According to the March 24 document submitted to the U.S. District Court of the Northern District of California, "different snippets" of the source code used to power Twitter's online operations were published on Github by a user going by the moniker "FreeSpeechEnthusiast."
The "proprietary source code for Twitter's platform and internal tools," according to Twitter, was part of the breach.
Microsoft-owned portal for sharing software development code, Github, claimed to have removed the code at Twitter's request.
In order to compel Github to reveal who was responsible for the leak, Twitter has requested a subpoena. A Github representative informed the BBC that the company "usually does not comment on decisions to remove content." Yet, "we post every DMCA [Digital Millenium Copyright Act] takedown request publicly in the interest of transparency."
The DMCA is a statute that was passed in 1998 with the intention of defending copyrighted content online.
The information was leaked following Elon Musk's announcement that Twitter would reveal its content recommendation algorithms.
On March 31, Twitter will open source all of the code that is used to suggest tweets, according to a post by Musk on March 17.
As algorithms are typically kept as closely-guarded trade secrets, the decision to disclose them is exceptional.
Users can connect with various persons, posts, or other related content using social media algorithms.
Opponents have expressed concern that these algorithms might be employed to favor some ideologies or points of view over others.
Following an investigation into the matter by the Senate Commerce, Science, and Transportation Committee headed by Sen. Ted Cruz, Musk decided to make Twitter's recommendation algorithm public (R-Texas).
Cruz has issued a warning about the potential impact of recommendation algorithms on political results.
In a recent letter to tech executives, Cruz stated that "in a world where seven out of ten Americans get their political news from social media, the method in which content is filtered through recommendation systems has an indisputable effect on what Individuals see, think, and ultimately believe."
Such algorithms, according to the Republican senator, might encourage social media addiction and increase exposure to hazardous content, or they can be used for partisan purposes.
Social media can lead users and young children to potentially harmful or biased content, according to whistleblower testimony presented to the Senate during the previous Congress by a former Meta employee.
Musk did not specify in his announcement whether the action was in response to Cruz's inquiry.
