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AFAIK Wifi Direct has quite wide hardware support -- https://en.wikipedia.org/wiki/Wi-Fi_Direct. But few people know about it?

Might not be how it appears. The CVE number can be reserved by the org and then "published" with only minimal info, then later update with full details. Looking at the meta data that's probably what happened here (not entirely sure what the update was though):

    {
    "cveId": "CVE-2025-14847",
    "assignerOrgId": "a39b4221-9bd0-4244-95fc-f3e2e07f1deb",
    "state": "PUBLISHED",
    "assignerShortName": "mongodb",
    "dateReserved": "2025-12-17T18:56:21.301Z",
    "datePublished": "2025-12-19T11:00:22.465Z",
    "dateUpdated": "2025-12-29T23:20:23.813Z"
    }

Cool, I get to call my Youtube, TikTok addiction my "intellectual crack" now. Only fair.

If you're using your YouTube and TikTok addictions to build things that other people can use, go nuts

Actually I think that's roughly how threat analysis works though.


For threat analysis, you need to know how hard you are to break in, what the incentives are, and who your potential adversaries are.

For each potential adversary, you list the risk strategy; that's threat analysis 101.

E.g. you have a locked door, some valuables, and your opponent is the state-level. Risk strategy: ignore, no door you can afford will be able to stop a state-level actor.


I concur the question, "Who would have an incentive to spend resources on DDoS'ing Codeberg?" is a bit convoluted in mixing incentive and resources. But it's still, exactly, threat analysis, just not very useful threat analysis.


Wouldn't an AI scraper working for a huge firm have more incentive to scrape your code, than a competitor?


> It would be cool to have something like this ..

Aren't LLMs something like this?


An LLM probabilistically produces tokens over its model which is why it can hallucinate whilst an actual graph model would not have that issue


https://github.com/opensearch-project/OpenSearch-Dashboards (Kibana fork) is one. But Grafana is still way better if you just stay away from anything that isn't the core product: data visualization and exploration (explorer and traces).


Talk about a coup against reality. Pay the man his due. Tesla produce very competitive EVs. He has been instrumental in the success of SpaceX and Tesla.


Tasmania doesn't do much sheep farming. They are more into salmon. Maybe you were making a derogatory reference to the local human population? Fair enough.


Tasmania has 38 sheep per square kilometer and is only surpassed by Victoria with 60 sheep km2. WA has 4 sheep per km2, QLD 1.44, SA 10, NSW 3.

In population terms, Tasmania has 4.5 sheep per person, whereas Victoria has 1.9 sheep per person. NSW 0.28, SA 5.2, WA 3.3, QLD 0.4

[1] https://www.ga.gov.au/scientific-topics/national-location-in... [2] https://www.abs.gov.au/statistics/people/population/national... [3] https://www.wool.com/market-intelligence/sheep-numbers-by-st...

* Population numbers are one head per person, so actual numbers may vary for Tasmania ;-)


Please keep arguing about this, it is relieving a lot of stress to watch this. There have to be more facts than just that. I'm serious. This helps me take focus off the rest of the world burning. I'm serious.


Understandable, it's counting sheep after all.


What are the salmon numbers?


They rise and fall as the orange bellied parrots fly over, salmon leaping to catch the parrots is a sight to behold.

I better get my maugean skates on...


NSW ~ 30.2 sheep / sq km.


Owning and renting a vacation accommodation is gig economy? Those poor renting seeking plebs.


Ever heard of airbnb?

I think mainly it helps property owners skirt the whole “I’m a landlord” thing and all the legal obligations it entails.


Yeah, I just don't really consider sitting on you fat butt and collecting rent a "gig". That's called rent seeking, or a scam.


Crude starting point from ChatGPT:

  U.S. Corporate Tax Revenue as a Percentage of GDP (1900–2020s)
  Decade Corporate Tax Revenue as % of GDP
  1900s ~0.1%
  1910s ~0.5%
  1920s ~0.8%
  1930s ~1.0%
  1940s ~4.0%
  1950s ~4.3%
  1960s ~3.5%
  1970s ~3.0%
  1980s ~2.5%
  1990s ~2.5%
  2000s ~1.3%
  2010s ~1.0%
  2020s (est.) ~1.0% (varies slightly)

  U.S. Individual Income Tax Revenue as a Percentage of GDP (1900-2020s)
  Decade Income Tax Revenue as % of GDP
  1900s ~0.0%
  1910s ~0.5%
  1920s ~1.5%
  1930s ~3.5%
  1940s ~7.5%
  1950s ~8.0%
  1960s ~8.0%
  1970s ~8.5%
  1980s ~8.0%
  1990s ~8.0%
  2000s ~8.5%
  2010s ~8.0%
  2020s (est.) ~8.0% (varies slightly)


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