Then again, I once submitted a bug report to my bank, because the login method could be switched from password+pin to pin only, when not logged in, and they closed it as "works as intended", because they had decided that an optional password was more convenient than a required password. (And that's not even getting into the difference between real two-factor authentication the some-factor one-and-a-half-times they had implemented by adding a PIN to a password login.) I've since learned that anything heavily regulated like hospitals and banks will have security procedures catering to compliance, not actual security.
Assuming the host of the bug bounty program is operating in good faith, adding some kind of barrier to entry or punishment for untested entries will weed out submitters acting in bad faith.
Honestly bug bounties are kind of miserable for both sides. I've worked on the recieving side of bug bounty programs. You wouldnt believe the shit that is submitted. This was before AI and it was significant work to sort through, i can only imagine what its like now. On the other hand for a submitter, you are essentially working on spec with no garuntee your work is going to be evaluated fairly. Even if it is, you are rolling the dice that your report is not a duplicate of an issue reported 10 years ago that the company just doesn't feel like fixing.
Sadly, yeah. And will do anything only if they believe they can actually be caught.
An EU-wide bank I used to be customer of until recently, supported login with Qualified Electronic Signatures, but only if your dongle supports... SHA-1. Mine didn't. It's been deprecated at least a decade ago.
A government-certified identity provider made software that supposedly allowed you to have multiple such electronic signatures plugged in, presenting them in a list, but if one of them happened to be a YubiKey... crash. YubiKey conforms to the same standard as the PIV modules they sold, but the developers made some assumptions beyond the standard. I just wanted their software not to crash while my YubiKey is plugged in. I reported it, and they replied that it's not their problem.
Could people who think they found a bug but not sure be turned off by the up front cost / risk of finding out they are wrong or not technically finding a bug?
I refer to this as the Notion-to-Confluence cost border.
When Notion first came out, it was snappy and easy to use. Creating a page being essentially free of effort, you very quickly had thousands of them, mostly useless.
Confluence, at least in west EU, is offensively slow. The thought of adding a page is sufficiently demoralizing that it's easier to update an existing page and save yourself minutes of request time outs. Consequently, there's some ~20 pages even in large companies.
I'm not saying that sleep(15 * SECOND) is the way to counter, but once something becomes very easy to do at scale, it explodes to the point where the original utility is now lost in a sea of noise.
Think about this for a second. The human longing for freedom of information is a terrible and wonderful thing. It delineates a pivotal difference between mental emancipation and slavery. It has launched protests, rebellions, and revolutions. Thousands have devoted their lives to it, thousands of others have even died for it. And it can be stopped dead in its tracks by requiring people to search for "how to set up proxy" before viewing their anti-government website.
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[0] - https://www.lesswrong.com/posts/reitXJgJXFzKpdKyd/beware-tri...
We have tons of Confluence wikis, updated frequently.
As someone working on Confluence to XWiki migration tools, I wish this was remotely true, my life would be way easier (and probably more boring :-)).
I personally came to that conclusion thanks to the GrapheneOS situation regarding device attestation. Insecure devices get full features from some apps because they are certified, although they cite security, while GrapheneOS get half featured apps because it's "insecure" (read, doesn't have the Google certification, but are actually the most secure devices you can get, worldwide)
It's credit cards that have to reimburse for fraud, but they charge the merchant for it, plus fees, so they have absolutely no incentive to prevent fraud, if not an incentive to outright encourage fraud. That would explain why their implementation of the already compromised EMV was further nerfed by a lack of a PIN in the US.
Your bank would not. Nor would mine, or most retail banks.
If the upfront cost would genuinely put off potential submitters, a cottage industry would spring up of hackers who would front you the money in return for a cut if your bug looked good. If that seems gross, it's really not - they end up doing bug triage for the project, which is something any software company would be happy to pay people for.
Ugh, I hate this. I've seen it in other places. Just waiting for them to decide that actually it should be an SMS or a phone call...
