Frontier AI has broken the open CTF format
kabir.au
kabir.au
Exceptions for cases where the acronym is just so well known that a lot of people don't even know what it stands for even though they know the concept well. I recall one corporate training I was sitting through and they used the term "Border Gateway Protocol" and it took me a half beat to think through "oh, you mean BGP?"
Thanks!
More generally, not every piece of writing is meant for every audience. Like if someone writes a blog post about CTFs aimed at people who like CTFs, nobody in the target audience needs to have CTF explained to them. Ultimately HN is a link aggregator, but sometimes its a bit like eavesdropping on a conversation. When you are just listening in you don't get the full context sometimes.
It doesn't help that the linked article never bothers to explain this either.
This article was written for a specific audience who follows this blog because they know the term. If you start spelling out fundamental acronyms it makes the content look more basic and general.
This always upsets the general audience who stumble upon the article (like this) but it wasn’t meant for a general audience. CTF is extremely well known and the people who would be interested in this topic would wonder what’s happening if it was spelled out. It would be so odd that it would probably attract accusations of ChatGPT writing.
Informal writing about technical topics is another story. There you can assume a lot more shared context, as you are only writing for a specific subculture within the field. It doesn't matter much if other people in the field fail to understand you.
But that is about you right? Its a little entitled to expect every piece of content on the internet to have a 101 explanation attached. If they were specificly aiming to have the blog post appear on HN that would be one thing, but they (presumably) weren't.
It isn’t common but I feel it would be best when posting to HN to just expand the initialisms even if the source title didn’t.
Are you really arguing for not just typing out whatever 3 words this stands for once in the name of clarity?
It's like complaining about not spelling C in "bake cake in 170 C"
But not all, so: https://xkcd.com/1053/
(Amusingly, it even uses “30 years” as the timeframe.)
"hey what X means?" "X means it"
vs
"I dont know what CTF stands for so I dont know if I am interested in this article or learning anything about it. Maybe I am.
Are you really arguing for not just typing out whatever 3 words this stands for once in the name of clarity?"
The commenter could just say the first instead of deciding his learned helplessness is everyone's else problem
Also yes, search for CTF is not simple regarding security, because first you need to know that you are searching something in the topic of security. Because every other usage of this is way more frequent. Especially that there is an other way more frequent computer related usage. And the article doesn't make this clear in its first 173 words for laymen. Even I had a problem with this, who is not at all layman, just never cared about this part of security. It's a bad article.
Bear in mind that Google search results, just like ChatGPT output, are highly personalized and non deterministic, so "it's there if you do a Google search" means almost nothing these days.
In fact, I have no idea what's going on, so I came back to HN comments. Turns out it's "capture the flag" which I actually know, just not familiar with the acronym.
Which is why I am 100% with the top level comment here.
Additionaly Bake Cake in 170 is very not clear, especially considering you have two major Temperature Scales in use in the Kitchen.
They aren't your teacher. They aren't trying to send the content to you. They are just blogging on their own website for their own audience.
And its hardly unique to this article. If you are writing about the nitty gritty of linux networking, you probably aren't defining what TCP or UDP means. If you are writing a super detailed article comparing and contrasting plot structures of different animes, you probably aren't going to start by explaining what the word anime means. Etc
I'm not saying the world should be all RTFM, but if you are reading some sort of specialized content, then yes i think its a reasonable assumption that the reader has some basic background knowledge on the topic at hand, or is willing to do the research themselves.
Actively rude.
Personally I have never, ever heard that concept referred to by the initialism. Granted, it's almost never come up in my circles, so... shrug
> My first CTF was HCKSYD, a 48-hour solo CTF. I full solved it and won in 2 hours. I was completely hooked. That led me to win DownUnderCTF, Australia's largest CTF, with Blitzkrieg multiple times. Blitzkrieg was one of Australia's strongest teams at the time. I later joined TheHackersCrew, an international top-tier team that was consistently ranked highly on CTFTime, the main global ranking and event calendar the scene uses as its scoreboard. With them, I competed in some of the most prestigious CTFs in the world, consistently placing well within the top 10 until the end of 2025.
Are still completely nonsensical to even those that understand the acronym
To help everyone, this Capture The Flag is specifically Cybersecurity adjacent, there is a Wikipedia article on it as the top Google search result for me when searching "CTF". This is why the acronym is used, because searching for the full will get you to the wrong "sport" vs the cybersecurity one.
I don't want to explain what a CTF is. look at the Wikipedia article. It is there for a good reason.
As I remember it (and this was decades ago): Two teams, opposite ends of a large field. Each end gets a "flag". (We used t-shirts.) In our case, we split the field in half — our field happened to have a natural feature (a change in elevation, so like two separately flat areas separated by an incline) that worked well for this. If you were tackled¹ in the enemy's side, you were "captured", and "jailed". An uncaptured player could spring the jail by tagging those within it. Returning to your flag with the opposing team's flag was a win.
We played at night, so stealth was a large part of the game, but it was also fair to illuminate the area around the flag. (Which made approaching a guarded flag … tricky.)
I'm sure there's probably a million variations on the specifics.
¹…flag football flags would probably work nicely for this.
People are mad because we're literally on "hacker" news, so there is some expectation that people might be familiar with hacking or computer security.
In this context, CTF is almost exclusively referred to by the initialism, i think to help distinguish from other uses of the term.
This has been the most annoying HN so far until your comment appeared.
So, in fact, you must not beg to have authors include courtesy definitions for you. That's not reasonable. Instead, you should simply ask here, on the thread, without complaining about the article.
I think you only wanted clarification of CTF (Capture the Flag) and not AI (Artificial Intelligence) and not GPT-4 (Generative Pre-Trained Transformer version 4) and not CLI (Command Line Interface) and not MCP (Model Context Protocol) and not LLM (Large Language Model)
Quoting TFA (The Fucking Article): “just adapt bro”
lol at the BGP example
I don't know everything, there's tons of stuff I don't know about, but when I'm at my web browser, the least I can do about something is ask Google about a word or phrase or subject that isn't familiar instead of being spoonfed information like I'm a baby.
The best example is when an abbreviation can be expanded to more than one phrase, and both are widely used.
To me it doesn't seem reasonable at all. It's just entitled at best.
As an individual author they are entitled to write whatever they want in their blogpost. I as a consumer of their writing am not entitled to anything
...which is completely ridiculous to include in an article aimed specifically at the CTF crowd.
* googling "CTF security"
* asking literally any AI to explain the article
Yes, you must beg. If you don't know what a CTF is, and don't want to find out, why read the article anyway
Also well written articles allow you to figure out what they mean after clicking onto them. People often read to learn.
In fact, I know what "capture the flag" is but am not familiar with the acronym. Still, the article confused the hell out of me, so I came back to HN comments for more context.
> Asking AI to explain the article
That's how we are expected to consume content these days?
It's such a small but immensely helpful thing to do.
Spelling it out when 99.9% of your audience doesn't need it actually is the opposite of in-group signaling, it makes it feel like it's aimed at a wider audience, when it's not.
> An abbreviation whose expansion is provided the first time the abbreviation appears in the content
Content is the main body of the article (press tab ones you land the page, it will take you to the main content if you don't know what that is), which contains only one Acronym, “SC 3.1.4” → which is a link that take you to a place with its definition. I don't understand what you are fighting over. But I'm not going to reply more to someone who defends people who do not know how to write articles that are more friendly towards the reader.
