1. Hacking The Trading Floor Gyan Chawdhary Session ID: HT2-304 Session Classification: Intermediate

2. Agenda 2 BRIEF HISTORY OF ECONOMIC HACKS APPLICATION ISSUES FIX ATTACKS

3. 3 Brief History of Economic Hacks

4. Brief History Of Security Compromises in the Banking Sector 4

5. More Recently … (2008-2010) Sergey Aleynikov, former Goldman Sachs computer programmer/prop trader indicted and prosecuted on charges of HFT algorithm theft. UBS filed a lawsuit against three former quants alleging to have stolen proprietary algorithmic trading software with the intent of using it at their new employer. Ukrainian hacker Oleksandr Dorozhko charged for insider trading by SEC. Mr Dorozhko traded option contracts on information gained by accessing earnings data from a staging server prior to their release date. 5

6. Even More Recently … (Dec 2010 - Jan 2011) Romanian Registry (Carbon Trading Platform) 1.6 million CO2 certificated from Holcim Cement account were stolen. Credits were transferred to hacker controlled accounts in EU states. Czech / Austrian Registry (Carbon Trading Platform) Two million credits worth 2.8 million were stolen and transferred to other registries and / or sold to other market participants. 6

7. Even More Recently … (Dec 2010 - Jan 2011) NASDAQ Director’s Desk Application Currently being investigated for a potential breach, the Directors Desk application is an EMS application that allows executives to share sensitive documents including earnings data, board minutes etc. 7

8. Common Theme / Trends Attackers are still leveraging the low hanging fruit in terms of security issues used to compromise these systems. As of 2011, the threats are increasing both in scale and sophistication. Outsider threat is increasing 8

9. Application Security 9

10. Case Studies Trade Optimized Strategy Engine Issues OTC Trading Platforms Issues Thick Client Trading Platforms Issues Reconciliation Platform Issues Indices Application Insecurities Computational Grid Attacks 10

11. Trade Optimized Strategy Engine WHAT Class of applications used for submission and analysis of investment/trading strategies. WHO Used mainly by Funds/Banks/Investment Management firms employing Global Macro/Event driven trading strategies HOW Third party Brokers, Analysts, Economists access the application to upload trading strategies/ideas. The application uses both statistical and/or proprietary algorithms to index/rate submitted strategies Traders trade the most optimum strategy 11

12. Case Study - Trade Optimized Strategy Engine Issues (Weak Input Validation) 12

13. Problems Infrastructure Issues Application Issues Governance 13

14. OTC Trading Platforms WHAT Predominantly dealer applications for trading over-the-counter derivatives. WHO Used by almost all banks dealing in credit derivatives markets - CDO, CDS, IRS etc Mainly used for structuring instruments, based on client requirements which are then traded directly or through a dealer. Mainly used by front office quants/traders HOW Trades are executed using commercial and/or bespoke platforms etc Post Trade processing can be carried in-house or outsourced. 14

15. Case Study – Bank OTC Trading Platform Issues (Trade Data / Client Discovery Attack) 15

16. Problems Application Issues Governance 16

17. Thick Client Trading Platforms WHAT Any front, middle or back office trading application. Often developed for business/analyst staff and/or used to extend trading services to third-party clients. 17

18. Case Study - Thick Client Trading Platform Issues (Forex Broker-Dealer Application) 18

19. Problems Application Issues 19

20. Case Study - Reconciliation Platform Issues

21. Indices Applications Definition Index - A basket/collection/group of securities to track the performance of a market/sector/asset. Can be traded as Futures/Options contracts or used as the underlying for other products. WHO Mostly developed and managed by Exchanges, Rating agencies and Banks. HOW A committee or bespoke methods / benchmarks are used to rebalance indices. 21

22. Case Study - Index Rebalancing/Turnover Attacks 22

23. Computational Grids WHAT High performance computing grids used for running solvers, simulations and analysis of financial time series data. (Monitcarlo, Volatility, OP etc) WHO Mostly institutions and departments involved with financial modeling. Users tend to be quants, traders and analysts. HOW Models are submitted to the grid environment using Web services, custom APIs and/or remote access. 23

24. Case Study - Computational Grid Attacks

25. Problems Infrastructure Issues Application Issues . Governance 25

26. FIX Protocol Weaknesses 26

27. What is FIX Protocol ? The Financial Information eXchange (FIX) protocol is an electronic communications protocol initiated in 1992 for international real-time exchange of information related to the securities transactions and markets – Wikipeda In other words, the protocol facilitates the buying and selling of securities electronically. 27

28. Who Uses FIX FIX is widely used by both the buy side (institutions) as well as the sell side (brokers/dealers) in the financial markets. Amongst its users are hedge funds, mutual funds, investment banks, brokers and stock exchanges Transaction types supported: Pretty much all asset classes i.e Equities, Bond, Derivatives and Forex. 28

29. Who Uses FIX 29

30. Why Investigate FIX ? FIX security is often overlooked in favor of Operating System and Host Security To demonstrate that FIX based front running is possible and not difficult to exploit To identify mitigating factors and strategies for some of the existing issues within FIX protocol 30

31. Algorithmic Trading Architecture 31

32. High Frequency Trading Architecture 32

33. Order Front Running (Demo) Demo Environment: Algorithmic Trading Environment – A simulated algorithmic/high frequency trading environment Brokerage Account – Hacker Controlled brokerage account to reply orders. Order Sniffer - Note The following examples used during this demonstration are not intended to suggest any insecurities or weaknesses in the third party applications and are only to be seen as a case study to demonstrate FIX protocol insecurities. 33

34. Algorithmic Trading Environment 34

35. Brokerage Account 35

36. Order Front Running 1 2 3 36

37. LibPcap FIX Sniffing (Slow) symbol = re.compile('55=[A-Z]*') # Symbol (APPL, GOOG .. ) buy = re.compile('54=1') # BUY Order sell = re.compile('54=2') # SELL Order order_qty = re.compile('38=[0-9]*') # Order quantity price = re.compile('44=[0-9]*') # Equity Price 37

38. Fix Virus 38

39. Cont 39

40. Binary Tree _ 40

41. Fast FIX walker (C++) 41

42. Order Builder 42

43. Hedgefund Example - Weak Wifi + FIX sniffer 43

44. IbPy Server Side Code - Contract Builder def build_stock_contract(symbol, quantity, oid): stock.m_symbol = symbol stock.m_secType = 'STK' stock.m_exchange = 'SMART' stock.m_currency = 'USD' Order.m_orderId = oid Order.m_clientId = 0 Order.m_permid = 0 Order.m_action = 'BUY' Order.m_lmtPrice = 0 Order.m_auxPrice = 0 Order.m_tif = 'DAY' Order.m_transmit = False Order.m_orderType = 'MKT' Order.m_totalQuantity = quantit 44

45. Order Sniffer (Excel plugin) – order encoding 45