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Point-of-Sale (POS)
Areas of Vulnerability
Data in
Memory
Data at Rest Data inTransit
Application
Code and
Configuration
1 2 3 4
Security Risk
 Data in Memory
Security concerns remain the same as those for device interfaces there are no standard security
mechanisms. Specific issues depend on the type of connectivity. If POS and PA run under the same
OS process, the memory of the process can be scanned using RAM scraping in order to retrieve
sensitive data.
Security Risk
Security Risk
 Data at Rest
“data at rest,” a term used to describe any form of hard-drive storage such as database, fl at-data
file, or log file.
Security Risk
 Data in Transit
There are different ways to “tap into the wire.” One of various sniffing attack scenarios would be a
hidden network tap device plugged into the store network. The tap device will catch the payment
application traffic and mirror it to the remote control center.
Security Risk
 Data in Transit
Security Risk
 Application Code and Configuration
Another key vulnerability area is payment Application Code itself and its Configuration (config). The
code or config don’t contain any cardholder information by themselves, but can be tampered by
attacker or malicious software in order to gain unauthorized access to the data in other key
vulnerability areas.
Exposure Area
Retail Store – POS Machine
POI Device
Payment
Application
Storage
Memory
POS App
Payment Processor Data Center
Payment
Processing Host
1
2
3
3
4
2
1
3
4
Data in memory
Data at rest
Data in Transit
App Code and Configuration
Pros and Cons
Some of the security pros and cons of this model are:
 Pro
 There’s no central location in the store that accumulates all the Sensitive data in memory, disk
storage, or network traffic. It is easier (and less expensive!) to protect a single machine and
application instance; however, once it is broken, all the store data is gone.
 The communication between POS and PA doesn’t carry sensitive data because PA handles all
the aspects of any payment transaction and only returns the masked results to the POS at the
end without exposing the details of the magnetic stripe.
 Con
 All POS machines (memory, data storage) at the store are exposed to sensitive data as well as
communication between the POS machine and the payment host.
The concept of EPS
 EPS stands for Electronic Payment System
 The main purpose of EPS is isolating the electronic payment processing application from the rest of
the point-of-sale functions.
 A logical (and often physical) separation of the POS and payment system allows “removing POS from
the scope” (security auditors terminology meaning that security standard requirements like PCI are
not applicable to a particular application or machine).
 Placing the POS application or machine “out of scope” saves a lot of Development and
implementation work for both software manufacturers and consumers
Store EPS Deployment Model
Retail Store
POI Device
Payment
Application
Storage
Memory
POS Payment
Processing Host
POS Machine Store Server
Payment
Processor
Data Center
2
1
3
4
Data in memory
Data at rest
Data in Transit
App Code and Configuration
1
2
4
3
3
Pros and Cons
Some of the security pros and cons of this model are:
 Pro
 The POS machine isn’t exposed to sensitive data because it doesn’t communicate with POI
devices.
 Communication between the POS and the store server machines doesn’t contain sensitive
data, so there’s no need to encrypt this traffic
 Con
 Communication between POI devices and the store server is implemented through the store
LAN (usually TCP/IP packets), exposing sensitive cardholder information to the network.
Hybrid POS/Store Deployment Model
Retail Store
Payment
Server App
Storage
Memory
POS
Payment
Processor
Data Center
Payment
Processing Host
POS App Store Server
Payment
Client App
POI Device
Memory
Storage
2
1
3
4
Data in memory
Data at rest
Data in Transit
App Code and Configuration
11
22
44
3
3
3
Pros and Cons
Some of the security pros and cons of this model are:
 Pro
 There are no security pros associated with this model.
 Con
 Both the POS and the store server machines and almost all their Components (memory, data
storage, application code, and communication lines) are entirely vulnerable.
Case Study: Pentesting POS
Retail Store
Payment
Processing Host
Counter/ POS Area Back-Office Area
Payment
Processor
Data Center
Storing Room
EPS
Case Study: Pentesting POS
Retail Store
Payment
Processing Host
Counter/ POS Area Back-Office Area
Payment
Processor
Data Center
Storing Room
Physical & Host Assessment
EPS
Case Study: Pentesting POS
 Physical & Host Assessment
 USB Drives, Keyboard and Mouse
 Hot-Key Shortcuts
 Randomly presses on touchscreen
 BIOS Configuration
 Reverse Engineering on Application [.Net]
 Directory Traversal on Application
Case Study: Pentesting POS
Retail Store
Payment
Processing Host
Counter/ POS Area Back-Office Area
Payment
Processor
Data Center
Storing Room
Network Segregation
&
Infrastructure Assessment
EPS
Case Study: Pentesting POS
 Network Segregation & Infrastructure Assessment
 Excessive Port on Device and Server
 Network Segmentation
 Password Reuse Rampant
 Pass-The-Hash
 Dump clear text passwords stored by
Windows authentication packages
Really !?
Case Study: Pentesting POS
Retail Store
Payment
Processing Host
Counter/ POS Area Back-Office Area
Payment
Processor
Data Center
Storing Room
Traffic Monitoring
EPS
Case Study: Pentesting POS
 Traffic Monitoring
 Identify PAN over the network.
 Sensitive information between SIT and EPS.
Protection
 Data in Memory
 Minimizing Data Exposure from the Application (.NET SecureString, Memory Buffer]
 Point-to-Point Encryption (P2PE), encrypt the data before it even reaches the memory of the
hosting machine, and decrypt it only after it has left the POS (in the Payment Gateway)
 Data in Transit
 Implementing Secure Socket Layer (SSL]
 Encrypted Tunnels, IPSec
 Data at Rest
 Avoiding the storage of sensitive data at all.
