cluster if you

add more nodes.● By default 5 primary shards and 1 replica shards are created while starting elasticsearch

____ ____ | 1 | | 2 | | 3 | | 4 | | 5 | |____| |____|

● Atleast 2 Nodes are required for replicas to be created

edit elasticsearch.yml

$ sudo nano /etc/elasticsearch/elasticsearch.yml

ctrl+w search for ”cluster.name”

Change the cluster name to elastic_yourname

ctrl+x Y

Now start ElasticSearch sudo service elasticsearch restart

Verifying Elasticsearch Installation

$curl –XGET http://localhost:9200Expected Output:

{ "status" : 200, "name" : "Edwin Jarvis", "cluster_name" : "elastic_yourname", "version" : {

"number" : "2.2.0","build_hash" : "927caff6f05403e936c20bf4529f144f0c89fd8c","build_timestamp" : "2016-1-27T14:11:12Z","build_snapshot" : false,"lucene_version" : "5.4.1"

}, "tagline" : "You Know, for Search"}

Plugins of Elasticsearch

head./plugin install mobz/elasticsearch-head

HQ./plugin install royrusso/elasticsearch-HQ

Restful API’s over http -- !help curlcurl -X<VERB> '<PROTOCOL>://<HOST>/<PATH>?<QUERY_STRING>' -d '<BODY>'

● VERB-The appropriate HTTP method or verb: GET, POST, PUT, HEAD, or DELETE.● PROTOCOL-Either http or https (if you have an https proxy in front of Elasticsearch.)● HOST-The hostname of any node in your Elasticsearch cluster, or localhost for a node on your

local machine.● PORT-The port running the Elasticsearch HTTP service, which defaults to 9200.● QUERY_STRING-Any optional query-string parameters (for example ?pretty will pretty-print

the JSON response to make it easier to read.)● BODY-A JSON encoded request body (if the request needs one.)

!help curlSimple Index Creation with XPUT:

curl -XPUT 'http://IP:9200/twitter/'

Add data to your created index:

curl -XPUT 'http://IP:9200/twitter/tweet/1' -d '{"user":"nullmeet"}'

Now check the Index status:

curl -XGET 'http://IP:9200/twitter/?pretty=true'

List all Indices in ES Instance:

curl -XGET 'http://IP:9200/_cat/indices?v'Check the shard status:curl -XGET 'http://IP:9200/twitter/_search_shards'

!help curlAutomatic doc creation in an index with XPOST:

curl -XPOST 'http://IP:9200/twitter/tweet/' -d '{"user":"nullcon"}'

Creating a user profile doc:

curl -XPUT 'http://IP:9200/twitter/tweet/9' -d '{"user":"admin", "role":"tester", "sex":"male"}'

curl -XPOST 'http://IP:9200/twitter/tester/' -d '{"user":"abcd", "role":"tester", "sex":"male"}'

curl -XPOST 'http://IP:9200/twitter/tester/' -d '{"user":"abcd", "role":"admin", "sex":"male"}'

Searching in ElasticSearch:

$ curl -XGET 'http://IP:9200/twitter/_search?q=user:abcd&pretty=true'

The Power of “Explain”

$ curl -XGET 'http://IP:9200/twitter/_search?q=user:abcd&explain&pretty=true'

!help curl

!help curlDeleting an doc in an index:$curl -XDELETE 'http://IP:9200/twitter/tweet/1'

Deleting the whole Index:$curl -XDELETE 'http://IP:9200/index_name/'

Cluster Health: (yellow to green)/ Significance of colours (green/yellow/red)$curl -XGET 'http://IP:9200/_cluster/health?pretty=true'

$./elasticsearch -D es.config=../config/elasticsearch2.yml &

Overview of Logstash

•Framework for managing logs•Founded by Jordan Sissel•Mainly consists of 3 components:● input : passing logs to process them into machine understandable

format(file,lumberjack,beat).

● filters: set of conditionals to perform specific action on a event(grok,geoip).

