Yes, which is why you can look at the article to figure out if it is real or not.

Google CTF is always one of the hardest ctfs of the year.

Often people work on ctfs in teams, which can be really great for learning.

I haven't seriously competed for a while - the team I used to play with is all but disbanded. Back in the day I used to complete a challenge, maybe two, very rarely three in the top tier CTFs - out of 20-30 challenges - so definitely you need a team. (I also often got zero challenges and nothing to show for my time.)

I don't have any references for this but I remember reading that a couple of the bigger teams, those who would win often, had 30-40 players so they have one or two people working on each challenge in parallel. Of course, talent isn't equally distributed - My team usually had 10-12 people, of which maybe 3 people would get us 60-70% of the points we earned.

(I was not one of them. My personal goal was 1/n of our points, so if we were 10 people playing and got 5000 points, I'd be content if I solved challenges worth at least 500. I made it about half the time.)

Anyway, I don't think CS theory is necessarily useful for this - with the exception of the crypto (more on this later). What you really need is a combination of four things:

1) Solid understanding of the elements of each challenge type:

For web or misc, that's how to use sockets, make HTTP requests; what you can and cannot do (can you send a request with unescaped characters? Can you send the wrong Content-Length header? How big a payload can you realistically send?); what basic algorithms exist, how fast they can run and how to use them; Linux permission models. For pwn that's exploitation techniques, ROP, memory protections. For reversing that's reverse engineering techniques, the use of Ghidra or IDA or radare2, sometimes writing processor definitions for them.

For crypto you need to understand linear algebra over finite fields at the very least.

2) Fast learning: You will need to learn a new crypto attack, or the intricacies and gotchas of a particular JS framework, a new language, or a new embedded processor. In [1] you needed to learn what PIL can and cannot parse, how Pickle works under the hood, and, at a shallow level, how PNG image compression works.

3) Iteration. Challenges often have multiple steps. Solving one is usually not enough. Read [1] - it's a great writeup that highlights that point.

4) Resilience. I worked on [2] for a day and a half. But I'm not super up on lattice reduction theory and I didn't know about BKZ reduction. Other people didn't know about it either, learned about it as they went and solved it. I didn't manage. So I didn't solve it. That happens a lot. Live with it and do your best.

[1] https://emanuelmairoll.at/posts/hitcon2025-imgc0nv

[2] https://ibrahimadel.netlify.app/posts/filtermaze-google-ctf-...