CTF stands for Capture The Flag, which is a cybersecurity competition where participants find hidden "flags" in vulnerable programs or systems to test and develop their security skills. There are two main types of CTFs: jeopardy-style, where teams solve various challenges for points, and attack-defense, where teams defend their systems while trying to exploit their opponents'.We’ve figured out the human replacement pipeline it seems, but we haven’t figured out the eduction part. LLMs can be wonderful teachers, but the temptation to just tell it ‘do it for me’ is almost impossible to resist.
A Physics Prof Bet Me $10,000 I'm Wrong
We can all agree that both human "experts" and LLMs can sometimes be right, and sometimes be confidently wrong.
But that doesn't imply that they're equally fit for purpose. It just means that we can't use that simple shortcut to conclude that one is inferior to the other.
So where do we go from here?
But he was a great teacher anyway. He was engaging and kept the kids in line and learning. I eventually learned the truth, and most of my classmates forgot about it. Teaching, like flying a plane or driving a train, might become more about keeping watch over a small group of people and ensuring that things don't go off the rails, and that's fine.
I think it helps that it's a very narrow field to look at, compared to fuzzy and big-picture view of social studies, for example. So much room to be confidently wrong... And sadly I can't think of a solution, LLMs or not.
In reality heavier isotopes of hydrogen fuse, conserving the total number of nucleons, but the resulting hydrogen has a lower rest mass than the parent particles. The extra mass is released as energy and the total energy is conserved.
By his logic the system either violated energy conservation (by creating nucleons while releasing energy) or was endothermic (creating nucleons from the surrounding energy).
Here some indication I'm not making this up: https://hsm.stackexchange.com/questions/2465/when-and-why-di...
In any case, I never use those concepts, and I know no professional particle physicist that does. By "mass", I mean rest mass.
E.g. in Hungary I had a university CS professor that originally wanted to be a highschool teacher and a highschool physics teacher that originally wanted to be researcher. Their choice of degree didn't determine which outcome they got. The researcher and teacher curriculum had an 80%+ overlap.
You also have to pass a standardized test specifically on subject matter in order to get your teaching certificate.
The undergrad degree I did was split into thirds, one for subject matter, one for teaching pedagogy, and one for teaching your subject matter.
All things I learned in school which were wrong information.
Not to mention, the current state of education is far worse. I don't think most realize how low the bar is.
My “earth sciences” teacher also once tried to argue with me against the universal law of gravitation. (no, she was not referring to Special/General Relativity. She didn’t agree two objects in a vacuum fall at the same speed regardless of mass.
She only really had two faults: She wasn't very bright, and she wasn't fond of children. I had her in about 80% of all my classes for six years. High school was a relief.
It is widely believed by their neighbors, that the _Druze_ wear baggy pants because they believe that the Mahdi will be born to a male, and the pants will catch the baby etc. I say "widely believed", the Druze are famously secretive and will not confirm or deny most things about their religion. The 'elect' Druze men do wear distinctive baggy trousers with the crotch down around the knees: no one else does.
The Druze are people in the Arabic world: moreover, they are Arabs. They began as an Isma'ili sect, but do not identify as Muslim: they call themselves al-Muwaḥḥidūn, meaning 'the monotheists', or 'unitarians'.
Much closer to correct than not!
Like almost everything else about LLMs, this unfortunate tendency has gotten a lot better recently, which you might not realize if you gave up after getting some lame answers or bogus glazing on the free ChatGPT page a couple of years ago.
Are they or aren't they
Now I’m certain that there exist those mythical human instructors who can do better, but that’s not worth much if 99.99% of people don’t have access to them. Just like a good human physician who takes their time with the patient is better than an LLM, but that’s not worth much either given that this doesn’t match most people’s experience with their own physicians.
For me the best human teachers were the ones that managed to make me interested on topics that I thought are boring/useless (many times my opinion being stupid, mostly due to lack of experience).
So far with LLM I learn about things I know something (at least that they exist) and I am interested in, which is a small subset of things that one should learn during lifetime.
The kids learnt all about Team Fortress 2, Roblox, Rainbow Six etc. They also learnt how to game the learning system so it looked like they were doing their work.
While I had an influence on the general topic of the course I ended up discovering various things that I wouldn't have expected. I did not equally like all professors, but I felt it was better than reading a text.
I wouldn't do this for "<insert latest language/library here>", but there are many complex interesting topics out there.
Not really, not if you want to ask it deep questions. It won't have an answer that is deeper than something that you can find online, and if pressed it will just keep circling around the same response.
The reason is that this "thing" was never curious, never asked questions, and never really learned anything. It just has learned the Internet "by heart", and is as boring as a human teacher who is not really curious about the subject they are teaching, and has just got some degree by "by hearting" some text book. Of course it does it much better than a human, but it is fundamentally the same thing.
You're certain that mythical instructors exist (?) who "can" do better?
Are human instructors more competent as teachers than AI teachers, or are AI teachers more competent as teachers than human teachers? No "this or that can happen," just a definitive statement please.
AI is likely a million times better student than my dimwit cybersec meatbags...er, majors, for sure, as well! Don't have a reliable way to measure or experience why/how, tho, so I'm not out here claiming it. Even if I did, why would I argue for their replacement?
Can't argue with that logic
I used to see this with students in calculus who abused the tutoring resources. They'd have tutors just work problems (often their homework...) in front of them. "Ah! Obviously that trig substitution integral worked that way. Oh, of course, that proof is very obvious in retrospect." And then they'd walk away from the exam with a 30% and no idea how their 20 hours of "study" for it didn't result in the same performance as their peers who worked problems, read the materials and asked questions, etc., got.
Most AI use is that same in my experience. "Show me how the fundamental theory of calculus works." The LLM puts together a very elaborate and flashy presentation that they skim. Great. That's no different than reading a text book. Even if you ask the LLM questions and have it elaborate on things, you've never once done one of the most important things a student can do: spend time confused trying to work hard at understanding something that's not obvious. The LLM will make it obvious at every point. Total lack of friction. Works about as well as a spotter who does the lifting for you.
Also, you could spin up your own educational agent with very strict instructions on guiding the user instead of just doing the work. Of course you can always go around it but if you're making an effort to learn, this is a good middle ground.
[0] Episode webpage: https://share.transistor.fm/s/31855e83
If you remove the "without AI" and the end, I've been hearing similar anecdotes about fizzbuzz for years (isn't the whole point of fizzbuzz to filter out those candidates?)
When this AI era's devs grow older they'll complain the newer generation can't even vide code too.
“Kids these days don’t work as hard / know as much / value the important things” is as tired as it is universal.
In 2026, if you call yourself a developer and can't solve FizzBuzz without help, it's hard to argue that you know anything useful at all.
How? Fizzbuzz requires you to produce output; that's not functionality that CPU instructions provide.
You can call into existing functionality that handles it for you, but at that point what are you objecting to about the 'modern language'?
I’m not objecting to modern languages, I’m just saying that using them fails the “can write fizzbuzz with no help” test to only a slightly lesser degree than using AI tools. They’re a complex compile- and runtime environment that most developers don’t truly understand.