● output: decision maker for processed event/log(elasticsearch,file)

Logstash Configuration

● Managing events and logs● Collect data ● Parse data● Enrich data

● Store data (search and visualizing)

} input

} filter

} output

Logstash Input Plugins

collectd drupal_dblog elasticsearcheventlog exec file ganglia gelf gemfiregenerator graphite heroku imap irc jmx

log4j beat pipe puppet_facterrabbitmq redis relp s3 snmptrap sqlitesqs stdin stomp syslog tcp twitter udpunix varnishlog websocket wmi xmpp

zenoss zeromq

Logstash Filter Plugins

advisor, alter, anonymize, checksum, cidr, cipher, clone, collate, csv, date, dns, drop, elapsed, elasticsearch, environment, extractnumbers, fingerprint, gelfify, geoip, grep, grok, grokdiscovery, i18n, json, json_encode, kv, metaevent, metrics, multiline, mutate, noop, prune, punct, railsparallelrequest, range, ruby, sleep, split, sumnumbers, syslog_pri, throttle, translate, unique, urldecode, useragent, uuid, wms, wmts, xml, zeromq

Logstash output Plugins

boundary circonus cloudwatch csv datadogelasticsearch exec email file ganglia gelf

gemfire google_bigquery google_cloud_storagegraphite graphtastic hipchat http irc jira

juggernaut librato loggly lumberjackmetriccatcher mongodb nagios null opentsdb

pagerduty pipe rabbitmq redis riak riemann s3sns solr_http sqs statsd stdout stomp syslog

tcp udp websocket xmpp zabbix zeromq

Installing & Configuring Logstash

$wget https://download.elastic.co/logstash/logstash/packages/debian/logstash_2.2.2-1_all.deb

$dpkg -i logstash_2.2.2-1_all.deb

•Starting logstash! --- /opt/logstash/bin

$ sudo ./logstash -f [Location].conf

•Lets start the most basic setup

…continued

run this!

./logstash -e 'input { stdin { } } output {elasticsearch {hosts => ["IP:9200"] } }'

Check head pluginhttp://IP:9200/_plugin/head

Setup - Apache access.log

input { file {

path => "/var/log/apache2/access.log" type => "apache" }}

output { elasticsearch { hosts => ["IP:9200"] } stdout { codec => json }}

Apache logs!

Let’s do it for syslog!

2 File input configuration!input { file { path => "/var/log/syslog" type => "syslog" } file { path => "/var/log/apache2/access.log" type => "apache" }

}output { elasticsearch { hosts => ["IP:9200"] } stdout { codec => rubydebug }

Logstash Filters!!input {

file { path => "/var/log/apache2/access.log"

type => "apache" }}

filter { grok {

match => { "message" => "%{COMBINEDAPACHELOG}" } }

output { elasticsearch { hosts => ["IP:9200"] } stdout { codec => json }}

•Powerful front-end dashboard for visualizing indexed information from elastic cluster.

•Capable to providing historical data in form of graphs,charts,etc.

•Enables real-time search of indexed information.

Overview of Kibana

./start Kibana wget -qO - https://packages.elastic.co/GPG-KEY-elasticsearch | sudo apt-key add - echo "deb http://packages.elastic.co/kibana/4.4/debian stable main" | sudo tee -a /etc/apt/sources.list sudo apt-get update && sudo apt-get install kibana

sudo service kibana start

Basic ELK Setup

Understanding Grok

Why grok?

actual regex to parse apache logs

Grok 101

•Understanding grok nomenclature.

•The syntax for a grok pattern is %{SYNTAX:SEMANTIC}•SYNTAX is the name of the pattern that will match your text.● E.g 1337 will be matched by the NUMBER pattern, 254.254.254

will be matched by the IP pattern.•SEMANTIC is the identifier you give to the piece of text being matched.● E.g. 1337 could be the count and 254.254.254 could be a client

making a request%{NUMBER:count} %{IP:client}

Grok 101…(continued)

• Common Grok Patterns:

• %{WORD:alphabet} e.g Nullcon

• %{INT:numeric} e.g. 1337

•%{NOTSPACE:pattern_until_space} e.g. Nullcon Goa

•%{GREEDYDATA:anything} e.g. $Nullcon@Goa_2016

Grok 101…(continued)

Let’s work out GROK for below:

● 192.168.1.101

● 192.168.1.101:8080

● [15:30:00]

● [03/08/2016]

● [08/March/2016:14:12:13 +0000]

Playing with grok filters

•Apache access.log event:

