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Securing NoSQL Clusters

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(1)

Presents

Securing NoSQL Clusters

Adrian Lane, CTO

[email protected] Twitter: @AdrianLane

David Mortman

[email protected] Twitter: @

(2)

About Securosis

Independent analysts with backgrounds on

both the user and vendor side.

Focused on deep technical and industry

expertise.

We like pragmatic.

(3)

The Research

How does big data help with security

analytics?

and

(4)

Encyclopedic

Hutton and the Big

(5)

Management: “Get it done!”

More data of more types

Need forensics

Need to determine risk

Need to detect fraud

Need to detect intrusions

Need to protect this data

(6)

Shock/Denial

Security analytics not working!

My systems won’t do the

forensics

Bolt-ons not working with my

SIEM or data management systems

Won’t collect the data types I

(7)

Why Doesn't my

SIEM do this?

Isn’t that what I

(8)
(9)

Not really ...

Most SIEM’s can’t handle the volume of

data

Most SIEMs can’t process all data types

Many based upon RDBMS

(10)

No problem!

I’ll buy a security analytics

platform

Feed event data in

Correlate across my SIEM and

data warehouse

Use my existing policies and

reports!

(11)

Anger

(12)

SIEM Mashup

An#$Fraud*&* 3rd*Party*Analy#cs*

General*Purpose* Analy#cs* DIY*“Big*Data”*

MSP*&*3rd*Party*

Monitoring*

Threat*Intelligence*

SIEM%

Advanced*Malware* Protec#on*

(13)

Security Analytics Platforms

Each deals with one use case - customers have

several

Companies need structured, unstructured and

semi-structured data analysis

Use different platforms internally, some

piggy-back on select SIEM, some are standalone

Real time _or_ forensic, not both

Vendors offer one or two analysis approach

(14)

Bargaining

(15)

The Inevitable Questions:

Bunch of previously acquired technologies - how

do we fit them together?

What is the rest of the industry doing?

Where are the enterprise grade analytics tools?

Who handles fraud and risk and security

intelligence and threat analytics?

(16)

Encyclopedia Hutton Asks

Friends For Advice

(17)

DIY Security Analytics!

Use ‘Big Data’ - it scales

It handles many types of data

You can customize as you see

fit

It’s designed to support

(18)

Hadoop let’s you do all this and more - virtually free

analytics tools on commodity hardware!

(19)

Big Data Will

Save The

Day!

(20)

How does big data help?

Performance

Scalability

Data volume

Data types

Fast lookup or fast analysis

(21)

Depression

Build everything from scratch?

Do you know how much this

will cost?

All new software

All new systems

Data architect, statisticians

and security pro’s

(22)

Big Data is Supposed to

Address My Problems

(23)

Getting control is not easy

I don’t know what I don’t know!

What pieces do I need?

How do I organize data?

How will I manage something this

complex?

How do I secure this critical

(24)

It’s all new

Pig? Hive? Flume?

What does it mean?

What exactly is a

data architect?

It’s not SQL?

Can I run queries

across databases?

How does it scale?

Key data on what

values?

(25)

NoSQL Cluster Architecture

Node% Manager% Node% Manager% Node% Manager% Resource% Manager% Data$ Data$ Data$ Data$ App$ App$ Client$ Client$ Client%Job%Request% Node%Status% Resource%Request% M7R%Status%

(26)
(27)

Talent Gap

http://flic.kr/p/efqfy9

Early days for big data

No in-house data scientist

Programmers needed

Just figuring out what we can

do with NoSQL

DIY Analytics

Today vendors don’t know

(28)

Integration Issues

APIs inconsistent/unavailable

Log Management & data collection

(29)

Acceptance

Taking on the task that is

security analytics with big data.

Realizing that platforms like

Hadoop are first step

Cluster Security can be done

With the right skills, that can

(30)
(31)

Applied Big Data

Start with Metrics

Build a model (aka have a theory)

Test it!

(32)

GQM

Goal

Question

(33)

Example - NIST CSF

ID.AM: The data, personnel, devices,

systems, and facilities that enable the

organization to achieve business

purposes are identified and managed

consistent with their relative

importance to business objectives

and the organization’s risk strategy.

(34)

Example - NIST CSF

Are network ingress points documented?

Are network egress points mapped?

(35)

Example - NIST CSF

# Undocumented Ingress points

# Undocumented egress points # of Undocumented Data Flows

% business units/business processes/etc. without data flow diagrams

(36)

SIRA - NIST CSF

(37)

Different Flavors of NoSQL

•  Hadoop - Universal M-R for huge data sets.

Great for search, log analysis, ad-hoc queries.

•  Cassandra - Columnar store. Indexed. Best for

writing lots of data quickly, few lookups. Highly distributable.

•  CouchDB - General purpose analytics database.

Fast insert/few changes. Pre-defined queries.

•  RIAK - Super-fast data lookup - like Dynamo -

but with data management and scalability. Control system logs and fast devices.

(38)

Operational Issues

Data at Rest Admin Access

Config. Management Monitoring

Node & App Validation

(39)

Big Data Security

Architectures

(40)
(41)
(42)

Model 1: Walled Garden

Think Mainframe security silo

Basically hide the cluster behind firewall

User passwords

(43)

Beyond the Status Quo

(44)
(45)

Model 2: App Protected

Authenticate Applications

Authenticate Users

Authorize data access (roles)

Filter API requests

(46)

Model 3: Data Centric Approach

(47)

Securosis Data Breach

Triangle

Data

Expl

oi

t

Eg

res

(48)
(49)

Model 3: Data Centric Approach

Protect data before it’s put into cluster

Can’t steal what’s not there

Removal: Masking

Removal: Tokenization

(50)

Model 4: Deploy in ‘The

Cloud’

(51)

Given general knowledge of

Cloud & NoSQL security,

some of you are thinking this

does not end well

(52)
(53)

Reality is different

u Security Zones u Data Encryption u Built-in SSL

u Authentication

u Hyper-segregation u Logging, monitoring

(54)

Model 4: Leverage Cloud Security

Data encryption (SSL, encrypted storage)

Key management services

Security zones

Authentication services

Server management (config, patch)

(55)

Easy? No.

Big Data Security is not easy

- Complex environments - No clear definition

- Lots of new research - Pragmatic approach - Many more issues

(56)

Adrian Lane

Securosis, L.L.C.

David Mortman

References

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