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Curl: We still have not seen a valid security report done with AI help
302 indigodaddy 152 5/6/2025, 5:07:58 PM linkedin.com ↗
AI spam is bad. We've also never had a valid report from an by an LLM (that we could tell).
People using them will take any being told why a bug report is not valid, questions, or asks for clarification and run them back through the same confused LLM. The second pass through generates even deeper nonsense.
It's making even responding with anything but "closed as spam" not worth the time.
I believe that one day there will be great code examining security tools. But people believe in their hearts that that day is today, and that they are riding the backs of fire breathing hack dragons. It's the people that concern me. They cannot tell the difference between truth and garbage.
It's easy for reputational damage to exceed $1'000, but if 1000 people do this...
Most companies make you fill in expense reports for every trivial purchase. It would be cheaper to just let employees take the cash - and most employees are honest enough. However the dishonest employee isn't why they do expense reports (there are other ways to catch dishonest employees). There used to be a scam where someone would just send a bill for "services" and those got paid often enough until companies realized the costs and started making everyone do the expense reports so they could track the little expenses.
Looking at one of the bogus reports, it doesn't even seem like a real person. Why do this if you're not trying to gain recognition?
They're doing it for money, a handful of their reports did result in payouts. Those reports aren't public though, so there's no way to know if they actually found real bugs or the reviewer rubber-stamped them without doing their due diligence.
I wonder if reputation systems might work here - you could give anyone who id's with an AML/KYC provider some reputation, enough for two or three reports, let people earn reputation digging through zero rep submissions and give someone like 10,000 reputation for each accurate vulnerability found, and 100s for any accurate promoted vulnerabilities. This would let people interact anonymously if they want to edit, quickly if they found something important and are willing to AML/KYC, and privilege quality people.
Either way, AI is definitely changing economics of this stuff, in this case enshittifying first.
That makes it extremely hard to build a reputation system for a site like that. Almost all the accounts are going to be spam, and the highest quality accounts are going to freshly created and take ~ 1 action on the platform.
Personally I can't imagine how miserable it would be for my hard-earned expertise to be relegated to sifting through SLOP where maybe 1 in hundreds or even thousands of inquiries is worth any time at all. But it also doesn't seem prudent to just ignore them.
I don't think better ML/AI technology or better information systems will make a significant difference on this issue. It's fundamentally about trust in people.
To be honest, this has been a grimly satisfying outcome of the AI slop debacle. For decades, the general stance of tech has been, “there is no such thing as a behavioral/social problem, we can always fix it with smarter technology”, and AI is taking that opinion and drowning it in a bathtub. You can’t fix AI slop with technology because anything you do to detect it will be incorporated into better models until they evade your tests.
We now have no choice but to acknowledge the social element of these problems, although considering what a shitshow all of Silicon Valley’s efforts at social technology have been up to now, I’m not optimistic this acknowledgement will actually lead anywhere good.
> I feel like the problem seems to me to be behavior, not a technology issue.
Yes, it's a behavior issue, but that doesn't mean it can't be solved or at least minimized by technology, particularly as a technology is what's exacerbating the issue?
> It's fundamentally about trust in people.
Who is lacking trust in who here?
I don't know where the limit would go.
This was like two weeks ago. These things suck.
I wonder if you could use AI to classify the probability factor that something is AI bullshit and deprioritize it?
Yes. Unfortunately, some companies seem to pay out the bug bounty without even verifying that the report is actually valid. This can be seen on the "reporter"'s profile: https://hackerone.com/evilginx
This alignment problem between responding with what the user wants (e.g. a security report, flattering responses) and going against the user seems a major problem limiting the effectiveness of such systems.
Well the reporter in the report that stated it that they are open for employment https://hackerone.com/reports/3125832 Anyone want to hire them? They can play with ChatGPT all day and spam random projects with the AI slop.
Meaning, instead of listening to a real-life expert in the company telling them how to handle the problem they ignored my advice and instead dumped the garbage from GPT.
I really fear that a number of engineers are going to us GPT to avoid thinking. They view it as a shortcut to problem solve and it isn't.
Let's just say not listening to someone and then complaining that doing something else didn't work isn't exactly new.
Oh but it is, used wisely.