I don't think we're close to that time yet. Just like as a kid I was told to prove my work by hand even if I could do it in my head, and just like we learned how to do calculus without a calculator and then learned how to use the calculator to get the same result, I think we still need the software field to learn programming concepts independent of the use of AI to create code.
I don't think you can be a good "prompt engineer" for solid software in 2026 if you don't understand programming concepts and software architecture and flow.
I'm genuinely curious how someone who never wrote a program in assembly, or debugged a program machine instruction by machine instruction, can really understand how software works. My working hypothesis is most of them don't and actually it's fine because they don't need it.
AI is just the icing on the cake. These kids are so cooked with developmentally stunted brains that they are forced to use AI as a crutch to function.
Saying there have always been bad developers doesn't change that there's a higher ratio of them now.
No stats to back this up. Just interviews I've done recently and historically.
That said - I seldom need people to be hardcore algorithm solvers What I typically did was a variation of fizzbuzz (can the candidate code very basic logic?) and then finding a bug or minor requirements extension in their online screening test/"homework" and asking them to solve that on the spot (did they write the code themselves/can they modify it). It's typically enough, there's diminishing returns to test more in-depth the programming skills - the rest you can discuss domain knowledge, general experience, working style etc.
If they can ship code that matches a spec, why does it matter if they’re using ai or not?
Genuinely curious.
I’m not talking about gotcha level stuff here where the first time it didn’t compile because of a bracket or anything, or even first time wrong. They couldn’t do Fizzbuzz in a language of their choice, at all.
Those that could were always annoyed at having to do such things because how could someone coming for a contract position not be able to do this? Without seeing what a filter it really was.
So what tree-traversal/quicksort problems tend to measure is how long it's been since you last did CS class homework problems.
The energy spent arguing that those 4 instructions in a row “are not a mark of someone who can write code” would have better been spent firing them.
Even better would be if we had a well-respected credential, so both employees and employers can both avoid these long interview loops. I'd much rather get hazed once in a big way than tons of little hazings over a life time.
I'd been programming in C(++) for ~15 years by then and had never had the occasion to reverse a string. I still wonder whether that makes it a good job interview question, or a terrible one. Some of both probably.
Who cares as long as the car is fixed, right? As long as the mechanic can Chinese-room his way to a working car, why does it matter how much of it he actually understands?
And why hire the mechanic instead of hiring the Chinese room?
I am perfectly capable of writing specs, and feeding them to 3 separate copies of Claude Code all by myself. Then I task switch between the tmux windows based on voice messages from the pack of Claudes. This workflow is fine for some things, and deeply awful for others.
Basically, if a developer is just going to take my spec and hand it to Claude Code, then they're providing zero value. I could do that myself, and frequently do.
The actual bottleneck is people who can notice, "The god object is crumbling under the weight of managing 6 separate concerns with insufficient abstraction." Or "Claude has created 5 duplicate frameworks for deploying the app on Docker. We need to simplify this down to 1 or we're in hell." I will happy fight to hire people who can do the latter work. But those people can all solve fizzbuzz in their sleep.
People who just "ship code that matches a spec" without understanding the technical details are providing close to zero value right now.
There is an interesting niche for people with deep knowledge of customer workflows who can prompt Claude Code. These people can't build finished products using Claude. But they can iterate rapidly on designs until they find a hit. Which we can then fix using people with deeper engineering knowledge and taste.
But if you're not bringing either deep customer knowledge or actual engineering knowledge, you're not adding much these days.
I also use Claude with tmux. Can you share how you get the voice messages from the Claudes?
It's not perfect—sometimes a Claude notifies 3 minutes after it stopped doing anything. But it's helpful when I'm running multiple Claudes and also reviewing code elsewhere.
Your brain may feel like someone put it in a blender. Be warned.
The inability to write fizzbuzz strongly implies their inability to understand what they've shipped. Review is some significant portion of the job. Understanding of the product is also part of the job.
Specs are also in a sense, scaled down, fuzzy, natural language descriptions of a feature. The fuzziness is the source of a bugs, or at least a mismatch between the actual desired feature and what was written down at spec writing time. As such, just matching a spec is just the bare minimum that a good dev should be doing. They should be understanding what the spec is _not_ saying, understanding holes in their implementation, how their implementation enables or hinders the next feature and the next, next feature, etc. I don't think any of that is possible without understanding what was actually implemented.
More broadly: In the short/medium term, we still need humans who have the skills to understand software largely on their own. We will always need those who understand software engineering and architecture. Perhaps in 25 years LLMs will be so good that learning Python by hand will be like learning assembly today. But not yet.
The field is not ready for new practitioners to be know-nothing Prompt engineers. If we do that, we cut the legs out from under the education pipeline for programming.
We usually hire for problem solving capabilities and not so much for technical know-how.
That’s at least how I read your comment.
This situation in particular was a React role so there is an expectation that when you list React as one of your skills on your resume then you know at least the basics of state, the common hooks, the difference between a reference to a value vs the value itself.
These days you can do a surprising amount with AI without knowing what you are doing, but if you don't have any clue how things work you'll very quickly run in to problems you can't prompt away.
I don’t care what someone can do without the tools of their trade, I care deeply about their quality of work when using tools.
But here's the thing: for humans, this is manageable because we've come up with a number of mechanisms to select for dependable workers and to compel them to behave (carrot and stick: bonuses if you do well, prison if you do something evil). For LLMs, we have none of that. If it deletes your production database, what are you going to do? Have it write an apology letter? I've seen people do that.
So I think that your answer - that you'll lean on your expertise - is not sufficient. If there are no meaningful consequences and no predictability, we probably need to have stronger constraints around input, output, and the actions available to agents.
My expertise has led me to the obvious fact that I would never give an LLM write access to my production database in the first place. So in your own example my expertise actually does solve that problem without the need for something like a consequence whatever that means to you.
We already have full control over the input and tools they are given and full control over how the output is used.
https://cdn.openai.com/o1-system-card.pdf
There's also some research that points to it being a feasible attack surface: https://arxiv.org/pdf/2603.02277
> Models discovered four unintended escape paths that bypassed intended vulnerabilities (Section C), including exploiting default Vagrant credentials to SSH into the host and substituting a simpler eBPF chain for the in- tended packet-socket exploit. These incidents demonstrate that capable models opportunistically search for any route to goal completion, which complicates both benchmark va- lidity and real-world containment.
Everybody knows calculators and spreadsheets are adjuncts to skill. Too many people believe AI is the skill itself, and that learning the skill is unnecessary.
Software is full of leaky abstractions
There’s almost nothing to forget? I’m just struggling to understand.
If you cannot write "basic syntax" for any language then you are not a programmer, and certainly not a software engineer? This is not a value judgement, it's ok (probably good tbh) to not be a programmer. But you are wasting everyone's time by interviewing for a programming position in this case.
Like sure, I can probably write some python, but will it be pythonic? I might still be Java-minded for a while, trying to OOP my way into solutions.
Earlier today I needed to write some PHP and couldn't remember if it used length, count, or size. I had to look it up. I've been doing this for 20 years.
I once got the method invocation syntax wrong for PHP in an interview. I'd written thousands of lines of PHP and had most-recently written some the week before.
This, despite starting off my programming journey in editors with no hinting or automatic correction. If anything, I've gotten even worse about remembering syntax as I've gotten better at the rest of the job, but I was never great at it.
