I agree with the need, but not your rationale, I’m in the “always curly braces” camp for two reasons:
Your question, as best as I could tell, is that you want DNS traffic to exit through your VPS node, rather than your client machine.
I posited one reason this could be happening, and additionally, a similar setup that provably routes traffic through the VPN based on the method I described.
Nobody in here is obligated to help you, I gave you a couple threads to pull on to resolve your question, so maybe consider accepting it graciously, rather than being obstinate.
Of course, you have to trust that third party, which may/may not be prudent.
It’s not completely clear what you mean, but I’m guessing you’re only routing a subset of your traffic through wireguard, probably only IPv4, and there may be some IPv6 traffic that is not being routed over your wireguard connection.
You can specify any IPs you want for DNS with wireguard, and if your allowed IPs include those addresses, then it should flow over your VPN.
I do this with Pihole at home, and it blocks ads while I’m away.
With whatever test you’re running that says stuff is “leaking,” keep in mind that the website is going to report any traffic that originates from your VPS as “unprotected” because it’s not their system, and even if you run your own DNS server, it’s still got to query upstream to a public DNS. All they’re really doing is demonstrating which upstream DNS server you have configured, and it’s up to you if you want your VPS’s IP to be connected to the query history of that upstream DNS provider.
You will usually need a hostname in DNS for your VPN server to make it easy to find/connect, which will use your normal DNS resolution. Once connected, if you have it set up correctly, new dns queries should route through your VPN connection. Just keep in mind that various results can be cached on your system and in web browsers, so you should quit and reopen your browser after you connect to the VPN before you run your “leak” test.
LLMs aren’t going to give you a roadmap or prioritize concepts. They also frequently produce contradictory information.
They’re good tools if you already have some experience and vocabulary in the field, but a more structured approach to building some projects and acquiring skills is better.
In my 20 year career, I’ve never had a single position where I could ssh into my work machine from a remote location.
I would say that if you have been able to do that, it’s exceptionally rare, and there are a number of security red flags of your organization is allowing that.
And you can do the previous years of the coding challenge at any time.
I took some time off, and this was a good source of solving “real” problems, rather than trying to write something to optimize for l33tcode (which, is fine… just not a good measure for typical software engineering responsibilities, IMO).
It’s necessarily complexity that is easily encapsulated in methods.
If those methods are under test to verify their behavior, trivial typos can be detected instantly, without adding another dialect and more conceptual overhead to a project.
If those methods are not under test, then there’s a tiny bit of help by using a DSL if it can be compile-time checked.
I used to be full on the ORM train. Now I’m a little less enthusiastic. What I actually think people need most of the time is something closer to ActiveRecord. Something that can easily map a result set into a collection of typed objects. You still generally write parameterized SQL, but the work of translating a db decimal into the correct target type on a record object in your language is handled for you (for example). In .net, Dapper is a good example.
I also think most people overemphasize or talk about how other programmers “suck at SQL” waaayy too much.
IMO, for most situations, these are the few high-level things that devs should be vigilant about:
On most of those points, if you don’t have aggregate query counts/metrics on query performance on your clusters, starting to get cute with complex queries is flying blind, and there’s no way to prioritize what to optimize.
For the vast majority of cases, simple, obvious selects that don’t involve special db features are going to do the job for most applications. When the database becomes a bottleneck, there are usually much more effective ways to handle them than to try to hand optimize all the queries.
Lastly, I have a little bit of a theory that part of the reason people do/do not like looking at SQL in code is because it’s a hard context switch from one language to another, often requiring the programmer to switch to “stringly-typed” mode, something we all learn causes huge numbers of headaches in our first few months of programming. Some developers accept that there’s going to be different languages/contexts and not all of them are going to be as fluent or familiar, but accept that this is par for the job. Others recoil from the unfamiliar and want to burn it down. IMO, the former attitude is a lot more productive.
My running joke, after four different friends told me they were using ChatGPT to help them with it, is that the language is so hard to learn that we invented an entirely new class of AI to help.
It’s a joke, of course, but it does have some “surprising” syntax, since some stuff is whitespace sensitive, and there are subtle differences between () and [] and [[ ]], for example. All of that’s due to the long history of shell behavior, so I don’t necessarily blame bash.
I would recommend email for this. It’s a text-based protocol and the original RFCs 821/822 are pretty straight-forward. There are some additional rabbit holes related to content encoding, but if one can implement a simple MTA, a huge amount of the magic of the internet becomes accessible.
I would not recommend trying to build a “production grade” MTA, as there is a lot of minutia to get right, and it’s easy to screw up.