Copyright © 2017 Splunk Inc.

Splunk User Group EdinburghAwesome Dashboarding & UF Vs. HFFebruary 2017

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Introduction - Harry McLaren● Alumnus of Edinburgh Napier● Senior Security Consultant at ECS – Role: Specialist Splunk Consultant & Enablement Lead– Specialism: Enterprise Security (SIEM) / Complex Deployments

● Splunk User Group Edinburgh: Leader / Founder

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Introduction to ECSStrategic Splunk Partner - UK – Type: Security / IT Operations / Managed Services– Awards: Splunk Revolution Award & Splunk Partner of the Year 2016

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Agenda

• Housekeeping: Overview & House Rules

• Presentation & Demo: Creating Awesome Dashboards

• Group Discussion: Sharing Dashboarding Tips & Tricks

• Presentation: Universal vs. Heavy vs. Intermediate Forwarders

• Group Discussion: Latest Splunk Challenges / Solutions

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Splunk [Official] User Group“The overall goal is to create an authentic, ongoing

user group experience for our users, where they contribute and get involved”

● User Lead Technical Discussions

● Sharing Environment

● Build Trust

● No Sales!

Creating Awesome DashboardsRobert Williamson

Robert Williamson

Alumnus of Edinburgh Napier university

IBM - Security Specialist

ECS - SOC Analyst, Senior SOC Analyst and Security Consultant

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What is a Dashboard?

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Creating a Dashboard

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Visualizations

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Table Formats

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Single Value – Colours

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Form Elements Within Panels

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Choropleth Maps

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I Could go on... But how is it done?

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Simple XML

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Dashboard Competition

Grab you phone and go to:http://splunk.com/shake

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Sharing Dashboarding Tips & TricksGroup Discussion

Universal Vs. Heavy ForwardersHarry McLarenBased on Darren Dance’s Blog

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Universal Vs. Heavy (+ Intermediate) Forwards

Universal Forwarder

HeavyForwarder

IntermediateForwarder

● Smallest Footprint● Standard Data Collection● Un-Parsed /

No Event Breaking

● Larger Footprint● Full Splunk Enterprise

Binary Install● Allows Filtering at

Source / In-Flight

● UF or HF Binaries● Aggregation Layer● Artificial Bottleneck● Performance Impact

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Heavy Forwarders Are[n’t] Awesome!The use of Heavy Forwarders were once commonly advised, but times change…

● Previous advice for using Heavy Forwarders – Filtering of data is best done at source and HF are required as UF cannot parse. – Use for aggregation layer for central management of data flows. ‣ Can cause data imbalance on the indexing tier that will reduce search performance.

● Reasons for NOT using Heavy Forwarder– Filter data at the Indexers. Greater use of compute resources / more performant.– Reduces network usage / IO by a significant degree. – Reduces the time from event generation to search availability. – Segmentation doesn’t always reduce threat vector for application exploitation.

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Artificial Bottleneck with IF

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Performance Impact Test Setup: File Contained 367,463,625 Events

Indexer Acknowledgement

Network Data Transferred (GB)

Network Speed Average (KBps)

Indexing Speed Average (KBps)

Duration (Secs)

HeavyYes 39.1 1,941 5,092 21,151

No 38.4 1,922 5,139 20,998

UniversalYes 6.5 863 14,344 7,923

No 6.4 1,015 17,466 6,662

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Performance Impact

Key Takeaways● The amount of data sent over the network was approximately 6 times

lower with the Universal Forwarder.● The amount of data indexed per second was approximately 3 times

higher when collected by a Universal Forwarder.● The total data set was indexed approximately 6 times quicker when

collected by the Universal Forwarder.

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Ideal Distribution with UF

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What About Network Segmentation?

● Limited Reduction to Application Threat Vector (UF > IF > IX)– If the Splunk software on the IF are vulnerable, then the same exploit could be

used to pivot into the next network layer anyway. ● Network Load

– If using a HF to aggregate the forwarder traffic, the additional network load could be upwards of 6x more than if UF directly to Indexers (Raw Vs. Parsed Data)

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Exceptions to UF > HFSome exceptions to using Universal Forwarders over Heavy Forwarders

● Special App Requirements – DB Connect / eStreamer / Opsec LEA / Etc.

● Modify In-Flight Events (Parsed Data Stream)– Change data before it leaves a specific environment (pattern replacement).

● Routing Based on Event Contents– Route data based on criteria such as source or type of event.

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Cloud Architecture

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Any Questions?

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Updates Announced at .conf 2016● Introducing Splunk Enterprise 6.5 - Available Now

‣ Splunk ML Toolkit: Guided workbench and SPL extensions to help you create and operationalize your own custom analytics based on your choice of algorithms.

‣ Tables: New feature that lets you create and analyse tabular data views without using SPL.

‣ Hadoop Data Roll: Gives you another way to reduce historical data storage costs while keeping full search capability.

● Premium Apps - New Releases:– Splunk Enterprise Security [Minor Release] – Splunk IT Service Intelligence [Major Release]– Splunk User Behaviour Analytics [Major Release]

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Get Involved!● Splunk User Group Edinburgh– https://usergroups.splunk.com/group/splunk-user-group-edinburgh.html– https://www.linkedin.com/groups/12013212

● Splunk’s Slack Group– Register via www.splunk402.com/chat – Channel: #edinburgh

● Present & Share at the User Group?Connect:‣ Harry McLaren | harry.mclaren@ecs.co.uk | @cyberharibu | harrymclaren.co.uk‣ ECS | enquiries@ecs.co.uk | @ECS_IT | ecs.co.uk

Thank You