One: it's a replacement for googling a problem and much faster. Instead of spending half an hour or half a day digging through bug reports, forum posts, and stack overflow for the solution to a problem. LLMs are a lot faster, occasionally correct, and very often at least rather close.
Two: it's a replacement for learning how to do something I don't want to learn how to do. Case Study: I have to create a decent-enough looking static error page for a website. I could do an awful job with my existing knowledge, I could spend half a day relearning and tweaking CSS, elements, etc. etc. or I could ask an LLM to do it and then tweak the results. Five minutes for "good enough" and it really is.
LLMs are not a replacement for real understanding, for digging into a codebase to really get to the core of a problem, or for becoming an expert in something, but in many cases I do not want to, and moreover it is a poor use of my time. Plenty of things are not my core competence or anywhere near the goals I'm trying to achieve. I just need a quick solution for a topic I'm not interested in.
There are so many things that a human worker or coder has to do in a day and a lot of those things are non-core.
If someone is trying to be an expert on every minor task that comes across their desk, they were never doing it right.
An error page is a great example.
There is functionality that sets a company apart and then there are things that look the same across all products.
Error pages are not core IP.
At almost any company, I don't want my $200,000-300,000 a year developer mastering the HTML and CSS of an error page.
I’m saying this tongue in cheek, but there’s some truth to it.
I doubt the reason has to do with your qualities as an engineer, which must be basically sound. Otherwise why bother to launder the product of your judgment, as you described here someone doing?
It does NOT mean, AT ALL, that if it is worth writing, it is worth reading.
Logic 101?
1. *"If it's not worth writing, it's not worth reading"* is a normative or idealistic statement — it sets a standard or value judgment about the quality of writing and reading. It suggests that only writing with value, purpose, or quality should be produced or consumed.
2. *"There is a lot of handwritten crap"* is a descriptive statement — it observes the reality that much of what is written (specifically by hand, in this case) is low in quality, poorly thought-out, or not meaningful.
So, putting them together:
* The first expresses *how things ought to be*. * The second expresses *how things actually are*.
In other words, the existence of a lot of poor-quality handwritten material does not invalidate the ideal that writing should be worth doing if it's to be read. It just highlights a gap between ideal and reality — a common tension in creative or intellectual work.
Would you like to explore how this tension plays out in publishing or education?
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It seems the initial rule seems rather worthless.
2. So a rule with occasional exceptions is worthless, ok
You know how I know the difference between something an AI wrote and something a human wrote? The AI knows the difference between "to" and "too".
I guess you proved your point.
Yes is true there could have been a skill issue. But it could also be true that the person just wanted input from people rather than Google. So that's why I drew the connection.
There are three main reasons I can think of for asking the Internet a question in 2010:
1. You don't know how to ask Google / you are too lazy.
2. You don't trust Google.
3. You already tried Google and it doesn't have the answer or it's wrong.
Maybe there are more I can't think of. But let's say you have one of those three reasons, so you post a question to an Internet forum in the year 2010. Someone replies back with lmgtfy. There are three typical responses depending on which of the those reasons you had f or posting:
1. "Thanks"
2. "Thanks, but I don't trust those sources, so I reiterate my question."
3. "Thanks, but I tried that and the answer is wrong, so I reiterate my question."
Now it's the year 2025 and you post a question to an Internet forum because you either don't know how to ask ChatGPT, don't trust ChatGPT, or already tried it and it's giving nonsense. Someone replies back with an answer from ChatGPT. There are three typical responses depending on your reason for posting to the forum.
1. "Thanks"
2. "Thanks, but I don't trust those sources, so I reiterate my question."
3. "Thanks, but I tried that and the answer is wrong, so I reiterate my question."
So the reason I drew the parallel was because of the similarity of experiences between 2010 and now for someone who doesn't trust this new technology.
I see email blasts suggesting I should be using it, I get peers saying I should be using it, I get management suggesting I should use it to cut costs… and there is some truth there but as usual, it depends.
I, like many others, can’t be asked to take on inefficiency in the name of efficiency ontop of currently most efficient ways to do my work. So I too say “ChatGPT said: …” because I dump lots of things into it now. Some things I can’t quickly verify, some things are off, and in general it can produce far more information than I have time to check. Saying “ChatGPT said…” is the current CYA caveat statement around the world of: use this thing but also take liability for it. No, if you practically mandate I use something, the liability falls on you or that thing. If it’s a quick verify I’ll integrate it into knowledge. A lot of things aren’t.