 Point-to-Point Encryption [P2PE]
 Symmetric Key Encryption
Thank you
 Recommended Book

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Point-Of-Sale Hacking - 2600Thailand#20

  • 1.
  • 3. Areas of Vulnerability Data in Memory Data at Rest Data inTransit Application Code and Configuration 1 2 3 4
  • 4. Security Risk  Data in Memory Security concerns remain the same as those for device interfaces there are no standard security mechanisms. Specific issues depend on the type of connectivity. If POS and PA run under the same OS process, the memory of the process can be scanned using RAM scraping in order to retrieve sensitive data.
  • 6. Security Risk  Data at Rest “data at rest,” a term used to describe any form of hard-drive storage such as database, fl at-data file, or log file.
  • 7. Security Risk  Data in Transit There are different ways to “tap into the wire.” One of various sniffing attack scenarios would be a hidden network tap device plugged into the store network. The tap device will catch the payment application traffic and mirror it to the remote control center.
  • 9. Security Risk  Application Code and Configuration Another key vulnerability area is payment Application Code itself and its Configuration (config). The code or config don’t contain any cardholder information by themselves, but can be tampered by attacker or malicious software in order to gain unauthorized access to the data in other key vulnerability areas.
  • 10. Exposure Area Retail Store – POS Machine POI Device Payment Application Storage Memory POS App Payment Processor Data Center Payment Processing Host 1 2 3 3 4 2 1 3 4 Data in memory Data at rest Data in Transit App Code and Configuration
  • 11. Pros and Cons Some of the security pros and cons of this model are:  Pro  There’s no central location in the store that accumulates all the Sensitive data in memory, disk storage, or network traffic. It is easier (and less expensive!) to protect a single machine and application instance; however, once it is broken, all the store data is gone.  The communication between POS and PA doesn’t carry sensitive data because PA handles all the aspects of any payment transaction and only returns the masked results to the POS at the end without exposing the details of the magnetic stripe.  Con  All POS machines (memory, data storage) at the store are exposed to sensitive data as well as communication between the POS machine and the payment host.
  • 12. The concept of EPS  EPS stands for Electronic Payment System  The main purpose of EPS is isolating the electronic payment processing application from the rest of the point-of-sale functions.  A logical (and often physical) separation of the POS and payment system allows “removing POS from the scope” (security auditors terminology meaning that security standard requirements like PCI are not applicable to a particular application or machine).  Placing the POS application or machine “out of scope” saves a lot of Development and implementation work for both software manufacturers and consumers
  • 13. Store EPS Deployment Model Retail Store POI Device Payment Application Storage Memory POS Payment Processing Host POS Machine Store Server Payment Processor Data Center 2 1 3 4 Data in memory Data at rest Data in Transit App Code and Configuration 1 2 4 3 3
  • 14. Pros and Cons Some of the security pros and cons of this model are:  Pro  The POS machine isn’t exposed to sensitive data because it doesn’t communicate with POI devices.  Communication between the POS and the store server machines doesn’t contain sensitive data, so there’s no need to encrypt this traffic  Con  Communication between POI devices and the store server is implemented through the store LAN (usually TCP/IP packets), exposing sensitive cardholder information to the network.
  • 15. Hybrid POS/Store Deployment Model Retail Store Payment Server App Storage Memory POS Payment Processor Data Center Payment Processing Host POS App Store Server Payment Client App POI Device Memory Storage 2 1 3 4 Data in memory Data at rest Data in Transit App Code and Configuration 11 22 44 3 3 3
  • 16. Pros and Cons Some of the security pros and cons of this model are:  Pro  There are no security pros associated with this model.  Con  Both the POS and the store server machines and almost all their Components (memory, data storage, application code, and communication lines) are entirely vulnerable.
  • 17. Case Study: Pentesting POS Retail Store Payment Processing Host Counter/ POS Area Back-Office Area Payment Processor Data Center Storing Room EPS
  • 18. Case Study: Pentesting POS Retail Store Payment Processing Host Counter/ POS Area Back-Office Area Payment Processor Data Center Storing Room Physical & Host Assessment EPS
  • 19. Case Study: Pentesting POS  Physical & Host Assessment  USB Drives, Keyboard and Mouse  Hot-Key Shortcuts  Randomly presses on touchscreen  BIOS Configuration  Reverse Engineering on Application [.Net]  Directory Traversal on Application
  • 20. Case Study: Pentesting POS Retail Store Payment Processing Host Counter/ POS Area Back-Office Area Payment Processor Data Center Storing Room Network Segregation & Infrastructure Assessment EPS
  • 21. Case Study: Pentesting POS  Network Segregation & Infrastructure Assessment  Excessive Port on Device and Server  Network Segmentation  Password Reuse Rampant  Pass-The-Hash  Dump clear text passwords stored by Windows authentication packages Really !?
  • 22. Case Study: Pentesting POS Retail Store Payment Processing Host Counter/ POS Area Back-Office Area Payment Processor Data Center Storing Room Traffic Monitoring EPS
  • 23. Case Study: Pentesting POS  Traffic Monitoring  Identify PAN over the network.  Sensitive information between SIT and EPS.
  • 24. Protection  Data in Memory  Minimizing Data Exposure from the Application (.NET SecureString, Memory Buffer]  Point-to-Point Encryption (P2PE), encrypt the data before it even reaches the memory of the hosting machine, and decrypt it only after it has left the POS (in the Payment Gateway)  Data in Transit  Implementing Secure Socket Layer (SSL]  Encrypted Tunnels, IPSec  Data at Rest  Avoiding the storage of sensitive data at all.  Point-to-Point Encryption [P2PE]  Symmetric Key Encryption