"Nepenthes generates random links that always point back to itself - the crawler downloads those new links. Nepenthes happily just returns more and more lists of links pointing back to itself."

A pseudonymous coder has created and released an open source “tar pit” to indefinitely trap AI training web crawlers in an infinitely, randomly-generating series of pages to waste their time and computing power. The program, called Nepenthes after the genus of carnivorous pitcher plants which trap and consume their prey, can be deployed by webpage owners to protect their own content from being scraped or can be deployed “offensively” as a honeypot trap to waste AI companies’ resources.

“It’s less like flypaper and more an infinite maze holding a minotaur, except the crawler is the minotaur that cannot get out. The typical web crawler doesn’t appear to have a lot of logic. It downloads a URL, and if it sees links to other URLs, it downloads those too. Nepenthes generates random links that always point back to itself - the crawler downloads those new links. Nepenthes happily just returns more and more lists of links pointing back to itself,” Aaron B, the creator of Nepenthes, told 404 Media.

  • count_dongulus@lemmy.worldEnglish
    402·
    16 hours ago

    This won’t work against commercial crawlers. They check page contents with something similar to a simhash and don’t recrawl these pages. They also have limiters like for depth to avoid getting stuck in circular links.

    You could generate random content for each new page, but you’ll still eventually hit the depth limit. There are probably other rules related to content quality to limit crawling too.

    • meyotch@slrpnk.netEnglish
      361·
      16 hours ago

      True, this is an arms race situation after all. The real benefit of this is creating garbage training data that makes garbage models. So it’s not just increasing the cost of crawling, it increases the cost of stealing everybody’s shit because you need extra data quality checks. Poisoning the well.

        • Thrashy@lemmy.worldEnglish
          10·
          15 hours ago

          Say it with me now: model collapse! I think this approach is especially insidious in that rather than dumping obvious nonsense into the training corpus that can then be scrubbed, it pushes the downstream LLM invisibly towards spontaneously imploding.

        • meyotch@slrpnk.netEnglish
          2·
          14 hours ago

          Exactly! That’s ideal because LLM or simple pattern matching can’t be used to easily winnow out random strings. If it’s sensible language but the usual LLM hallucinations, then you need humans to curate your data. Fuck you, Sam Altman.