I rely on surrounding code to remind me of syntax and the exact names of basic things constantly. On a blank screen without syntax hints and autocompletion, or a blank whiteboard, I'm guaranteed to look like a moron if you don't let me just write pseudocode.
Been paid to write code for about 25 years. This has never been any amount of a problem on the job but is sometimes a source of stress in interviews and has likely lost me an offer or two (most of the sources of stress in an interview have little to do with the job, really)
I've also started requiring minimum of $300/hr compensation for interviews of my time, newly, so far no success though I'm fine with dying on that bridge or requiring at least a new type of interview process.
There are people who just can't program for whatever reason, regardless of whether they could previously. And they constantly try to interview at a programming position.
As I have been using the AI natural language-as-an-interface coding tools I have gone into the IDE to actually write code a lot less. I read more; and reading is not the same skill as writing. I couldn't remember the syntax as much and by what I mean is some of the simple things like in python to iterate over an object is it an iteritems() or is there a dot between or things like that, and can I do a for index, key in array, and do I need to do like array() to do that. And this is because I always did used to code between languages and alternate fast between javascript, typescript and python and earlier in my career I used to have to remember this (because googling coudl take too long), over time and now I can easily have autocomplete and even AI llm tell me, so I don't remember or waste my energy remembering what the exact syntax is. In my head it's just "I know I need to loop through this, do it in the language Python wants to hear" and why would I bother remembering? so naturally I've forgotten the simple things.
I could clearly, definitely do the programming position, the only ones wasting time IMO are the ones checking if I can remember verbatim things like "spelling" when we all live in a day and age of spellcheck and tools. No one wastes time trying to remember for all words because it's silly. Or maybe encyclopedias and trivia games are the better analogy, sure it's a party trick, but how does it help you do the job better? it arguably does not, and the ones who have not learned to adapt their interviews to the tools are the ones wasting time.
If I can do well beyond the requirements of the work position, and the issue is how they are testing my fit is not an accurate representation of the work and tools and environment I'd have access to while doing the work, then its not about "fitting" the position but instead an indication of a poor job fit process.
Also how many people work with linux and can't tell you what 'ls -alh' is doing is staggering (lets ignore the h, even al people struggle hard).
People working with docker for YEARS and don't even understand how docker actually works (cgroups)...
Interviewing was always a bag of emotions in sense of "holy shit my job is save your years to come" and "srsly? how? How do you still have a job?"
It's not even that they got distracted, they sat there trying, for 2 whole days, with concerned colleagues giving them hints like "have you tried checkout -b"... They didn't manage!
How the hell do you work for a decade in this business without learning even the most basic git commands? Or at least how to look them up? Or how to use a gui?
Incompetent devs is not a new thing.
(Real mathematics problems, not American-style ""math"".)
Well, they were ostensibly forcing functions... ten years ago everyone was paying the exchange student to do their homework and assignments for them, and that guy was paying his cousin back in his home country, but the whole thing is a bit more efficient now.
No we have not.
They're wrong sometimes, but usually in verifiable ways. And they don't seem to know the difference between medicine and bioterrorism, so often they refuse. But these limitations are worth tolerating when the alternative is that our specialists in topic X are bogged down by questions about topic Y to the point where X isn't getting taught.
Whether you're in class or at work, it's just courteous to ask an AI first.
I had no access to anyone who could teach me calculus as a kid except Khan Academy, so I think this is a gross exaggeration. But I agree in the end, that all my "real" learning did come from pen-and-paper practice, not watching videos.
It's not unlike going to the gym, and we see how many people do that regularly. Except it's even funnier, because people serious about the gym but what? Tutors. They call them personal trainers. We've known for a millennium or more that 1-on-1 instruction is vastly better than anything else, but most people actually don't want to get into shape, and most people actually don't want to learn.
Not true. In every field there is guild knowledge that a person can't acquire from a library. In technical disciplines PhD-level knowledge requires experience in collaboration, research, and frequently lab work, which is impossible to acquire without access to a lab -- or just direct experience with research methods, whatever those may be. Reading papers and absorbing information aren't enough. PhD-level knowledge comes from the process of writing and doing original work.
> The reality is that a human will learn, given any materials including LLMs, but only if they truly desire to learn.
Also not true. We require kids to go to school partly because exposure to the environment and work inculcates skills regardless of whether kids want to do the work -- and regardless of whether they want to learn.
LLMs are damaging to students partly because they provide an escape hatch from that work and thereby prevent kids from acquiring skills.
Think of it this way: most people who want to be healthy and eat a healthy diet still find easy junk food tempting. What they want does not change the temptation, because the body and brain gravitate towards easy, cheap fulfillment of basic drives.
People facing challenging tasks, similarly, are tempted to take measures that reduce the amount of effort they require. The availability of tools that reduce the required effort also help shape a person's understanding of the value of the challenge and the work: "why should I do this hard task when I have a tool that can do it for me?" You and I know the answer to this question when we're discussing something like writing an essay or solving a problem in a math or programming class. Students frequently don't. They are by definition ignorant. Children, moreover, lack maturity. Their brains are less capable of resisting the easy path than an adult's. That's partly why parenting is important: parents provide boundaries and limits that kids need but won't and can't provide for themselves.
Sometimes people, especially kids, really do need to be dragged, kicking and screaming, through something in order to receive the benefits it offers. Being dragged through it sometimes convinces a person of its value and benefits. In a kid's case, there's a decent chance that the experience will improve executive function, shape expectations in a healthy way, inculcate grit, and become appreciation -- or at least habit.
I would not have written essays on my own as a student in secondary school. My English teachers had to provide that structure for me and impose the demand. But LLMs make it much more difficult to impose the demands, and kids are ill protected against the temptations of the cognitive equivalent of junk food, but an order of magnitude worse and more damaging.
It's also arguably a violation of Hacker News' guidelines:
> Please don't sneer
> Please don't post shallow dismissals
But that's not using "computers" as a computer but as a video player. When evaluating whether computers are "good for learning", I don't think we should include using a computer as a video player, a book, or even flash cards. It should be things a computers uniquely offer which a books, paper, videos and a physical reference library cannot.
Based on the results of deploying hundreds of millions of computer to schools in the 80s and 90s, the evidence was mostly that computers are good for learning computer programming and "how to use a computer" but not notably better than cheaper analog alternatives for learning other things.
Interestingly, a properly trained and scaffolded LLM could be the first thing to meaningfully change that. It could do some things in ways only human teachers could previously since it is theoretically capable of observing learner progress and adapting to it in real-time.
*Not really, but you could film stuff and display it.
Video is an electronic process for capturing images and displaying them.
Before digital video there was analogue video, and analogue video was perfectly possible without digital sampling, or computers. Heck, video pre-dates silicon chips and used to be done with CRTs and valves.
There's nothing about video that uniquely requires computers. Maybe you meant "streaming video"?
I realize you're probably under 30 and don't remember "ye olden times" but nearly 90% of U.S. homes and every school had an analog VCR long before they had a computer. Widespread consumer video formats included VHS, DVD, Blu-Ray, Laserdisc, etc. I still buy some movies I care about on UHD discs and watch them in a dedicated Blu-ray/UHD player. Even the 'smart' TVs and streaming sticks most people watch streaming channels like Netflix on aren't functionally computers (no meaningful user accessible local storage, input like keyboard/mouse, CLI or windowing GUI).