123.249.19.22 - - [08/Mar/2016:14:12:13 +0000] "GET /manager/html HTTP/1.1" 404 448 "-" "Mozilla/3.0 (compatible; Indy Library)"

•Matching grok:

%{IPV4} %{USER:ident} %{USER:auth} \[%{HTTPDATE:timestamp}\] "(?:%{WORD:verb} %{NOTSPACE:request}(?: HTTP/%{NUMBER:httpversion})?)" %{NUMBER:response} (?:%{NUMBER:bytes}|-)

•Things can get even more simpler using grok:%{COMBINEDAPACHELOG}

Logstash V/S Fluentd

fluentd conf file

<source> type tail path /var/log/nginx/access.log pos_file /var/log/td-agent/kibana.log.pos format nginx tag nginx.access</source>

Introducing filebeat!

Log Forwarding using filebeat

How to install filebeat

$ wget https://download.elastic.co/beats/filebeat/filebeat_1.1.1_amd64.deb

$ sudo dpkg -i filebeat_1.1.1_amd64.deb

$ sudo service filbeat start

Shippers and Indexers!

#### Filebeat ####filebeat: prospectors: - paths: - /var/log/apache2/access.log input_type: log document_type: beat registry_file: /var/lib/filebeat/registry#### Output ####output: ### Logstash as output logstash: hosts: ["INDEXER-IP:5044"]

#### Logging #####logging: to_files: true files:

path: /var/log/filebeatname: filebeatrotateeverybytes: 10485760 # = 10MB

level: error

filebeat-shipper Setup$sudo nano /etc/filebeat/filebeat.yml

logstash server(indexer) config -/etc/logstash/beat_indexer.conf

input { beats { port => 5044 } }

filter { if [type] == "beat" { grok { match => { "message" => "%{COMBINEDAPACHELOG}" } } date { match => [ "timestamp" , "dd/MMM/yyyy:HH:mm:ss Z" ] } } }

output { elasticsearch { hosts => ["localhost:9200"] } }

How Does your company mitigate DoS?

Identifying DoS patterns

-Identifying DoS patterns is trivial.

- Any traffic that tends to exhaust your connection pool would result in DoS.

- Traffic need not be volumetric

DoS Examples!

-Layer 7 attacks:-Slowloris : GET /index.php HTTP/1.1[CRLF]-SlowRead : syn->syn,ack->ack->{win:98bytes}-XMLRPC Attack

-Layer 4 attacks: -SynFlood

-Zero window scan {window size: 0}-Amplification attacks

Logs to Rescue● "HEAD / HTTP/1.1" 301 5.000 0 "-" "-" - -

● "GET / HTTP/1.1" 408 0 "-" "-"

● **SYN Flood to Host** SourceIP, 3350->> DestIP, 80

● SourceIP - - [09/Mar/2014:11:05:27 -0400] "GET /?4137049=6431829 HTTP/1.0" 403 0 "-" "WordPress/3.8; http://www.victim.com"

DNS Reflection attack!

$ dig ANY @RougeOpenDNSIP +edns=0 +notcp +bufsize=4096

+ Spoofing N/w

http://map.norsecorp.com/

SynFlood Demo

hping3

Attacker:$ sudo hping3 -i u1 -S -p 80 192.168.1.1

Victim:$ tcpdump -n -i eth0 'tcp[13] & 2 !=0'

IDS - IPS Solutions in the MarketProduct Speeds Available

Cisco IPS 4200 Sensor 1 Gbps, 600 Mbps, 250 Mbps, 80 Mbps

IBM Proventia Network Intrusion Prevention System

2 Gbps, 1.2 Gbps, 400 Mbps, 200 Mbps

McAfee’s IntruShield Network IPS 2 Gbps, 1 Gbps, 600 Mbps, 200 Mbps, 100 Mbps

Reflex Security 10 Gbps, 5 Gbps, 1 Gpbs, 200 Mbps, 100 Mbps, 30 Mbps, 10 Mbps

Juniper Networks IDP 1 Gbps, 500 Mbps; 250 Mbps; 50 Mbps

More Use cases - ModSecurity Alerts

modsec_audit.log!!

Logtash grok to rescue!

https://github.com/bitsofinfo/logstash-modsecurity

Kibana Overview

● Queries ES instance

● Visualization capabilities on top of the content indexed on an Elasticsearch cluster.

