This document discusses using the ELK stack (Elasticsearch, Logstash, Kibana) for attack monitoring. It provides an overview of each component, describes how to set up ELK and configure Logstash for log collection and parsing. It also demonstrates log forwarding using Logstash Forwarder, and shows how to configure alerts and dashboards in Kibana for attack monitoring. Examples are given for parsing Apache logs and syslog using Grok filters in Logstash.

1. Attack Monitoring Using ELK
@Nullcon Goa 2015
@prajalkulkarni
@mehimansu

2. About Us
@prajalkulkarni
-Security Analyst @flipkart.com
-Interested in webapps, mobile, loves scripting in python
-Fan of cricket! and a wannabe guitarist!
@mehimansu
-Security Analyst @flipkart.com
-CTF Player - Team SegFault
-Interested in binaries, fuzzing

4. Today’s workshop agenda
•Overview & Architecture of ELK
•Setting up & configuring ELK
•Logstash forwarder
•Alerting And Attack monitoring

5. What does the vm contains?
● Extracted ELK Tar files in /opt/
● java version "1.7.0_76"
● Apache installed
● Logstash-forwarder package

6. Why ELK?

7. 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)

8. Other SIEM Market Solutions!
● Symantec Security Information Manager
● Splunk
● HP/Arcsight
● Tripwire
● NetIQ
● Quest Software
● IBM/Q1 Labs
● Novell
● Enterprise Security Manager

9. Overview of Elasticsearch
•Open source search server written in Java
•Used to index any kind of heterogeneous data
•Enables real-time ability to search through index
•Has REST API web-interface with JSON output

10. 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).
● filters: set of conditionals to perform specific action on a
event(grok,geoip).
● output: decision maker for processed event/log(elasticsearch,file)

11. •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

12. Basic ELK Setup

13. Let’s Setup ELK
Make sure about the update/dependencies!
$sudo apt-get update
$sudo add-apt-repository -y ppa:webupd8team/java
$sudo apt-get update
$sudo apt-get -y install oracle-java7-installer
$sudo apt-get install apache2

14. Installing Elasticsearch
$cd /opt
$curl –O
https://download.elasticsearch.org/elasticsearch/elasticsearch/elasticsea
rch-1.4.2.tar.gz
$tar -zxvf elasticsearch-1.4.2.tar.gz
$cd elasticsearch-1.4.2/

15. edit elasticsearch.yml
$sudo nano /opt/elasticsearch/config/elasticsearch.yml
ctrl+w search for ”cluster.name”
Change the cluster name to elastic_yourname
ctrl+x Y
Now start ElasticSearch sudo ./elasticsearch

16. Verifying Elasticsearch Installation
$curl –XGET http://localhost:9200
Expected Output:
{
"status" : 200,
"name" : "Edwin Jarvis",
"cluster_name" : "elastic_yourname",
"version" : {
"number" : "1.4.2",
"build_hash" : "927caff6f05403e936c20bf4529f144f0c89fd8c",
"build_timestamp" : "2014-12-16T14:11:12Z",
"build_snapshot" : false,
"lucene_version" : "4.10.2"
},
"tagline" : "You Know, for Search"
}

17. Terminologies of Elastic Search!
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"

18. Terminologies of Elastic Search!
Node
● 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

19. Terminologies of Elastic Search!
Index
● 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

20. 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.
Terminologies of Elastic Search!

21. Terminologies of Elastic Search!
Shard
● 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

23. Plugins of Elasticsearch
head
./plugin -install mobz/elasticsearch-head
HQ
./plugin -install royrusso/elasticsearch-HQ
Bigdesk
./plugin -install lukas-vlcek/bigdesk

24. Restful API’s over http -- !help curl
curl -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.)

25. !help curl
Simple Index Creation with XPUT:
curl -XPUT 'http://localhost:9200/twitter/'
Add data to your created index:
curl -XPUT 'http://localhost:9200/twitter/tweet/1' -d '{"user":"nullcon"}'
Now check the Index status:
curl -XGET 'http://localhost:9200/twitter/?pretty=true'

26. !help curl
Automatic doc creation in an index with XPOST:
curl -XPOST ‘http://localhost:9200/twitter/tweet/' -d ‘{“user”:”nullcon”}’
Creating a user profile doc:
curl -XPUT 'http://localhost:9200/twitter/tweet/9' -d '{"user”:”admin”, “role”:”tester”,
“sex”:"male"}'
Searching a doc in an index:
First create 2 docs:
curl -XPOST 'http://localhost:9200/twitter/tester/' -d '{"user":"abcd", "role":"tester",
"sex":"male"}'
curl -XPOST 'http://localhost:9200/twitter/tester/' -d '{"user":"abcd", "role":"admin",
"sex":"male"}'
curl -XGET 'http://localhost:9200/twitter/_search?q=user:abcd&pretty=true'

27. !help curl
Deleting an doc in an index:
$curl -XDELETE 'http://localhost:9200/twitter/tweet/1'
Cluster Health: (yellow to green)/ Significance of
colours(yellow/green/red)
$curl -XGET ‘http://localhost:9200/_cluster/health?pretty=true’
$./elasticsearch -D es.config=../config/elasticsearch2.yml &

