Theft Of Proprietary Algorithms Prosecutions

30 Sep 2025 --
0 Comments

1. United States v. Sergey Aleynikov (Goldman Sachs Case, 2010 & 2012)

Court: U.S. District Court, Southern District of New York; later Second Circuit Court of Appeals
Facts:
Sergey Aleynikov, a former computer programmer at Goldman Sachs, downloaded portions of the firm’s proprietary high-frequency trading (HFT) source code to his personal server before leaving to join a startup. The code was highly confidential and worth millions, forming the backbone of Goldman’s trading operations.

Prosecution:
He was initially charged under the Economic Espionage Act (EEA) and the National Stolen Property Act (NSPA). The government argued that Aleynikov’s act endangered Goldman’s competitive position.

Outcome:
Aleynikov was convicted at first but acquitted on appeal because the EEA, at that time, only covered products “produced for or placed in interstate commerce.” Since Goldman’s algorithm wasn’t sold or distributed commercially, the court overturned the conviction.

Impact:
This case prompted Congress to amend the EEA in 2012 through the Theft of Trade Secrets Clarification Act, closing the loophole and extending coverage to internal trade secrets like proprietary algorithms.

2. United States v. Anthony Levandowski (Google v. Uber, 2017–2020)

Court: U.S. District Court, Northern District of California
Facts:
Anthony Levandowski, a lead engineer at Google’s Waymo (self-driving car division), downloaded thousands of confidential files, including design schematics and algorithms related to LiDAR technology, before founding his own startup, which was later acquired by Uber.

Prosecution:
The U.S. Department of Justice charged Levandowski under 18 U.S.C. §1832 (Theft of Trade Secrets). The government claimed that the files contained proprietary algorithms for self-driving systems.

Outcome:
Levandowski pleaded guilty to one count in 2020. He was sentenced to 18 months in prison (later pardoned by President Donald Trump in 2021) and ordered to pay $756,000 in restitution to Google.

Impact:
This case became a landmark example of trade secret enforcement in the tech industry, highlighting how algorithmic theft between corporate competitors can lead to both criminal and civil consequences.

3. United States v. Xu Jiaqiang (IBM Source Code Theft, 2017)

Court: U.S. District Court, Southern District of New York
Facts:
Xu Jiaqiang, a former software developer at IBM, stole portions of IBM’s proprietary source code for its distributed file system — a core algorithm for handling massive data workloads. Xu intended to sell or share the code with Chinese entities.

Prosecution:
He was charged under the Economic Espionage Act (18 U.S.C. §§1831–1839) for stealing trade secrets related to technology used by IBM for high-speed computing.

Outcome:
Xu pleaded guilty and was sentenced to five years in federal prison in 2017.

Impact:
The case demonstrated the U.S. government’s increasing concern about international trade secret theft involving proprietary algorithms and the use of the EEA to counter such espionage.

4. United States v. Biswamohan Pani (Intel v. AMD, 2012)

Court: U.S. District Court, District of Massachusetts
Facts:
Pani, a former Intel engineer, copied confidential documents related to Intel’s microprocessor design algorithms while still employed by Intel but after accepting a job at competitor AMD. The files contained proprietary chip design methodologies.

Prosecution:
He was charged under 18 U.S.C. §1832 for theft of trade secrets and wire fraud.

Outcome:
Pani pleaded guilty and was sentenced to three years in prison and ordered to pay $17,500 in fines.

Impact:
The case reinforced that even if the stolen data isn’t directly used or sold, mere possession or intent to use proprietary algorithms can constitute a criminal offense under trade secret laws.

5. Waymo LLC v. Uber Technologies Inc. (Civil + Criminal Dimensions, 2018)

Court: U.S. District Court, Northern District of California
Facts:
This case followed from Levandowski’s criminal charges but focused on the civil side. Waymo alleged that Uber misappropriated self-driving car algorithms and LiDAR blueprints originally developed by Google.

Prosecution/Civil Action:
Waymo accused Uber of benefiting from stolen algorithms that were integral to autonomous navigation systems.

Outcome:
Uber and Waymo settled in 2018, with Uber agreeing to pay $245 million in equity to Waymo and pledging not to use the stolen technology.

Impact:
The case showed how criminal algorithm theft often runs parallel to major intellectual property lawsuits, setting industry norms for protecting proprietary code and models.

6. United States v. Turab Lookman (Los Alamos National Laboratory Case, 2019)

Court: U.S. District Court, District of New Mexico
Facts:
Dr. Turab Lookman, a physicist at Los Alamos National Laboratory, attempted to transfer U.S. government-funded machine learning algorithms to foreign collaborators without authorization. The algorithms were part of sensitive defense-related research.

Prosecution:
He was charged under false statement and trade secret protection statutes, since the algorithms were classified as confidential intellectual property under U.S. national interest.

Outcome:
Lookman pleaded guilty and received probation and a fine, as the government considered the act a breach of trust rather than pure espionage.

Impact:
This case emphasized how even government-funded proprietary algorithms fall under trade secret and export control laws.

Legal Principles Highlighted

Economic Espionage Act (18 U.S.C. §1831–1839):
Protects trade secrets, including proprietary algorithms, against both domestic theft and foreign espionage.

National Stolen Property Act (18 U.S.C. §2314):
Applies when digital property or source code is transported or transferred unlawfully across state lines.

Amendment via Theft of Trade Secrets Clarification Act (2012):
Extended protection to internally used trade secrets (like algorithms not sold in commerce).

Civil Remedies under the Defend Trade Secrets Act (DTSA) 2016:
Allows companies to sue for damages and injunctions in federal court for algorithm theft.

Summary

Case	Defendant	Company Affected	Type of Algorithm	Outcome
Aleynikov (2010)	Sergey Aleynikov	Goldman Sachs	Trading Algorithm	Conviction overturned (law amended)
Levandowski (2017)	Anthony Levandowski	Google/Waymo	Self-driving algorithm	Pleaded guilty, sentenced
Xu Jiaqiang (2017)	Xu Jiaqiang	IBM	Data processing algorithm	Pleaded guilty, 5 years
Pani (2012)	Biswamohan Pani	Intel	Microprocessor algorithm	3 years prison
Waymo v. Uber (2018)	Uber (Civil)	Google/Waymo	LiDAR & navigation algorithms	$245M settlement
Lookman (2019)	Turab Lookman	Los Alamos Lab	Machine learning algorithm	Probation and fine