● create bar, line and scatter plots, or pie charts and maps on top of large volumes

First view of Kibana

Settings tab

Kibana Dashboard Demo!!

Discover - Overview of all Data pumped into ES InstanceVisualize - Setup cool graphsDashboard - Arrange all visualizations, and make a sorted dashboard.Settings- Configure

● ES Instance● Indices● Fields

Discover Tab

Kibana - Visualizations

Different Visualizations

● Area Chart ● Data Table● Line Chart● Markdown Widget● Metric● Pie Chart● Tile Map● Vertical bar Chart

Kibana - Sample Visualization

X-Axis and Y-Axis Important Fields

Y Axis○ Count○ Average○ Unique Count○ Sum

X - Axis○ Date Histogram○ Filter○ Term○ Sum

Dashboard

● Collection of Visualizations

● Go to Dashboards, add Visualizations, Save.

● Repeat.

Kibana - Sample Dashboard

What Next?

Dashboards are cool - They show you everything. Wait What? They are lazy.

We need ALERTING 24 / 7 /365 days.

Basic Attack Alert!

How to alert?

Alert based on IP count / UA Count

Open monitor.py

An ELK architecture for Security Monitoring & Alerting

Overview

•Alerting Framework for ElasticSearch Events•Queries ES instance periodically•Checks for a Match•If match { create Alert;}•Supports Alerts on Kibana, Email, Command, JIRA, etc.•Highly Scalable

Flow Diagram - Elast Alert

Installation

git clone https://github.com/Yelp/elastalert.git

mv config.yaml.example config.yaml

Modify config.yaml

pip install -r requirements.txt

python -m elastalert.elastalert --verbose --rule rules/frequency.yaml

Config.yaml – The backbone

Main configuration file for multiple settings.Key Value pair based configuration.

● ES_host● Buffer_time● Use_terms_query● Rules_folder● Run_every

Different Rule Types available● Frequency - X events in Y time.● Spike - rate of events increases or decreases.● Flatline - less than X events in Y time.● Blacklist / Whitelist - certain field matches a blacklist/whitelist.● Any - any event matching a given filter● Change - if field has two different values within some time.

Rules Config

● All rules reside in a folder.● Rules_folder in config.yaml● Important Configurations

○ type: Rule type to be used (eg. Frequency / spike / etc.)○ index: (eg. Logstash-*)○ filter: (eg. term: \n host:’xyzhostname’)○ num_events: (eg. 10)○ timeframe: [hours / minutes / seconds / days] (eg. Hours: 3)○ alert: (eg. Email / JIRA / Command / etc.)

So far we discussed about “external threats”, but what about “internal threats”?

Understanding osquery● Open source project from Facebook Security Team.

● osquery exposes an operating system as a lightweight, high-performance relational database.

● With osquery, your system acts as “database” and “tables” represents concepts as running process, packages installed, open network connections, etc...

● Two operational modes:○ osqueryi - CLI interface○ sudo service osquery restart - daemon service

Understanding osquery

● Tables power osquery, they represent OS details as SQL tables

Installing osquery$ sudo apt-key adv --keyserver keyserver.ubuntu.com --recv-keys 1484120AC4E9F8A1A577AEEE97A80C63C9D8B80B

$ sudo add-apt-repository "deb [arch=amd64] https://osquery-packages.s3.amazonaws.com/trusty trusty main"

$ sudo apt-get update

$ sudo apt-get install osquery

osqueryi

osqueryd - Run scheduled queries of tables$ sudo service osquery restart

$ cat /etc/osquery/osquery.conf

"schedule": {

"debpackages": { "query": "select name,version from deb_packages;", "interval": 10

},"total_processes": {

"query": "select name,pid from processes;", "interval": 10

},"ports_listening": {

"query": "select pid,port,address from listening_ports;", "interval": 10

Verify your osquery is workingOpen a terminal and type below:

$ sudo tailf /var/log/osquery/osqueryd.results.log

Open a new terminal and type below:

$ python -m SimpleHTTPServer

Go to your first terminal and verify the event from second terminal.

Thanks for your time!

Null Bachaav - May 07 Attack Monitoring workshop.

Engineering