"Hey, whatcha doin?"
"Oh hi, yea, this car has a slight misfire on cyl 4, so I was just pulling one of the coilpacks to-"
"Yea alright, that's great. So hey! You _really_ need to use this tool. Trust me, it's gonna make your life so much easier"
"umm... that's a 3d printer. I don't really think-"
"Trust me! It's gonna 10x your work!"
...
I love the tech. It's the evangelists that don't seem to bother researching the tech beyond making an account and asking it to write a couple scripts that bug me. And then they proclaim it can replace a bunch of other stuff they don't/haven't ever bothered to research or understand.
This is kind of the same with any AI gen art. Like I can go generate a bunch of cool images with AI too, why should I give a shit about your random Midjourney output.
Here's an example https://files.meiobit.com/wp-content/uploads/2024/11/22l0nqm...
Being dismissive of AI art is like those people who dismiss electronic music because there's a drum machine.
Doing things well still requires an immense amount of skill and exhaustive amount of effort. It's wildly complicated
Photographers are not painters.
People who do modular synths aren't guitarists.
Technical DJing is quite different from tapping on a Spotify app on a smartphone.
Just because you've exclusively exposed yourself to crude implementations doesn't mean sophisticated ones don't exist.
It took a solid hundred years to legitimate photography as an artistic medium, right? To the extent that the controversy still isn’t entirely dead?
Any cool images I ask AI for are going to involve a lot less patience and refinement than some of these things the kids are using AI to turn out…
For that matter, I’ve watched friends try to ask for factual information from LLMs and found myself screaming inwardly at how vague and counterproductive their style of questioning was. They can’t figure out why I get results I find useful while they get back a wall of hedging and waffling.
They have to prove to someone that they're worth their money. /s
- I had to Google it...
- According to a StackOverflow answer...
- Person X told me about this nice trick...
- etc.
Stating your sources should surely not be a bad thing, no?
And all the other examples will have a chain of "upstream" references, data and discussion.
I suppose you can use those same phrases to reference things without that, random "summaries" without references or research, "expert opinion" from someone without any experience in that sector, opinion pieces etc. but I'd say they're equally worthless as references as "According to GPT...", and should be treated similarly.
Just do the research, and you don't have to qualify it. "GPT said that Don Knuth said..." Just verify that Don said it, and report the real fact! And if something turns out to be too difficult to fact check, that's still valuable information.
I don't think I've ever seen anyone lambasted for citing stackoverflow as a source. At best, they chastised for not reading the comments, but nowhere as much pushback as for LLMs.
Also, using Stack Overflow correctly requires more critical thinking. You have to determine whether any given question-and-answer is actually relevant to your problem, rather than just pasting in your code and seeing what the LLM says. Requiring more work is not inherently a good thing, but it does mean that if you’re citing Stack Overflow, you probably have a somewhat better understanding of whatever you’re citing it for than if you cited an LLM.
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If anything, SO having verified answers helps its credibility slightly compared to a LLM which are all known to regularly hallucinate (see: literally this post).
"Hey, I didn't study this, I found it on Google. Take it with a grain of caution, as it came from the internet" has been shortened to "I googled it and...", which is now evolving to "Hey, I asked chatGPT, and...."
Copy and pasting from ChatGPT has the same consequences as copying and pasting from StackOverflow, which is to say you're now on the hook supporting code in production that you don't understand.
I can use ChatGPT to teach me and understand a topic or i can use it to give me an answer and not double check and just copy paste.
Just shows off how much you care about the topic at hand, no?
Starting the answer with "I asked ChatGPT and it said..." almost 100% means the poster did not double-check.
(This is the same with other systems: If you say, "According to Google...", then you are admitting you don't know much about this topic. This can occasionally be useful, but most of the time it's just annoying...)
It sucks at sports trivia. It will confidently return information that is straight up wrong [1]. This should be a walk in the park for an LLM, but it fails spectacularly at it. How is this useful for learning at all?
[1] https://news.ycombinator.com/item?id=43669364
[0] https://en.m.wikipedia.org/wiki/Gell-Mann_amnesia_effect
If you don't know anything about the subject area, how do you know if you are asking the right questions?