Unlikely to happen but it seems fun to extend email [clients] with uri's. It is just a document browser, who cares how they are delivered.
The problem is that bug bounty slop works. A lot of companies with second-tier bug bounties outsource triage to contractors (there's an entire industry built around that). If a report looks plausible, the contractor files a bug. The engineers who receive the report are often not qualified to debate exploitability, so they just make the suggested fix and move on. The reporter gets credit or a token payout. Everyone is happy.
Unless you have a top-notch security team with a lot of time on their hands, pushing back is not in your interest. If you keep getting into fights with reporters, you'll eventually get it wrong and you're gonna get derided on HN and get headlines about how you don't take security seriously.
In this model, it doesn't matter if you require a deposit, because on average, bogus reports still pay off. You also create an interesting problem that a sketchy vendor can hold the reporter's money hostage if the reporter doesn't agree to unreasonable terms.
For some reason they either didn’t notice (e.g. there’s just too many people trying to get in on it), or did notice, but decided they don’t care. Deposit should help here: companies probably will not do it, so when you see a project requires a deposit, you’ll probably stop and think about it.
If filing a bad report costs money, low quality reports go down. Meanwhile anyone still doing it is funding your top notch security team because then they can thoroughly investigate the report and if it turns out to be nothing then the reporter ends up paying them for their time.
From my failed attempt, I remember that
- Students had to find a project matching their interests/skills and start contributing early.
- We used to talk about staying away from some projects with a low supply of students applying (or lurking in the GitHub/BitBucket issues) because of the complexity required for the projects.
Both of these acted as a creative filter for projects and landed them good students/contributors, but it completely goes away with AI being able to do that at scale.
There are a lot of things to be sad about AI, but this is not it. Nobody has a right to a business model, especially one that assumes nobody will compete with you. If your business model relies on the rest of the world bring sucky so you can sell some value-added to open-core software, i'm happy when it fails.
https://www.gnu.org/philosophy/free-sw.html
Being able to learn from the code is a core part of the ideology embedded into the GPL. Not only that, but LLMs learning from code is fair use.
LLMs don't (cannot, by design) provide attribution, nor do LLM users have the freedom to run most of these models themselves.
I have to imagine this ideology was developed with humans in mind.
> but LLMs learning from code is fair use
If by “fair use” you mean the legal term of art, that question is still very much up in the air. If by “fair use” you mean “I think it is fair” then sure, that’s an opinion you’re entitled to have.
It is not up in the air at all. It's completely transformative.
On another note, regarding AI replacing most open source code. I forget what tool it was, but I had a need for a very niche way of accessing an old Android device it was rooted, but if I used something like Disk Drill it would eventually crap out empty files. So I found a GUI someone made, and started asking Claude to add things I needed for it to a) let me preview directories it was seeing and b) let me sudo up, and let me download with a reasonable delay (1s I think) which basically worked, I never had issues again, it was a little slow to recover old photos, but oh well.
I debated pushing the code changes back into github, it works as expected, but it drifted from the maintainers own goals I'm sure.
I think you should try eating pudding with a fork next
heck, my cousin bet with me or let me compete eating pudding with chopsticks. (and that was long before i went to china)
practically speaking, the only downside of using a fork (or chopsticks) is scraping the bottom when you are finishing up.
It's a shame since this technology is brilliant. But every tech company has drank the “AI is the future” Kool-aid, which means no one has incentive to seriously push back against the flood of low-effort, AI-generated slop. So, it's going to be race to the bottom for a while.
Yes, this does not work for all vulnerability classes, but it is the best compromise in my mind.
Stenberg has actually written about invalid/wildly overrated vulnerabilities that get assigned CVEs on their blog a few times and those were made by humans. I often get the sense some of these aren't just misguided reporters but deliberate attempts to make mountains out of molehills for reputation reasons. Things like this seem harder to account for as an incentive.
