AWS WAF

Tel Aviv Loft9 March 2016

Tom Witman, Business DevelopmentAWS Seattle

Today’s Agenda

AWS WAF OverviewAWS WAF with CloudFrontAWS WAF Automation with AWS LambdaCustomer Example / Use Case: Magazine Luiza

What is a WAF?

•A Web Application Firewall (WAF) is an appliance, server plugin, or software filter that applies a set of rules to HTTP traffic providing Layer 7 (application) protection

•WAFs Come in Four Flavors• Pure Play: stand alone appliance or software• CDN: bundled with Content Delivery Network• Load Balancer: bundled with a load balancer• Universal Threat Manager (UTM): catch-all for misc. security

What is AWS WAF?

Web application firewall (WAF) that gives you control over who (or what) can access your web applications.

• Full-feature API• Customizable security• Integrated with Amazon CloudFront - protection at the edge• Use cases: protection against exploits, abuse, and application

DDoS

Web site without AWS WAF

Good users

Attackers

Web siteExploit

Web site with Amazon CloudFront + AWS WAF

Good usersWeb site

Exploit

Attackers

CloudFrontAWS WAF

Amazon CloudFront, Amazon Route 53, and AWS WAF Locations54 CloudFront Edge Locations (PoPs), 38 Cities, 5 Continents

CloudFront

Amazon Route 53

AWS WAF

North AmericaCities: 15PoPs: 21

Ashburn, VA (3)Atlanta, GAChicago, IL

Dallas/Fort Worth, TX (2)Hayward, CA

Jacksonville, FLLos Angeles, CA (2)

Miami, FLNew York, NY (3)

Newark, NJPalo Alto, CASan Jose, CASeattle, WA

South Bend, INSt. Louis, MO

Amazon CloudFront, Amazon Route 53, and AWS WAF Locations54 CloudFront Edge Locations (PoPs), 38 Cities, 5 Continents

South AmericaCities: 2PoPs: 2

Rio de Janeiro, Brazil

São Paulo, Brazil

Europe / Middle East / Africa

Cities: 10PoPs: 16

Amsterdam, The Netherlands (2) Dublin, Ireland

Frankfurt, Germany (3)London, England (3)

Madrid, SpainMarseille, France

Milan, ItalyParis, France (2)

Stockholm, SwedenWarsaw, Poland

Asia PacificCities: 11PoPs: 15

Chennai, IndiaHong Kong, China (2)Manila, the PhilippinesMelbourne, Australia

Mumbai, IndiaOsaka, Japan

Seoul, Korea (2)Singapore (2)

Sydney, AustraliaTaipei, Taiwan

Tokyo, Japan (2)CloudFron

tAmazon Route 53

AWS WAF

Edge location

AWS Region

AWS WAF Set Up Questions

1. What do I want to take action on? (Conditions – IP / String Match Set / SQL injection match sets)

2. Should I block, allow, count? (Rules - Precedence / Rule / Action)

3. What sites/distributions need these rules? (CloudFront Distribution)

4. What should I call the container of these rules? (Web Access Control Lists – WebACLs)

5. How do I see if the rules are working? (Real Time Metrics, Sampled Web Requests)

AWS WAF: WebACLs

•WebACLs contain a set of conditions, rules, and actions.

•WebACLs are applied to one or many CloudFront distributions.

•WebACLs show you Real-Time Metrics & Sampled Web Requests for each rule.

AWS WAF: Conditions

Conditions are lists of criteria that identify components of web requests.Conditions include matching on the following:

• IP address i.e., /8, /16, /24, /32• Strings, i.e., URI, query string, header, etc.• SQL injection, i.e., looks for valid SQL

statements

Conditions are logically disjoined, i.e. “OR”.

/login?x=test%20Id=10%20AND=1

/login?x=test%27%20UNION%20ALL%20select%20NULL%20--

/login?x=test’ UNION ALL select NULL --

Transform: URL Decode

True

Match: SQL Injection

False

Match Conditions: SQLi

AWS WAF: Rules

Rules are sets of conditions with a predetermined action.Available actions are:

• Block• Allow• Count

Rules can logically join conditions, i.e., “AND”.Rules can be applied to many WebACLs.

AWS WAF: Resources

WebACLs: applied to CloudFront distributions today•Rule reusability: use one WebACL for all distributions•Flexibility: use individual WebACL for each distributionAWS Partners: developing integrations with AWS WAF

• Trend Mirco: Deep Security• GitHub: https://github.com/deep-security/aws-waf• Blog: http://aws.trendmicro.com/aws-waf-and-deep-security/

• Imperva: Threat Radar• Alert Logic: Web Security Manager

AWS WAF: Reporting & Logs

Real-Time Metrics (CloudWatch):• Blocked web requests• Allowed web requests• Counted web requests

Adjustments to rules in response to real time analysis.Time period can be adjusted by sliding graph end points or via filters.