I will ask for all claims to be backed with cited evidence. And then, I check those.
In other cases, of things like code generation, I ask for a test harness be written in and test.
In some foreign language translation (High German to english), I ask for a sentence to sentence comparison in the syntax of a diff.
All marketing departments are trying to manipulate you to buy their thing, it should be illegal.
But just testing out this new stuff and seeing what's useful for you (or not) is usually the way
If you're just parroting what you read, what is it that you do here?!
It is just bad design. You want errors to be as loud as possible. So they can be traced and resolved. On the other hand, LLMs optimize human preference (or some proxy of this). While humans prefer accuracy, it would be naive to ignore all the other things that optimize this objective. Specifically, humans prefer answers that they don't know are wrong over those that they do know are wrong.
This doesn't make LLMs useless but certainly it should strongly inform how we use them. Frankly, you cannot trust outputs, so you have to verify. I think this is where there's a big divergence between LLM users (and non-users). Those that blindly trust and those that don't (extreme case is non-users). If you need to constantly verify AND recognize that verification is extra hard (because it is optimized to be invisible to you), it can create extra work, not less.
It really is two camps and I think it says a lot:
Wide range of opinions in these two camps, but I think it comes down to some threshold of default trust or default suspicion.Seems like if all you do is forward questions to LLMs, maybe you CAN be replaced by a LLM.
most annoying is when people trust chatgpt more that experts they pay. we had case when our client asked us for some specific optimization, and we told him that it makes no sense, then he asked the other company that we cooperate with and got similar response, then he asked chatgpt and it told him it's great idea. And guess what, he bought $20k subscription to implement it.
If that's all the available information and you're out of time, you may as well cut the blue wire. But, pretty much any other source is automatically more trustworthy.
English please
"I asked X and it said..." is an appeal to authority and suspect on its face whether or not X is an LLM. But when it's an LLM, then it's even worse. Presumably, the reason for the appeal is because the person using it considers the LLM to be an authoritative or meaningful source. That makes me question the competence of the person saying it.
If they're saying it to you, why wouldn't you assume they understand and trust what they came up with?
Do you need people to start with "I understand and believe and trust what I'm about to show you ..."?
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https://blog.bismuth.sh/blog/bismuth-found-the-atop-bug
https://www.cve.org/CVERecord?id=CVE-2025-31160
The amount of bad reports curl in particular has gotten is staggering and it's all from people who have no background just latching onto a tool that won't elevate them.
Edit: Also shoutout to one of our old professors Brendan Dolan-Gavitt who now works on offensive security agents who has a highly ranked vulnerability agent XBOW.
https://hackerone.com/xbow?type=user
So these tools are there and doing real work its just there are so many people looking for a quick buck that you really have to tease the noise from the bs.
https://arc.dev/talent-blog/impact-of-ai-on-code/
In that sense, it has destroyed actual value as the noise crowds out the signal. AI could easily do the same to, like, all Internet communication.
And most contributions with 'AI help' tend to not follow the code practices of the code base itself, while also in general generating worse code.
Also, just like in HTTP stuff 'if curl does it its probably right', I'm also tend to think that 'if the curl team says something its bullshit its probably bullshit'.
Anything for linkedin, a light interface that doesn't required logging in?
I pretty much stopped going to linkedin years ago because they started aggressively directing a person to login. I was shocked this post works without login. I don't know if that is how it has always been, or if that is a recent change, or what. It would be nice to have alternative interfaces.
In case some people are getting gated here is their post:
===
Daniel Stenberg curl CEO. Code Emitting Organism
That's it. I've had it. I'm putting my foot down on this craziness.
1. Every reporter submitting security reports on #Hackerone for #curl now needs to answer this question:
"Did you use an AI to find the problem or generate this submission?"
(and if they do select it, they can expect a stream of proof of actual intelligence follow-up questions)
2. We now ban every reporter INSTANTLY who submits reports we deem AI slop. A threshold has been reached. We are effectively being DDoSed. If we could, we would charge them for this waste of our time.
We still have not seen a single valid security report done with AI help.
---
This is the latest one that really pushed me over the limit: https://hackerone.com/reports/3125832
===
I just opened the site with JS off on mobile. No issues.