Part 15 of “The Restricting Covenant” Series: Non-Competes, Trade Secrets and Corporate Espionage
Monday, July 2, 2018

Highly valuable trade secrets, corporate espionage, elaborate schemes to evade detection, and national defense implications.  Have I piqued your curiosity?  I hope so.  In this fifteenth article of The Restricting Covenant series, I discuss two cases that involve individuals and business enterprises charged by the federal government with stealing valuable trade secrets from U.S.-based companies.  The stakes are extremely high on all sides.

USA v. Shan Shi, et al.

Two words:  Syntactic foam.  While I had not heard about this foam before writing this article, it’s obviously very difficult to manufacture and extremely valuable stuff.

According to a federal indictment released by the Department of Justice in April 2018, two businessmen, along with their U.S. and China-based business enterprises, conspired to steal highly valuable and well-guarded trade secrets from a Swedish engineering company based in Houston, Texas (“Company A”), that manufactures and sells syntactic foam – a strong, lightweight buoyant material with commercial (e.g., offshore oil rigging) and military (e.g., underwater vehicles) uses.

Through its technical expertise and more than five decades of continued research and development, Company A developed a manufacturing process that gave it a competitive advantage in the marketplace for at least seven trade secrets related to syntactic foam.  To protect these confidential and proprietary trade secrets, Company A limited visitor access to its facilities and required them to sign a confidentiality agreement, limited its computer network to designated employees, password protected its computer files, and required all new hires and terminated employees to sign non-competition agreements that included language not to divulge protected information.  In other words, Company A took reasonable precautions to keep its syntactic foam formula from falling into the wrong hands.

The government alleges that over a five-year period, the defendants, most of whom were former employees of Company A, engaged in a scheme to help a Chinese company manufacture the syntactic foam in furtherance of the China government’s goal of becoming a worldwide marine power.  Many of the trade secrets were stolen electronically and secretly transferred via Company A’s email accounts to the defendants’ personal email accounts.  One email, for example, between the defendants stated, “I need information regarding formula, preparation process and performance of syntactic materials.”  The indictment references other emails with attachments containing Company A’s foam resin models, ingredient lists, and formulas.  By 2016, the Chinese manufacturing company that was affiliated with the defendants had a syntactic foam factory in China and was bidding for significant contracts in competition with Company A.

At least one person pleaded guilty to conspiring to steal Company A’s trade secrets before the indictment was unsealed.  The defendants are charged with economic espionage, theft of trade secrets, and money laundering, and if convicted could face 10 to 20 years in prison.  The case is being prosecuted by the U.S. Attorney’s Office for the District of Columbia and the National Security Division’s Counterintelligence and Export Control Section.

USA v. Zheng Quan Zhang

One word:  Algorithms.  A great algorithm can be worth millions of dollars to a financial securities firm.  Companies carefully guard these computer codes from disclosure to the public and ask their employees to do the same through confidentiality and non-competition agreements.

In April 2017, the government arrested Zheng Quan Zhang a/k/a Jim Z. Zhang in California and charged him with stealing confidential computer codes relating to algorithmic trading models and trading platforms from his former employer, an unidentified global financial services firm headquartered in New York City (“Firm-1”).

Like many financial services firms, Firm-1 uses proprietary algorithmic trading models to help it predict market movements and make trading decisions.  Most of the trading was conducted using Firm-1’s proprietary trading platforms, which create and execute orders and automatically submit them to an exchange.  Firm-1 tried to protect this electronic source code through a variety of security measures, including unique computer login identifiers, encryption keys, and restrictions on its employees’ use of external email and file-sharing websites.  Firm-1’s employees signed agreements that explained, among other things, the confidential nature of Firm-1’s codes and platforms.

According to the Complaint filed by the U.S. Attorney’s Office for the Southern District of New York, Complex Frauds and Cybercrime Unit, and sworn by an FBI Special Agent, for at least six months, Zhang, an employee in the technical operations and development and network troubleshooting groups, went to great lengths to steal computer code surreptitiously from his employer.  He installed on Firm-1’s system a computer code designed to look for encryption keys to gain access to portions of Firm-1’s algorithms.  He also installed software that captured analysts’ passwords and login information.  He installed a separate code designed to send data from Firm-1’s system to an external third-party software development site, which Zhang accessed thousands of times from Firm-1’s system.  Zhang siphoned over 3 million files, including unencrypted portions of Firm-1’s trading source codes.

Zhang’s activities were discovered when one of Firm-1’s quantitative analysts reported to Firm-1’s network security group some unusual activity with his remote desktop access.  That group determined that Zhang had accessed the analyst’s remote desktop without authorization.  The Complaint alleges that Zhang admitted in an email to a co-worker that he had “remotely logged in a few desktops randomly without authorization,” but explained to his co-worker that he had accessed these accounts because he was concerned about the status of his job in light of rumors of a potential acquisition of Firm-1 and wanted to understand the status of the company.

Additional Summer Reading about Alleged Theft of Trade Secrets     

In addition to the Shi and Zhang cases discussed above, if you are interested in cybercrime, trade secrets, and the potential consequences for stealing trade secrets and intellectual property, then you’ll want to review the cases of United States v. Sergey Aleynikov and Aleynikov v. Goldman Sachs Group, Inc. (involving alleged theft of source code related to Goldman Sachs’ proprietary high-frequency trading system).  These disputes have been ongoing for more than a decade.  The twists and turns of the Aleynikov/Goldman Sachs cases in state and federal courts in Delaware, New Jersey and New York, are fascinating and must reads.

Also worth a read is the complaint filed by the electric vehicle company, Tesla, Inc., on June 20, 2018 in Nevada federal court against a former technician, alleging that he had hacked into Tesla’s manufacturing operating system and transferred several gigabytes of Tesla trade secret data to outside entities.  This is not the first time that Tesla has pursued legal relief against its former employees on trade secret issues.  In June 2017, a judge in California sentenced a former Tesla engineer who plead guilty to computer intrusion to five years’ probation and ordered him to pay Tesla restitution for illegally accessing a former manager’s email and downloading confidential information he later posted online.

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The goal of this Series is to provide a brief overview and some interesting insights and practical pointers when dealing with unique issues that might arise in the context of restrictive covenants.  It is not intended to provide and should not be construed as providing legal advice. Stay tuned for future articles in this Series, which will discuss the restrictive covenant landscape for many other occupations and industries, including veterinarians, web designers, high-frequency traders and brokers, and more.

 

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