22
Session ID: Session Classification: Jason Sloderbeck Silver Tail Systems, Part of RSA SPO1-W22 General Track CUSTOMERS & CRIMINALS: USE WEB SESSION INTELLIGENCE TO DETECT ‘WHO IS WHO’ ONLINE

Spo1 w22

Embed Size (px)

Citation preview

Page 1: Spo1 w22

Session ID:

Session Classification:

Jason Sloderbeck Silver Tail Systems, Part of RSA

SPO1-W22

General Track

CUSTOMERS & CRIMINALS: USE WEB SESSION INTELLIGENCE TO DETECT ‘WHO IS WHO’ ONLINE

Page 2: Spo1 w22

Do criminals in a retail store behave differently from typical customers?

Question

Page 3: Spo1 w22

Security Guard – stop

shoplifters

Cashier – Protect & Ensure sales

Security camera-

capture events

Shoplifter- Taking items

Price tag swapper-

Mis-representing prices

Retail Circa 2013

Page 4: Spo1 w22

Do criminals on your web site behave differently from typical customers?

Question

Page 5: Spo1 w22

The Web Has Evolved

Web Transaction vs Web Interaction

Page 6: Spo1 w22

Big Data Meets Web Sessions

Full Session Data • Click-by-click visibility • Entire HTTP request insight • Understand behavior

Just Logs • Limited transaction visibility • No traceability into behavior • Disconnected story

Page 7: Spo1 w22

Behavioral Analytics

Page 8: Spo1 w22

Population-based Behavior

Page 9: Spo1 w22

Man-in-the-Browser Attack

Criminals Look Different than Customers

• Velocity • Page Sequence • Origin • Contextual Information

Page 10: Spo1 w22

Business Logic Abuse

Page 11: Spo1 w22

► “Business logic abuse results … when a criminal uses the legitimate pages of the website to perpetrate cyber attacks, hacks or fraud.”

What is Business Logic Abuse?

Source: Ponemon Institute ‘The Risk of Business Logic Abuse: U.S. Study’ (September 2012)

Page 12: Spo1 w22

Scope of Business Logic Abuse

► Site Scraping ► Account Hijacking ► Password Guessing ► Pay-per-click Fraud ► Testing Stolen Credit Cards ► Denial of Service ► eCoupons

► eWallet Abuse ► App Store Abuse ► Mass Registration ► Fraudulent Money

Movement ► Vulnerability Probing

Page 13: Spo1 w22

Survey of US IT Executives

90% Report lost revenue due to Business

Logic Abuse

74% Can’t tell if a web session is a

customer or a criminal

64% No clear visibility into

their web session traffic

1/3 Do not know who is

responsible for addressing business logic abuse

Page 14: Spo1 w22

Real-world Examples

Page 15: Spo1 w22

Vulnerability Probing What were they doing?

► Jiggling doorknobs

► Probing for vulnerabilities ► Site reconnaissance

What looked suspicious?

► Sub-second clicks ► Modified user-agent strings ► Alphabetical page requests ► Multiple password reset attempts ► Requests for non-existent pages

Page 16: Spo1 w22

Horizontal Password Guessing

What was happening? ► Testing a common password e.g. Faceb00k!

What looked suspicious?

► Spike in login page hits ► Multiple login attempts with one

password ► Scripted variability ► Elevated behavior scores for

sessions driving the spike

Page 17: Spo1 w22

Mobile Account Penetration

What were they doing? ► Stealing credentials on public

WiFi from low-security mobile application

► Spoofing mobile user agents What looked suspicious? ► Cluster of IPs generated a high

behavior score ► Clickstream showed the same

cookie being used by two devices

Same Cookie

Different UA Strings

Page 18: Spo1 w22

Fraudulent Money Movement

What where they doing? ► Compromising accounts with malware ► Creating a virtual account number

(VAN) ► Receiving a new line of credit ► Maxing credit limit with fraudulent

purchases What looked suspicious?

► High Man-in-the-Middle score ► Fast clicks ► Multiple IP addresses in one session ► IPs traced to disparate geographies ► User-agent variation

Clickstream shows different IPs, UA strings and activities intermingled

Page 19: Spo1 w22

E-Commerce Fraud

The customer knew the “what”… ► Omniture reported revenue drop for affiliate

orders

Behavior exposed the “how” in minutes… ► Users added a sale item to their cart ► The sale price persisted in the cart after the

sale ended ► Users stacked the next promotion in their cart ► Inconsistent price floors were exploited ► Accepted orders were sub-floor or negative

value

New Seasonal Promotion

Cart Logic Flaw

Staring at a six-figure loss in an

Afternoon

Page 20: Spo1 w22

Session DDoS

What where they doing? ► Application resource exhaustion ► Botnets sending Search, Login New

Account, Purchase queries What looked suspicious?

► Device ID / User-Agent randomization

► Thousands of IP addresses were acting in concert

► Identical activity on a specific set of pages

Page 21: Spo1 w22

Spectrum of Threats

New Account Registration

Fraud

Account Takeover Password Guessing

Parameter Injection Man In The Browser

Man In The Middle Fraudulent Money

Movement

Unauthorized Account Activity

Promotion Abuse

High Risk Checkout

Site Scraping

Vulnerability Probing

DDOS Attacks

Beginning of Web Session

Login Transaction and Logout