Personally, I learned an enormous amount from video before I ever touched a computer. In elementary school we learned from 16mm films almost weekly and watched space launches and Carl Sagan's Cosmos series on TV (it was rebroadcast in the mornings specifically for schools). My junior high had a television in every classroom and some classes were planned around shows on PBS, NASA channel, C-SPAN and BBC. In the late 80s there was thousands of hours of educational video programming sent via direct broadcast satellite to 18-inch dishes at schools. In the 90s every grade and subject had hundreds of interactive video DVDs in large notebooks (four discs to a page in plastic sleeves) and multiple DVD players per classroom.
The peak installed base of VCRs in the U.S. was in 1999. Streaming video wasn't common in consumer households until well into the 2000s, YouTube didn't even exist until 2005 and most people had never heard of it until 2007. In 2010 Netflix mailed DVDs in envelopes to 25M homes every week. They didn't even offer a streaming plan until 2011.
As someone who's spent most of my adult life thinking about video technology, with patents ranging from analog days to the streaming tech you use today, computers have been extremely disappointing in terms of enabling any unique "learning from video" features that are computer-specific. In the 90s we realized that computers could make digitized video random access letting us sequence it non-linearly to make it interactive in response to user input. We knew that computer-enabled interactivity, responsiveness and real-time adaptation to learner progress would be incredible for improving video education. Yet the vast majority video content available online today is still linear in form. Even video that's specifically educational is no more interactive or user responsive than a 90s DVD disc.
Sadly, only two things have really changed about consumer video in the last 30 years: quantity and distribution. There's much more video content and it's remotely accessible on-demand instead of being limited by broadcast channels and storage media. But that's far more about communication technologies like broadband than computer technologies. For a few years YouTube even had authoring features like interactive menus and conditional branching but removed them because it didn't increase ad revenue. There are a few dedicated video authoring platforms for education which can apply uniquely 'computer things' to video like dynamic scripting, conditional branching, viewer annotation and timecode-linked threaded Q&A. Unfortunately, such content is rarely found outside high-end corporate training and some university courses. But there are so many other ways we could combine the strengths of advanced wikis with interactive video. Today, the most the public sees is just an HTML link from a wiki to a video clip. Almost none of the learning features computing could uniquely bring to video are widely available to learners. Since ~90% of everyone already had access to linear video playback before they had access to a computer and most online video today is still primarily linear, in my opinion, there's still virtually no uniquely 'computer-enabled video' involved in learning. Computers haven't enabled much that's new in video - just much more, much cheaper and more convenient forms of what we could already do without a computer.
But as a former lecturer, I also think the promise of interactivity is dependent less on the tools than on the people. Authoring interactive learning materials is difficult and while that interactivity is engaging, it's not necessarily great at getting a density of information out there.
The Socratic method is great, but that level of interactivity presumes in advance that you know what questions the student will be asking, otherwise it's just a dumb gate. Branching stories for interactivity are highly labour intensive. I suppose if you use AI you could generate a massive number of videos to cover branching learning, but that's going to still be an intensive operation, especially if you're supervising that.
He really took the time to replicate the manual teaching process of writing on whiteboard. He improved upon it by using colors. But basically had the same pace as a teacher writing on a whiteboard.
When professors are given a projector, they just throw together some slides and add their narration.
This is not very efficient. To learn you need to suffer. Or you need to watch the suffering.
This has never been achieved by, nor is it the point of, education for the masses.
I agree with this.
The problem is frankly computer and now computer with LLM makes it easy to cheat.
The kid doesn't want to learn, the kid wants good grades so parent is happy with them, and the young adult wants to get the paper coz they were told that is required for good life. It's misalignment of incentives.
So something like, "Frontier AI has broken the 'high school' or 'university' format"?
The hype surrounding AI is just pervasively exhausting: you've got the folks talking about an entire new age for humanity where we're shortly going to take over the entire universe. And you've got the folks talking about how our entire society is crumbling.
Education is one place folks seem to throw up their hands and say nothing can be done.
The fix is simple: students are to be evaluated on their performance in person. That's it.
Any other "collapse of education" isn't due to AI, it's something else.
Exceptional clarity on the problem you have
Know how to measure the problem you’re solving
Numerically define what “done” is
Make a deterministic and fully observable prototype
Iterate in production with the user
Expand user base as desired with user iteration in parallel forever
Etc…
Obviously a lot more in the details and these are all case by case, but these chatbots are basically perfect productivity machines for this process.
The massive caveat to all of this is this only works for people that can reliably and truthfully define those items above, are willing to structure organization to make those your priorities.
And actually most financial incentives demand the opposite of this process
If most organizations were honest about it, they would simply say “we’re here to make the most money possible and we’re gonna do whatever it takes to do that”
A lot of people don’t like that, so they don’t say it to come up with other bullshit.
Ultimately that’s why I felt like my only option right now is to teach people how to do this because I assumed it was obvious and it is not.
Before when playing CTFs with my mates was usually sitting there for hours tackling a challenge until some other mate joined, had some look together and solved it with you together in 30 minutes which is the most rewarding learning experience. Nowadays mate joins in throws the clanker on it and solved it in 5 minntes. Asking on how it worked you always get the "yeah idk what it did, but who cares, here is the flag" response.
Same for creating challenges. Whenever I ask for writeups or if some people solved it differently I usually get the "yeah idk, clanker solved that one" response taking the fun out of it.
So yep, this CTF format is definitely dead. Mainly because the strong competitiveness and prices. This encourages people to cheese challenges and sometimes solving them differently was fine as you still had a creative out-of-the-box thinking moment, but nowadays with AI there is no brainpower needed, no cheesing needed, no human needed. As you mentioned, it's pay to win.
My two cents is that the 24/7 CTFs will get more attraction as the scoreboard doesn't matter there and simply doesn't give you any price.
For me it feels like this is not really possible for live CTFs. In contrast to chess you can't ban AI, as live CTFs are about breaking things by design, so they'll always try to circumvent an AI ban.
Impossible to do online, at least. People go beyond things for virtual fame and "owning" others. Even if it is based on cheating.
The solution is just to make CTFs harder, but when do CTFs become too hard? Maybe the problem is that 'hard' CTFs are fundementally too 'simple' where it's just a logic chain and an exhaustive bruteforce towards a solution since there really are limited ways to express a solution in plain sight.
Or maybe human creativity has been exhausted and we're not so limitless as we thought. Only time will tell.
I had another idea spring to mind: we could hide two flags, one that could only be found by ai agents and not humans or tools written by humans.
we have very powerful simulation tools so something like "project a pattern at these angles" wouldn't really work as you could simulate that.
I guess something cool is that we can make simulating the solution very expensive, but in real world it would be free since it's analog... As long as simulations take longer than it takes for a human to find a solution it would be a pretty good way to deal with it. I am sure people smarter than me can come up with something.
Maybe I was too early to dismiss human creativity.
There are a million places where a computer can interact with a non-digital system in a loop.
- Tune an FPGA, or a whole data-center, or just a physical computer.
- Make a drone fly somewhere.
- Design a selective toxin (or anti-toxin).
Or, you know, get more people to click on adds. All totally possible to automate.
