ABasilPlant

I need a recognisable domain name website that google or duckduckgo has picked as the product.

This doesn't always work. For example, I used to (and still do) see a lot of fake websites when I l type revanced (https://revanced.app/) on duckduckgo, and I've nearly fallen for two of the fake ones before (I think two of .com / .org / .to...?)

Thankfully ublock origin warns users of this:

Otherwise, I'd have 100% downloaded some malware-loaded crap.

Not exactly what you asked, but do you know about ufw-blocklist?

I've been using this on my multiple VPSes for some time now and the number of fail2ban failed/banned has gone down like crazy. Previously, I had 20k failed attempts after a few months and 30-50 currently-banned IPs at all times; now it's less than 1k failed after a year and maybe 3-ish banned at any time.

There was also that paid service where users share their spammy IP address attempts with a centralized network, which does some dynamic intelligence monitoring. I forgot the name and search these days isn't great. Something to do with "Sense"? It was paid, but well recommended as far as I remember.

Edit: seems like the keyword is " threat intelligence platform"

PR Videos to save you a click:

https://www.youtube.com/watch?v=mWKhSrsj3V0

https://www.youtube.com/watch?v=-v283Og5DLw

Can single-branch handle cloning from a particular commit? I know that it's possible to clone particular branches and particular tags with depth=1, but OP states cloning at a particular commit, not HEAD.

~~--depth=1? I use this all the time when I clone the kernel.~~

Edit: reread that you wanted to download code at a particular commit.

https://wikipedia.org/wiki/Mate_choice_copying

Yep, a few forks were identified within a few hours. I think the maintainers had forks too.

Yes, this would essentially be a detecting mechanism for local instances. However, a network trained on all available federated data could still yield favorable results. You may just end up not needing IP Addresses and emails. Just upvotes / downvotes across a set of existing comments would even help.

The important point is figuring out all possible data you can extract and feed it to a "ML" black box. The black box can deal with things by itself.

My bachelor's thesis was about comment amplifying/deamplifying on reddit using Graph Neural Networks (PyTorch-Geometric).

Essentially: there used to be commenters who would constantly agree / disagree with a particular sentiment, and these would be used to amplify / deamplify opinions, respectively. Using a set of metrics [1], I fed it into a Graph Neural Network (GNN) and it produced reasonably well results back in the day. Since Pytorch-Geomteric has been out, there's been numerous advancements to GNN research as a whole, and I suspect it would be significantly more developed now.

Since upvotes are known to the instance administrator (for brevity, not getting into the fediverse aspect of this), and since their email addresses are known too, I believe that these two pieces of information can be accounted for in order to detect patterns. This would lead to much better results.

In the beginning, such a solution needs to look for patterns first and these patterns need to be flagged as true (bots) or false (users) by the instance administrator - maybe 200 manual flaggings. Afterwards, the GNN could possibly decide to act based on confidence of previous pattern matching.

This may be an interesting bachelor's / master's thesis (or a side project in general) for anyone looking for one. Of course, there's a lot of nuances I've missed. Plus, I haven't kept up with GNNs in a very long time, so that should be accounted for too.

Edit: perhaps IP addresses could be used too? That's one way reddit would detect vote manipulation.

[1] account age, comment time, comment time difference with parent comment, sentiment agreement/disgareement with parent commenters, number of child comments after an hour, post karma, comment karma, number of comments, number of subreddits participated in, number of posts, and more I can't remember.

Ah if you messed it up, you can press "e" on the grub entry and edit the command line parameters to remove the thing that messes it up. Good luck with your fresh install [and use Debian this time... jk :)]

Make sure to update your grub after you do. I've messed that one up before lol 😅

Do you not need the nvidia-drm.modeset=1 in GRUB_CMDLINE_LINUX?

https://www.if-not-true-then-false.com/2015/fedora-nvidia-guide/#262-edit-etcdefaultgrub