Suno hack exposes training data scraping from YouTube Music, Deezer and Genius

The same old tune.

Suno has previously faced criticism for building an AI song creator on copyrighted works, and here's more evidence.

For years, musicians have said AI song generators fed on their work without asking. A hacker just opened the black box and showed them exactly how. Leaked source code from Suno, one of the biggest AI music tools, tells the story. It trained its model by scraping millions of songs and lyrics from across the […] This story continues at The Next Web

A hacker who breached Suno reportedly revealed source code and training-library details showing the AI music generator scraped millions of songs and lyrics from sources including YouTube Music, Deezer, Genius, Pond5, Jamendo, Freesound, and podcast RSS feeds. "The hacked data is a rare look at exactly how AI models and tools are built," reports 404 Media. "Suno is one of the largest AI music generation tools on the internet, and has been the subject of several major lawsuits from the record industry, which accused the company of training on millions of copyrighted songs." Suno maintains that its models were trained on publicly available music files and metadata as fair use. 404 Media reports: The Recording Industry Association of America accused Suno of ripping songs directly from YouTube; the hacked data seen by 404 Media confirms this. The hacked material includes source code that appears to be from 2023 and 2024 that includes scraping instructions and details about the scope of at least some of the scraping. For example, the comments in one file note that they will pull from "genius_hq, youtube_music, freesound, jamendo, imp, deezer, ytm_tagged," and that "non-music will be filtered out." A file called "youtube_music" notes that at the time the file was last updated, it had ingested "2,013,545 music clips." Another file contains comments about different datasets Suno had created, which included "113,879 hours of youtube_music," "17,615 hours of genius_hq," "410 hours of free sound," "19,514 hours of imslp," "3,726 hours of jamendo," "62,117 hours of pond5_music," "12,287 hours of deezer," "152,162 hours of ytm_tagged," and "103 hours of musescore_lyrics." In total, this is at least decades worth of music. Other code the hacker shared with 404 Media appeared to look specifically for vocals by searching specifically for acapella versions of songs on YouTube. The code also suggested that Suno was using proxies to scrape songs from YouTube through a company called Bright Data, which sells scraping tools, infrastructure, and data services. Additional code shows that with the help of an online tool called PodcastIndex, Suno identified 420,000 different podcasts that had at least five, 30-minute episodes and sought to download roughly 1 million hours of podcasts. [...] The hacker, ellie.191, told 404 Media they breached the company by hacking an individual employee using the Shai-Hulud worm, a supply chain attack that allowed hackers to harvest GitHub and cloud service credentials. They said they also accessed Suno's customer list, which included customers' emails and/or phone numbers and Stripe payment details, depending on what they used to login. The hacker provided a sample of some of the customers, some of whom confirmed to 404 Media they had used their phone number to sign up for Suno and said they were never notified of a breach. The hacker told 404 Media they had no specific motivation for hacking Suno and said "I like to hack anything and everything." Read more of this story at Slashdot.

The AI music generator reportedly scraped millions of songs and lyrics from YouTube, Deezer, and Genius

Suno has long acknowledged that its AI music generator relied on the scraping of millions of songs available across the internet, but a new hack reveals just how the company pulled from streaming services and websites such as YouTube Music, Deezer and Genius to power its product — all while user information remained vulnerable. A report […]