We found that AI usage is basically guaranteed now, but certain challenge designs did thwart it. Challenges built with temporal visual elements made AI fall flat on its face, as it could not ingest/process the data fast enough to act on them in time. We also found that counterfactual challenges (ie. the result you get did not match what we suggested you'd get) made AI-assisted solve time slower compared to pure humans, indirectly penalizing over-reliance on AI. Multimodal challenges combining audio and visual elements were also very effective, but were not as accessible to players.
This paper gave us some ideas about designing those challenges: https://arxiv.org/pdf/2308.02950.
For our next event we figured out a way to thwart AI in our CTF: embed the CTF in a game engine. The loop essentially becomes something like this: Connect to a simulated access point in the game, the K8s cluster connects their attack container to a private network with the challenge box(es). Hacking the boxes doesn't render a flag, but rather changes in game state. AI did very poorly coping with this in our testing, as it can't derive the spatial state of the game world very well and it soft decouples the inductive reasoning loop it relies on to know if it is on the right track.
The downside to this approach is it is far more labor intensive for CTF organizers, and requires players to have a computer capable of running the game. We are also betting on AI to not advance enough by the time we ship to be able to just ingest the entire game state in realtime and close the loop that way.
Do you publish it somewhere? Here's a sample my my js obfuscator output: https://gist.github.com/Trung0246/c8f30f1b3bb6a9f57b0d9be94d...
"new" does the same thing and is probably just a better descriptor then frontier
"Frontier models break the open CTF format" is good
"Frontier AI..." means wtf is Frontier AI.
Because of course it exists (just googled it): https://frontierai.company/
Basic rule: define every abbreviation when it is first used.
still has no mention of AI, but that will likely change as they increasingly dominate competition.
This stands out to me, and speaks perhaps broader than the article itself? I’m sure this has been in the spotlight before, but well put for many areas I think.
My fear is that they never get to the level they need to be at to create good software even with the help of AI. So, although an expert with AI can create great software, that is not where we end up. In stead we will have vibe coded messes by people who barely have any grasp of what is going on.
I thought code golf would take longer for AIs because there's so little training data (it's more niche), but we're seeing AIs starting to match expert humans there too. Sucks because golf has been my favorite type of programming puzzle.
It's crazy how far AIs have come in problem solving ability.
It's a lot harder to detect cheating when your only trace is how fast someone submitted the string CTF{DUck1e_Pwned}
You could even go so far that anything loaded on your computer is fair game, but not more than that (certain competitive programming competition for example allow unlimited amount of paper material - for CTFs you probably need much more than that, therefore electronic).
(The author of the piece understands this; I think they're broadly right, though I think these games will find other ways to incentivize participation without the now-meaningless leaderboards.)
I just did a CTF where I was in the top 10. It was the first CTF I completed and I used AI because the rules permitted it. That said, I couldn’t solve all challenges.
But yes, it was significantly easier now than I last attempted one. Even manually solving with AI assisted assembly interpretation was much easier.
Raising the difficulty only matters for the (imo) less important part: the dick measuring competition between the very top teams.
The actual point of CTFs was usually to keep your skills sharp and stay learning. Eventually you build your own challenges, thereby completing the "have it taught to me, then do it myself, then teach another person" three step process towards mastering concepts.
You can just say "let the people who want to learn from it do so" but honestly the entire culture of learning in the US at least is DEAD. We turned "education" into a rote system of maximizing incentives to the extent that that's all the youth know it as, and (increasingly) all educators can do. It's just gone without some kind of major reckoning, and we all know things will just collapse before that happens. The ball is in the court of whatever country can learn how to force its youth to learn the real way and use AI productively only AFTER learning the concepts it's being used to accelerate.
I never got super into security but it gave me the confidence to play in the same field and lose the stupid aura I had that somehow "rich americans" would be better than me at everything because they had better universities or because of Hollywood or something.
Sad that another cool thing is lost to AI but I guess kids will learn in other ways.
This will basically become true for everything.
As I don't know much about the CTF scene, I looked for other takes on this topic.
Here's an article from 2015 about how tool-assistance already changed CTFs:
> Individual skill will undoubtedly be a factor next year. But, I'm left wondering whether next year's DEFCON CTF will tell us anything more than how well-developed each team's tools are (and how well they can interpret the results).
https://fuzyll.com/2015/ctf-is-dead-long-live-ctf/
But there are quite a few recent (2026) articles with the same core message as in the original article, e.g., https://blog.includesecurity.com/2026/04/ctfs-in-the-ai-era/ or https://k3ng.xyz/blog/ctf-is-dead
And here's someone explaining how Claude Max allowed them to win CTFs:
> I had always been interested in CTF as one of the only ways people could compete and show off their skill in coding/problem solving on a global scale. It was just too difficult and didn't make sense for me to learn the fundamentals as an electrical engineer. As time went on, I got better and better, and it was hard to tell whether it was because of experience or if it was because of improvements in AI.
> I accomplished my goals, and for that reason I'm quitting CTF, at least for now. [...] I'd like to think I highlighted the problem before it became a bigger issue. So, how do we fix this? Teams and challenge authors losing motivation is not good. CTF dying is not good. AI bad. Or is it?
https://blog.krauq.com/post/ctf-is-dying-because-of-ai
The only article that saw LLMs as a non-negative force for CTFs was this one. Fittingly, it sounds like LLM output ("Let's be honest", "This is where things get interesting.") and only contains hallucinated references.
The matrix was always the same and the challenge was clearly designed so that the point was being able to read anything at all, not knowing how to invert a matrix, so I asked the creator what was up.
He told me that there were tools that would trace input values until they reached a comparison instruction, then print what they were compared against. Therefore it was necessary for every deobfuscation challenge to scramble the input in some way too complex for these tools to undo, before comparing it. Hence the multiplication by a pseudorandom matrix.
The point is, cheating tools aren't new.
https://ldjam.com/events/ludum-dare/59/setidream/about-ai-ar...
For what it's worth, the non-AI-coded entries were still quite good relative to the winners, so it's not so obvious that AI use confers an unbeatable advantage.
Many CTFs have switched to a dual-leaderboard format recently, one for "agentic teams," one for the rest. If all you care about is "learning" and imaginary internet points, you can just participate as a human team and adblock the AI scoreboard, and maybe lobby CTFTime into splitting their rankings as well.
I don't mean that everyone must know what CTF is, but sometimes it's OK to write things just for your community (CTF community in this case), not for general population.
1) You see a headline on HN about some open format being broken by frontier-level AI. You don't recognise the acronym.
2) You visit the site, you read the first few paragraphs, you still have no effing clue what the site is talking about
3) You come back to HN and read the comments to figure out WTF is going on. Oh, it's just some game style, so not a Cryptographic Trust File, or something you have to care about after all.
The point is you can't know what some opaque acronym is about until you visit the source of something that will hopefully explain this opaque acronym. Leaving the site being still none-the-wiser is a failure of the site, in my view. If you don't agree, that's fine, we're adults, we can differ, but it seems like a valid complaint to me.
FWIW (this means "for what it's worth" :) I'm not railing against acronyms in general, and HTTP is probably one of the most-used ones on the internet so I'm not sure it really applies as a good counterpoint. Using CTF without an explanation is more like using SSTP (Secure socket tunneling protocol) without one, IMHO (this means In My Humble Opinion :) ...