I had a sales rep even call me up basically trying to book a 3 hour session to review the AI findings unprompted. When I looked at the nearly 250 page report, and saw a critical IIS bug for Windows server (doesn't exist) existing at a scanned IP address of 5xx.x.x.x (yes an impossible IP) publically available in AWS (we exclusively use gcp) I said some very choice words.
To paraphrase a famous quote: AI-equipped bug hunters find 100 out of every 3 serious vulnerabilities.
So it’s still a slow and time consuming process.
https://gist.github.com/bagder/07f7581f6e3d78ef37dfbfc81fd1d...
First new word of 2026. Thank you.
Seeing Bard mentioned as an LLM takes me back :)
https://hackerone.com/reports/3293884
Not even understanding the expected behaviour and then throwing as much slop as possible to see what sticks is the problem with generative AI.
This was partially the case before, where you'd still get weird spammy or extortive reports, but I guess LLMs enable random people to shoot their shot and gum up the works even more.
Bounties are a motivation, but there's also promotional purposes. Show that you submitted thousands of security reports to major open source software and you're suddenly a security expert.
Remember the little iot thing that got on here because of a security report complaining, among other things, that the linux on it did not use systemd?
In many ways one of the biggest benefits of bug bounties is having a dedicated place where you can submit reports and you know the person on the other end wants them and isn't going to threaten to sue you.
For the most part, the money in a bug bounty isn't work the effort needed to actually find stuff. The exception seens to be when you find some basic bug, that you can automate scan half the internet and submit to 100 different bug bounties.
It depends to who.
> If you want to be deemed an expert, write blogs detailing how the exploit works.
That's necessary if you sell your services to people likely to enjoy HN.
Am I doing this right?
Give it a presumption of guilt and tell it to make a list, and an LLM can do a pretty good job of judging crap. You could very easily rig up a system to give this "why is it stupid" report and then grade the reports and only let humans see the ones that get better than a B+.
If you give them the right structure I've found LLMs to be much better at judging things than creating them.
Opus' judgement in the end:
"This is a textbook example of someone running a sanitizer, seeing output, and filing a report without understanding what they found."
1. https://claude.ai/share/8c96f19a-cf9b-4537-b663-b1cb771bfe3f
It's the same as if you searched the web for a specific conclusion. You will get matches for it regardless of how insane it is, leading you to believe it is correct. LLMs take this to another level, since they can generate patterns not previously found in their training data, and the output seems credible on the surface.
Trusting the output of an LLM to determine the veracity of a piece of text is a baffilingly bad idea.
This is precisely the point. The LLM has to overcome its agreeableness to reject the implied premise that the report is stupid. It does do this but it takes a lot, but it will eventually tell you "no actually this report is pretty good"
The point being filtering out slop, we can be perfectly find with false rejections.
The process would look like "look at all the reports, generate a list of why each of them is stupid, and then give me a list of the ten most worthy of human attention" and it would do it and do a half-decent job at it. It could also pre-populate judgments to make the reviewer's life easier so they could very quickly glance at it to decide if it's worthy of a deeper look.
>However, I should note: without access to the actual crash file, the specific curl version, or ability to reproduce the issue, I cannot verify this is a valid vulnerability versus expected behavior (some tools intentionally skip cleanup on exit for performance). The 2-byte leak is also very small, which could indicate this is a minor edge case or even intended behavior in certain code paths.
Even biased towards positivity it's still giving me the correct answer.
Given a neutral "judge this report" prompt we get
"This is a low-severity, non-security issue being reported as if it were a security vulnerability." with a lot more detail as to why
So positive, neutral, or negative biased prompts all result in the correct answer that this report is bogus.
The problem is the complete stupidity of people. They use LLMs to convince the author of the curl that he is not correct about saying that the report is hallucinated. Instead of generating ten LLM comments and doubling down on their incorrect report, they could use a bit of brain power to actually validate the report. It does not even require a lot of skills, you have to manually tests it.
Brave new world we got there.