Like, it can’t be a real person, right? Has anyone tried following the links? I’m curious how they’re scamming people. It just seems like anyone getting the same message 5 times won’t fall for being catfished, so I don’t understand what their strategy is.

    • cynar@lemmy.world
      link
      fedilink
      English
      arrow-up
      2
      ·
      8 hours ago

      No evidence that we have. The spammers obviously think it’s worth doing however, and they are the ones that would have the statistics.

      • null_dot@lemmy.dbzer0.com
        link
        fedilink
        English
        arrow-up
        2
        arrow-down
        1
        ·
        8 hours ago

        All the evidence we do have demonstrates that the typos evade Bayesian filters and improve deliverability. This is demonstrably true.

        When you hear hoof beats think horses not zebras.

        • cynar@lemmy.world
          link
          fedilink
          English
          arrow-up
          1
          ·
          8 hours ago

          Does it however? I’m not up to speed on modern anti spam, but a huge number of spelling mistakes screams spam to me. I would be extremely surprised if it wasn’t the case. The best way to deliver spam is to make it indistinguishable from legit messages.

          Also, the existence of spear fishing implies it’s a choice.

          • null_dot@lemmy.dbzer0.com
            link
            fedilink
            English
            arrow-up
            1
            arrow-down
            1
            ·
            6 hours ago

            a huge number of spelling mistakes screams spam to me

            Do you mean to say, you’ve learned to associate spelling errors with spam because most of the spam you see… the spam that gets past your spam filters… has a lot of spelling errors?

            The best way to deliver spam is to make it indistinguishable from legit messages.

            That’s just not true. The best way to deliver spam is to send it from a reputable address, and to avoid looking like spam.

            Bayesian filters need to be trained by a user identifying email as spam. From those emails it learns which words frequently appear in spam emails. Including spelling errors means more unique words rather than words that look like spam.

            • cynar@lemmy.world
              link
              fedilink
              English
              arrow-up
              1
              ·
              6 hours ago

              More than I see very few of them anymore. I see more of them when I look in the junk mail, but even hotmail has gotten good a filtering out all the crap.