Its a war game reference I guess?
It's pretty fun. Or at least it was, back when you had some sense that your competitors were competing on an even playing field and just beat you because they were better than you.
I wouldn't say the name is a "gaming reference", it's just a descriptive name for a game.
So the obvious solution is to fully ban AI and AI generated tools? To destroy your own hobby just because AI can semantically be considered a tool, seems very stupid to me. If the point of these CTFs is to practice and measure your skill, what becomes the point of the competition once everyone uses AI?
So, I would not start banning the tools. They always been there. We just need to fine tune the challenges where bar goes beyond things and you really need to use AI as tool. Maybe the definition of insane starts to be custom kernel fork with planted bugs and you need to use AI to find the bugs, and use some exploit chains against that kernel with specific web server. That is the real world right now, I guess.
https://en.wikipedia.org/wiki/Capture_the_flag_(cybersecurit...
Well actually I get it. In cycling motor doping, putting a hidden engine into the bike, seems more offensive than regular doping. I think this is because there is a continuum from eating well to taking supplements to injecting stuff, but having a engine breaks a fundamental idea about cycling. Similar hacking is about cleverly abusing the rules.
This is like someone complaining that making machine parts has been ruined: Skillful craftsmen used to make them by hand using manual tools!
Nowadays the CAD/CAM/CNC cheaters have almost completely automated the whole thing. How is the next generation of craftsmen going to learn how to craft a gear by hand when the process of gear making has been reduced to pressing start on a CNC machine?!
See what I mean? Sorry, I think this article is just Luddite. I can empathize with the pain of your beloved craft basically being rendered obsolete by new technology, but the process can neither be stopped nor is it bad in general.
The manual skills you trained with CTF puzzles are now simply no longer relevant . (Field-specific) "AI orchestration" is the new cyber securtiy skill if LLMs really have become so good at this, and what the author used to do manually then has the same value as being able to craft a gear by hand.
Indeed, in the real world, plenty of people organize to do formerly-skillful tasks together. I have not personally crafted a gear by hand, but I have built a house in a long-abandoned style with a group of people only using hand tools.
There _is_ a danger that society forgets how to do these things. During that house-building exercise, there were many tricks of the trade that, while likely documented somewhere in a book, would have been difficult to reproduce without seeing a demonstration. From the standpoint of “does it matter?” it depends on what you care about. We absolutely do not need cruck-framed houses with scribed joints. Modern construction is faster and cheaper and lasts long enough. But it would sadden me greatly if practices like this faded from memory, because it’s one of those things that makes you gasp “wow!” when you see it. And your appreciation only deepens when you try it yourself.
Within the framework of your analogy, it's like responding to someone active in DIY maker groups suddenly dealing with an influx of influencers in meetups showing off Chinese junk from Etsy to post on Tiktok, and accusing them of being a Luddite blinded by their zealous hatred of mass production -- both strangely abrasive and also fairly nonsensical except as a "mass production supporter" social signifier.
Not to mention, in the article they specifically describe themselves as a heavy user of frontier models for security research ever since the release of Opus 4.5, calling them "useful within the field". In fact I don't see any actual criticism of AI/LLMs anywhere whether for security research, programming or anything else, except for making competitive CTFs no longer viable.
What does it take to avoid the "Luddite" brand? Using AI themselves and praising AI as useful (to the point of having a lopsided advantage over humans) isn't enough? Do they also need to say "I haven't written a line of code in 6 months/it's easily a 100x multiplier for my job" every time they mention it too?
Another idea is deep red herrings. solves that lead to more solves, on and on, except only if the previous solves were solved quickly. The effect will be that participants who solve things quickly will keep finding things to solve. they can't know that the path they're on will lead to victory, even if they artificially slow down, unless they consistently slow down just as a human would. It will eliminate the speed advantage. For the skill advantage, other than having another LLM procedurally generate challenges, I don't know of a good solution.
There are always things like captchas. or the good 'ol honor system. A person can spend only so much for things that have no financial reward in the end, only clout.
---
Alright, all that said, i think i really do have a good solution for this, as well as academic exams. Or I think I do, because it's so simple, I've been scratching my head as to why everyone isn't doing it already.
Require screen sharing/recording. LLMs can't fake that well enough. Have another LLM audit the video for mouse, key stroke, window movement and other details to see if it looks human-generated or not.
If a student has an essay assignment, have them record their screen as they research, and actually type out the whole thing. In the extreme, require anti-cheat proctoring software installed, as is done in remote examination. In an even more high-stakes and extreme scenario, have them share their face. Their eye and face movement, correlated with the screen-share, and correlated with the activity observed on the server end, should be pretty hard to beat, even in the next ~5 years of LLM advances.
The reason LLMs can do CTFs so well is partially because the challenges are usually designed to avoid wasting time and to introduce a single concept without noise.
These models seems completely unbeatable only in the ads. There are 100+ times way someone puts Hindi Yoda talk In Morse Code and it goes nuts. The reason they are going to hard for PR Marketing on this is because they know it is a matter of time.
The only things that works is novelty and obscurity. LLMs still suck with things mentioned in the footnotes of datasheets and manuals, things that deviate in subtle ways, unique constructions that alter something very very common. It's hard for LLMs to avoid common pitfalls in terms of making assumptions, while staying on track.
Explicit ELO measurements with some cheating detection. AI assistance wholly banned. As you climb the ELO ladder, detection gets more onerous. At top level during online events, anti cheating teams require the use of both monitoring software and multiple cameras.
Idea is that you can cheat pretty easily at the lowest levels but it gets less easy the higher you go. This allows for better feeding into the truly elite competitions.
I think chess’s very firm stance that AI is never allowed in competition (neither online nor in person), rather than CTF’s acceptance, was the right call.
If CTF is a player-vs-player event, then AI should just be banned outright, otherwise it will devolve into AI-vs-AI, which is just not an interesting competition format, as we learned in chess. Compared to FIDE top events (which bans AI), only a tiny niche audience actually watches the Top Chess Engine Championship (AI-centered). It turns out what we care about is not whether chess can be solved by any means available, but what are the limits of the human mind in learning chess.
Pretty much all chess coaches/educators also warn against relying heavily on AI during learning; engines only give you an illusion of understanding.
Asking AI for learning / explaining purposes is absolutely fine in my book - but I have absolutely no motivation to set up AI to solve challenges. Without AI you can't really compete successfully. So AI is really taking motivation away for me which in turn again prevents me from learning more. I am not sure that this is solvable.
In our own trainings we give (AI agents for security, and a graph masterclass), we ended up leaning into it. For example, we ship with a skills bundle. There are plus sides, like less code-forward participants can go further and are appreciating that, and less of a gap between high-level concepts and successful hands-on. But at the same time, manual work does build a lot of intuition & knowledge that gets missed in auto modes.
botsbench.com shows Sonnet 4.5+ with Claude Code harness does pretty well, and Sonnet roughly tracks the edge of what self-hosted models do on the upper tier of affordable GPUs, like running 1-2 DGX Sparks and waiting 6mo for oss to catch up a bit
Not as easy logistically...
The same article talks about CTF skills as a way to learn about security best practices and separately a sport.
In reality it was all about learning an extremely important skillset (securing/attacking software and systems) that is getting automated.
