Securing your web applications can be a daunting task, as attackers find different ways to exploit your web application or impact your availability. In this webinar (Level 300), we will share AWS Lambda scripts that you can use to automate security with AWS WAF (web application firewall) and write dynamic rules that can prevent HTTP floods, protect against bad-behaving IPs, and maintain IP reputation lists. You can also learn how Brazilian retailer, Magazine Luiza, leveraged AWS WAF and Lambda to protect its site and guaranteed an operationally smooth Black Friday. Objectives: • Learn how to use AWS WAF and Lambda together to automate security responses. • Get the Lambda scripts and CloudFormation templates that prevent HTTP floods, automatically block bad-behaving IPs, bad-behaving bots, and allow you to import and maintain publicly available IP reputation lists. • Gain an understanding of strategies for protecting your web applications using AWS WAF, CloudFront, and Lambda. Who Should Attend: IT Managers, Security Engineers, DevOps Engineers, Developers, Solution Architects, and Web Site Administrators

1. © 2016, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Nathan Dye
AWS WAF Software Development Manager
Gleicon Moraes, Magazine Luiza Infrastructure Manager
March 2, 2016
Using AWS WAF & Lambda for Automatic Protection

2. Agenda
WAF & Lambda Intro Security Automation Scripts & Templates Customer story

3. Web site without AWS WAF
Good users
Attackers
Web site
Exploit

4. Web site with AWS WAF
Good users
Web site
Exploit
Attackers

5. 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

6. 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

7. • 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?

8. Automated security
Good users
Logs Threat analysis
Rule updater
Web siteRules
Exploit
Attackers

9. Automated security – traditional data center
Good users
Logs Threat analysis
Rule updater
Web site
Exploit
Attackers
Rules

10. Automated security – AWS makes it easier
Good users
Logs Threat analysis
Rule updater
Web site
Exploit
Attackers
Rules

11. Other AWS Services we’ll use
Amazon CloudFront Amazon CloudWatch AWS CloudFormation
Amazon S3 Amazon API Gateway

12. Types of attacks that need automation
HTTP floods Scans & probesIP reputation lists Bots & scrapers
Attackers

13. 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, Spamhause, Tor Node list) and update lists
using CloudWatch events

14. IP reputation lists (cont’d)

15. IP reputation lists (cont’d)
<Example Demo>

16. 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

17. HTTP floods (cont’d)

18. HTTP floods (cont’d)
<Example Demo>

19. 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

20. Scans & probes (cont’d)
<Example Demo>

21. Bots & scrapers
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

22. Bots & scrapers (cont’d)

23. Bots & scrapers (cont’d)
<Example Demo>

24. 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

25. Customer story (cont’d)
Challenges
• Balance security with performance & cost
• Traditional WAFs didn’t work:
1. Inflated models – lots of rules & based on vm or hardware
2. Couldn’t scale - constrained by bandwidth & CPU
3. Automation meant more hardware
• Need to block bad bots (based on IP) without affecting search &
shopping experience
• Have solution in place by Black Friday

26. Customer story (cont’d)
Previous Architecture

27. Customer story (cont’d)
New Architecture

28. Customer story (cont’d)
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

29. Customer Story (cont’d)
Black Friday
• November 26: jumped from 4 – 28.9 million views/day
• November 26: all hands on deck for the last infrastructure scale.
• 12am: everyone went home, 5 people decided to sleep in our
leisure room, I kept following monitoring.
• November 27: Traffic started to ramp up around 6AM and stayed
high during the entire weekend.

30. Customer Story (cont’d)
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

31. Resources
Security Blogs
• Rate-Based Blacklisting Heitor Vital <heitorc@amazon.com>
• IPs Generating Errors Ben Potter <benpo@amazon.com>
• Blocking Bots (this month) Vlad Vlasceanu <vladv@amazon.com>
• Importing IP Reputation Lists (this month) Lee Atkinson
<leeatk@amazon.co.uk>
Tutorials Page
• aws.amazon.com/waf/preconfiguredrules/

32. Thank you!