Web Application Firewall (WAF) RSA ® Conference 2013.

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Web Application Firewall (WAF) RSA ® Conference 2013

Transcript of Web Application Firewall (WAF) RSA ® Conference 2013.

Page 1: Web Application Firewall (WAF) RSA ® Conference 2013.

Web Application Firewall (WAF)

RSA® Conference 2013

Page 2: Web Application Firewall (WAF) RSA ® Conference 2013.

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The Cybercrime Landscape in 2013

Attacks have become more sophisticated...

…and easier to carry out

Source: hackmageddon.com/

…industry agnostic...

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Moving From Network to Application Layer

Target of Traditional DDoS Attacks

Network Layer

(Layers 3/4)

Application Layer

(Layer 7)

Where increasing number of attacks are focused

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Web Application Firewall Highlights

• Operates at the network edge – over 100,000 servers• Inspects requests and responses for malicious content and info leakage• Inspects packets to protect against attacks such as SQL Injections &

Cross-Site Scripts  • Configurable to log or block activities against policy• Protects organizations against application layer attacks propagated via

HTTP and HTTPS• Enables compliance with PCI DSS 1.2 section 6.6• Provides advanced rate controls (behavioral based protections) • Propagates quickly (~30 minutes)• Configured via portal

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Kona Security Solutions 2.0

•ModSecurity Rule Update• Core Rule Set 2.2.6• Legacy CRS support

•Akamai Common Rules • Based on Akamai’s unique view• 20 – 25% of internet traffic

•Advanced Rate Controls• Session-ID; Client-IP+User-Agent

•Rule Upgrade Wizard

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Appendix & Details

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Akamai Intelligent Platform™Deflecting Network Layer Attacks at the Edge

Network Layer attack mitigation Built-in protection is “always on” Only Port 80 (HTTP) or Port 443 (HTTPS) traffic

allowed on Platformo All other traffic dropped at the Akamai Edge

• Attack traffic never makes it onto Platform• Customer not charged for traffic dropped at Edge

o Absorbs attack requests without requiring identificationo Requires CNAME onto Akamai Intelligent Platform

Absorbs attacks through massive scale ~5.5 Tbps average throughput; up to 8Tbps Distribution of HTTP request traffic across 100,000+

servers; 1,100+ networks No re-routing, added latency, or point of failure

Examples of attacks types dropped at Akamai Edge UDP Fragments ICMP Floods SYN Floods ACK Floods RESET Floods UDP Floods

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Custom RulesWeb Application Firewall

Description WAF Custom Rules implemented

in Akamai metadata written by Akamai Professional Services

Rules are created and managed incustomer portal Rules are then associated with firewall policies and deployed with WAF in 45 minutes

The Result New rule logic can be built to handle

specific use cases for the customer Rules can be built that execute when

one or more baseline rules or rate control rules match

Output of application vulnerability products can be implemented as “virtual patches”

Advanced piping to user validation actions can be achieved (prioritization)

Page 10: Web Application Firewall (WAF) RSA ® Conference 2013.

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Custom RulesWeb Application Firewall

Description WAF Custom Rules implemented

in Akamai metadata written by Akamai Professional Services

Rules are created and managed incustomer portal Rules are then associated with firewall policies and deployed with WAF in 45 minutes

The Result New rule logic can be built to handle

specific use cases for the customer Rules can be built that execute when

one or more baseline rules or rate control rules match

Output of application vulnerability products can be implemented as “virtual patches”

Advanced piping to user validation actions can be achieved (prioritization)

Page 11: Web Application Firewall (WAF) RSA ® Conference 2013.

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Adaptive Rate ControlsMalicious Behavior Detection

Specify number of requests per second against a given URLo Controls requests based on behavior

pattern – not request structure• Use client IP address, session ID, cookies, etc.

Configure rate categories to control request rates against digital properties•Mitigate rate-based DDoS attacks

Statistics collected for 3 request phaseso Client Request – Client to Akamai Servero Forward Request – Akamai Server to Origino Forward Response – Origin to Akamai Server

Statistics collected allow us to ignore large proxies and pick out a malicious user hiding behind a proxy

Statistics collected allow for detection of pathological behavior by a cliento Request rate is excessive for any stageo Requests causing too many Origin errors

Page 12: Web Application Firewall (WAF) RSA ® Conference 2013.

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Adaptive Rate ControlsMalicious Behavior Detection

Specify number of requests per second against a given URLo Controls requests based on behavior

pattern – not request structure• Use client IP address, session ID, cookies, etc.

Configure rate categories to control request rates against digital properties•Mitigate rate-based DDoS attacks

Statistics collected for 3 request phaseso Client Request – Client to Akamai Servero Forward Request – Akamai Server to Origino Forward Response – Origin to Akamai Server

Statistics collected allow us to ignore large proxies and pick out a malicious user hiding behind a proxy

Statistics collected allow for detection of pathological behavior by a cliento Request rate is excessive for any stageo Requests causing too many Origin errors

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Security Monitor (1 of 3)

Timeline of Requests by Hour

Visual Display of Requests by Geography

Requests by WAF Message

Requests by WAF Tag

Requests by WAF Rule ID

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Security Monitor (2 of 3)

Multiple waysto display

request statistics

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Security Monitor (3 of 3)

Requests byClient IP address

Requests by City

ARLs beingattacked

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