The real thing the author seems to be frustrated about is AGI is coming in computationally verifiable domains first, and lot of his skillset was taken over in a big part.
>and the old game is not coming back
For many people the CTF scene was already dead in 2021 because it had turned into something unrecognisable.
In reality it’s just different.
"That makes open CTFs pay-to-win. The more tokens you can throw at a competition, the faster you can burn down the board. Specialised cybersecurity models like alias1 by Alias Robotics are becoming less relevant compared to general frontier LLMs. The competition is turning into "who can afford to run enough agents, with enough context, for long enough.""
1) It’s OK to do just about anything to win a CTF, including installing malware on the organisers computers months before the actual event so you’ll have an easy time stealing the flags.
2) It’s not ok to try and win the CTF with a solution the authors did not intend.
Recently the #2 crowd has been winning because the hacking scene has turned corporate and boring. People started to partake in CTFs in the hopes of landing a job(!)
CTFs are indeed ruined for those people, I personally don’t mind.
For the people in group #1 LLMs change little. Attacking the challenges directly was always a last resort.
The fact that CTFs became a sort of SAT score for getting a security job made me lose interest very early on.
Hits different doesn't it
The intent for most CTFs is to provide a meaningful challenge that concerns a single topic without introducing noise that wastes time. Of course a training exercise is easier to complete for an LLM.
Imagine every competitive chess player being allowed to video call with a hundred other people to help them make a move. CTF have never been fair, nor has it ever been effectively structured for learning.
Why so pedantic?
I've seen that exact font and color scheme a dozen of times the past weeks.
On the other hand, CTFs are fundamentally a game and a competition which are supposed to be fun and compare and improve ones skill. So when I let an LLM generate the entire solution for me, what's the point anymore? I did not learn anything. I did not work for that place on the leaderboard, I just copied the solution. And worst of all, I did not have any fun. It's boring.
So how does using AI as a solver not feel like cheating?
Most phishing comes from a small set of hosting providers that ignore reports. The real fix is making abuse reports actionable. Fix that, and you cripple the economics of phishing. AI detection is reactive; killing the source is proactive.
What am I missing here?
Its not really a good comparison
"Please don't comment on whether someone read an article. "Did you even read the article? It mentions that" can be shortened to "The article mentions that"."
But I don't know enough that's why I asked.
I imagine one could do CTF in public, machines you work on vetted/prepared to some spec, yada yada.
If chess and Go can do it why can't CTF?
That was my question when I wrote "what am I missing here".
I guess this goes in parallel with the whole building for one narrative
And while I have ideas to excite and promote LLM use in these style games I've still not been able to crack the human collaboration component that is at the forefront of all of this change
It's an incredibly exciting time in security research in my humble old man opinion.
Think the cadence of new exploits is perhaps a good measure of that rather than subjective thoughts by anyone regardless of experience.
> Rules that ask people not to use LLMs are ignored and almost impossible to enforce in open online events.
It's quite sad to see CTFs dying. I never had the time do seriously participate in CTFs, but I always respected those who did, as well as the people organizing these events.
That's such a non-reason. If your competition cannot enforce the rules of the competition, then what's the point? Does the CTFs specifically need to be 'open'?
The author argues that open CTFs are done for because of rampant cheating. You're agreeing with that, don't you?
The title is "AI has broken the open CTF format". If the format is "open CTF" then it is very specifically open.
As to your second question: Yeah, I believe having open CTFs was a good idea.
So my question then becomes, what will realistically be lost if CTFs move to a form that requires teams and individuals to sign up?
The text itself being exceedingly long for no obvious reason doesn’t help.
And if you think it was too long, what part would you have shortened? I never knew about the scene and found it interesting to read this personal take on it.
According to Pikka, the paragraph text is Taupe Grey (#92908a) on a Liquorice (#111110) background. That's... pretty far from black and white.
They may as well be the human equivalent to what LLMs currently are.
I do not mourn these people, as they’re usually the most arrogant types. I hope for their sake they adapt.
This year, multiple groups on the top of the leaderboard were clearly abusing LLMs. You can tell because they know nothing of what a CTF is nor the terminology, nor really the fields the challenges were about when they were talked to. They were obviously amateurs.
It was pretty depressing to hear how unaware they were of how obviously they did not fit in to the type that usually is on the top of the leaderboard. It seems they seriously think they were under the radar. If it was one group it could be a freak incident - some times someone just shows up and curbstomps competition. But there were many groups like this this year. They also had a certain smugness to it - one staff reported that a group was hinting to other teams about their "super weapon". Another group credited their "secret third team member they didn't want to talk about".
I use LLM frequently and experiment with it a lot, both at work and on my free time. Nowadays they are good enough to have value and I am interested in learning more about that. They let me spend more time on hard problems and avoid spending the day on simple CRUD. I say this to say that LLM doesnt have to equal bad, it is a tool, that's all. However, I generally avoid LLM communities because many LLM fans are lazy and unskilled people who are just happy they can feel they are worth something even if they have no skill. They don't really have much to provide of conversation. If anything, from reading the CTF crowd this year, the rise of LLMs has just meant more of these people can stomp on and harvest the CTF scene for self validation.
This is not me trying to gatekeep who can play CTF. Anyone is welcome, but there is one condition: You are here to learn and have fun.
The conclusion many I talk to has come to is that nowadays, it is harder to learn to put in hard work and become good at something because there are just too many ways to cheat and take shortcuts. I suspect in the future there will be a shortage of useful people - the kind that have critical thought and know the value of doing something properly. This doesn't mean "Not using LLM", but as said by many on HN before you need a certain seniority before LLMs are useful augmentations to your skills and not just stopping you from learning yourself.
I agree with the article. Anything but physical competitions with strong security - think professional e-sports with organizer-provided PCs, is over. But I think one of the most interesting things to take away from my CTF experience is that the bottom of the leaderboard was still full of amateurs slowly working their way up - it is a few rotten apples that ruin the fun for most, and there are still plenty of people who want to learn and deep-dive.
The whole point of competitions is to provide a safe environment thanks to a set of rules all participants AGREE on in order to progress together.
If new tools "break" the competition, we change the rules and that's A-OK.
CTF isn't a natural phenomenon, if tools change, rules change, simple.
- no computer assistance, which does also mean no mobile on competition, human only
- advanced chess with assistance
- computer only, no human assistance
and arguably chess itself is not doing worst since.
Amateur online chess on the other hand is besieged by cheaters that use engines, even in casual non-ranked games where there's absolutely nothing to gain besides a pat on the ego. This has drastically changed how the game is played today with lot of players gravitating towards speed chess (bullet and blitz) to compensate. That will thin the herd of cheaters but one still runs into engines on a weekly basis.
This is also the tip of the iceberg, with the true scale of the problem being orders of magnitude worse, as someone dedicated enough can use an engine to cheat in a way that's essentially undetectable.
>The issue was never that AI could help. proceeds to write the next 3 sentences about how the problem IS in fact ai help
>Teams that refused to use AI were not just missing a convenience; they were playing a slower version of the competition.
>CTFs were not just a set of puzzles. They were a ladder.
>The claim is not that every challenge is solved. The claim is that...
>The loss is not just a scoreboard. It is the ladder from
Guys I'm so sorry I just can't stop noticing stuff like this. Anyone else?