AWS WAF: End to End Flow

1. Create WebACL2. Create Conditions

(IP, string match, SQL)

3. Create Rules and Actions (order, rule, action)

4. Associate WebACL to CloudFront distribution

5. Review and Deploy

AWS WAF: API & Data Types

API ActionsCreateDeleteGetListUpdate

Data Types• ChangeToken• ChangeTokenStatus• WebACL• IPSet• StringeMatchSet• SQLinjectionMatchSet• Rule

AWS WAF: APIs

1. Get Change Token – a change token can only be used once to make a change to WAF resources.

2. Use Token to Make a Change – provide the change token to the change request

3. Check Status Using Token – use token to determine the status of your changes. INSYNC means changes were propagated

© 2016, Amazon Web Services, Inc. or its Affiliates. All rights reserved.

AWS WAF + AWS Lambda = Automatic Protection

What is AWS Lambda?

Lambda automatically runs your code without requiring you to provision servers.• “Server-less” scripting; event driven actions• Integrated with other AWS services• Use cases: scheduled events, provisioning services,

and customer analysis

• Bad guys are adaptive and persistent• Better protection

• Integrate application specific or open-source data sources• Sophisticated out of band analysis

Why build automated security?

Automated security

Good users

Logs Threat analysis

Rule updater

Web siteRulesExploit

Attackers

Automated security – traditional data center

Good users

Logs Threat analysis

Rule updater

Web siteExploit

Attackers

Rules

Automated security – AWS makes it easier

Good users

Logs Threat analysis

Rule updater

Web siteExploit

Attackers

Rules

Other AWS Services we’ll use

Amazon CloudFront Amazon CloudWatch AWS CloudFormation

Amazon S3 Amazon API Gateway

Types of attacks that can be automated

HTTP floods Scans & probesIP reputation lists Bots & scrapers

Attackers

IP reputation lists

Collection of IP addresses with a bad reputation based on sending history• Open proxies or known hosts that send

spam/trojans/viruses• Constantly changing/updating• Solution: import open source lists (i.e., Emerging

Threats, SSL blacklist, Tor Node list) and update lists using CloudWatch events

IP reputation lists

HTTP Floods

Legitimate requests at a level that excessively consume web server resources• Requests targeted at expensive components, i.e.,

login, product search, etc.• Different than other types of flood attacks because

requests follow protocol.• Creates the problem of identifying attack from flash

crowd.• Solution: count number of requests in CloudFront

access logs and block offenders

Attackers

HTTP Floods

Scans & probes

Program that communicates with web application front end to identify potential vulnerabilities• Initiated by you – good; initiated by someone else –

bad• Someone (something) with bad intentions• Consume resources by requesting URLs that don’t

exist• Solution: count 40x error in access logs and block

offenders

Bots & scrappers

Software application that run automated tasks over the internet.• Good bots (search engines, weather, price

comparison) vs bad bots (scrape content, steal data, malware)

• Aggressive vs conservative days• Constantly changing/updating• Solution: use robots.txt and “honeypot” file to identify

& block offenders

Bots & scrappers

Customer Story

Magazine Luiza• One of the largest retail

chains in Brazil• More than 700 stores, 24K

staff, & 8 distribution centers• e-commerce platform

customers use for purchases• Moving “all in” to AWS over

the past 2-3 years• Breaking up monolithic app

Customer Story

Challenges• Balance security with performance & cost• Traditional WAFs didn’t work:

1. Inflated models – lots of rules & based on vm or hardware2. Couldn’t scale - constrained by bandwidth & CPU3. Automation meant more hardware

• Need to block bad bots (based on IP) without affecting search & shopping experience

• Have solution in place by Black Friday

Customer Story

Previous Architecture

Customer Story

New Architecture

Customer Story

Milestones Before Black Friday• September – October: confirmed new architecture and started

building.• October – new architecture ready to go• November – started countdown and moved over all production traffic

Customer Story

Black Friday• November 26: jumped from 4 to 28.9 million views/day• November 26 all hands on deck for the last infrastructure scale up!• All hands on deck until midnight, everyone went home, 5 people decided to

sleep in our leisure room, I kept following monitoring.• Traffic started to ramp up again November 27 6:00AM and kept high page

views and sales during the weekend.

Customer Story

Advice to Others• Do analysis in house & start small• Use the right library for the job• Identify what needs protection• Think about the time it takes to process logs• Defense in Depth: simple security rules at perimeter, complex

security rules closer to app

Conclusion

Types of Attacks that can be Automated• IP reputation lists• HTTP floods• Web probes & scans• Bots & scrappers

Thanks to our Solution Architects:• Heitor Vital, Ben Potter, Vlad Vlasceanu, and Lee Atkinson• Tutorials available on https://aws.amazon.com/waf/preconfiguredrules/

Thank you!