28. Installing Kibana
$cd /var/www/html
$curl –O https://download.elasticsearch.org/kibana/kibana/kibana-
3.1.2.tar.gz
$tar –xzvf kibana-3.1.2.tar.gz
$mv kibana-3.1.2 kibana

29. Setting up Elasticsearch & Kibana
•Starting your elasticsearch server(default on 9200)
$cd /opt/elasticsearch-1.4.2/bin/
•Edit elasticsearch.yml and add below 2 lines:
● http.cors.enabled: true
● http.cors.allow-origin to the correct protocol, hostname, and port
For example, http://mycompany.com:8080, not
http://mycompany.com:8080/kibana.
$sudo ./elasticsearch &

31. Logstash Configuration
● Managing events and logs
● Collect data
● Parse data
● Enrich data
● Store data (search and
visualizing)
} input
} filter
} output

32. Logstash Input
collectd drupal_dblog elasticsearch
eventlog exec file ganglia gelf gemfire
generator graphite heroku imap irc jmx
log4j lumberjack pipe puppet_facter
rabbitmq redis relp s3 snmptrap sqlite
sqs stdin stomp syslog tcp twitter udp
unix varnishlog websocket wmi xmpp
zenoss zeromq

33. Logstash output!
boundary circonus cloudwatch csv datadog
elasticsearch exec email file ganglia gelf
gemfire google_bigquery google_cloud_storage
graphite graphtastic hipchat http irc jira
juggernaut librato loggly lumberjack
metriccatcher mongodb nagios null opentsdb
pagerduty pipe rabbitmq redis riak riemann s3
sns solr_http sqs statsd stdout stomp syslog
tcp udp websocket xmpp zabbix zeromq

34. Installing & Configuring Logstash
$cd /opt
$curl –O
https://download.elasticsearch.org/logstash/logstash/lo
gstash-1.4.2.tar.gz
$tar zxvf logstash-1.4.2.tar.gz

35. •Starting logstash
$cd /opt/logstash-1.4.2/bin/
•Lets start the most basic setup
… continued

36. run this!
./logstash -e 'input { stdin { } } output
{elasticsearch {host => localhost } }'
Check head plugin
http://localhost:9200/_plugin/head

37. ...continued
Setup - Apache access.log
input {
file {
path => [ "/var/log/apache2/access.log" ]
}
}
filter {
grok {
pattern => "%{COMBINEDAPACHELOG}"
}
}
output {
elasticsearch {
host => localhost
protocol => http
index => “indexname”
}
}

38. Now do it for syslog

39. Understanding Grok
Why grok?
actual regex to parse apache logs

40. Understanding Grok
•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}

41. Playing with grok filters
•GROK Playground: https://grokdebug.herokuapp.com/
•Apache access.log event:
123.249.19.22 - - [01/Feb/2015:14:12:13 +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}

42. Log Forwarding using logstash-forwarder

43. Logstash-Indexer Setup
$sudo mkdir -p /etc/pki/tls/certs
$sudo mkdir /etc/pki/tls/private
$cd /etc/pki/tls; sudo openssl req -x509 -batch -nodes -days 3650 -newkey
rsa:2048 -keyout private/logstash-forwarder.key -out certs/logstash-
forwarder.crt

44. logstash server(indexer) config
input {
lumberjack {
port => 5000
type => "apache-access"
ssl_certificate => "/etc/pki/tls/certs/logstash-forwarder.crt"
ssl_key => "/etc/pki/tls/private/logstash-forwarder.key"
}
}

45. Logstash-Shipper Setup
cp logstash-forwarder.crt /etc/pki/tls/certs/logstash-forwarder.crt
logstash-forwarder.conf
{
"network": {
"servers": [ "54.149.159.194:5000" ],
"timeout": 15,
"ssl ca": "/etc/pki/tls/certs/logstash-forwarder.crt"
},
"files": [
{
"paths": [
"/var/log/apache2/access.log"
]
}
]
}
./logstash-forwarder -config logstash-forwarder.conf

46. How Does your company mitigate DoS?

47. Logstash Alerting!
When to alert?
Alert based on IP count / UA Count

48. filter {
grok {
type => "elastic-cluster"
pattern => "%{COMBINEDAPACHELOG}"}
throttle {
before_count => 0
after_count => 5
period => 5
key => "%{clientip}"
add_tag => "throttled"
}
}
output {
if "throttled" in [tags] {
email {
from => "logstash@company.com"
subject => "Production System Alert"
to => "me.himansu@gmail.com"
via => "sendmail"
body => "Alert on %{host} from path
%{path}:nn%{message}"
options => { "location" =>
"/usr/sbin/sendmail" }
}
}
elasticsearch {
host => localhost
} }

49. More Use cases

50. modsec_audit.log!!

51. Logtash grok to rescue!
https://github.com/bitsofinfo/logstash-modsecurity

52. Logstash V/S Fluentd
credits:blog.deimos.fr

53. 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>

54. An ELK architecture for Security Monitoring & Alerting

55. Kibana Dashboard Demo!!

56. Open monitor.py

57. Thanks for your time!