Framing Unexpected Trust Issues in Reporting in AI and Cybersecurity: The Rise of False Bug Reports
In Machines we Trust
In Machines we Trust
4.3 • 6 Ratings
🗓️ 16 September 2025
⏱️ 10 minutes
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Summary
In this episode, we’re framing the unexpected side of trust issues in reporting under the theme of AI and Cybersecurity: The Rise of False Bug Reports. This phenomenon is making it harder to distinguish real issues from noise, revealing new layers of complexity in cybersecurity defense. We look at what's driving the rise of false bug reports—and how to stay ahead of the curve.
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Transcript
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| 0:00.0 | Today on the podcast, I want to talk about an issue with AI and cybersecurity. Now, a lot of times people talk about, oh my gosh, AI is going to completely be used by hackers and malicious people to destroy companies. And I mean, I'm sure there's like different ways that you can use AI to do good and bad things, of course. And there's, you know, red teaming groups inside of all these top LLMs to mitigate that. I'm not actually talking about that. Today I want to talk about |
| 0:24.3 | false positive bug reporting, AI slop that are used to create fake reports saying that there |
| 0:30.9 | is security vulnerabilities with companies and how hard it is. Some companies are getting completely |
| 0:35.4 | overwhelmed and shutting down their bug bounty |
| 0:38.4 | programs because they're getting inundated with so much AI slop. So actually, this is |
| 0:43.3 | another area because now these programs are gone that these vulnerabilities are not getting |
| 0:46.8 | reported or seen. And this actually could create its very own security problem. So I want to |
| 0:53.1 | get into all of that today on the podcast. But before I do, I wanted to mention, if you want to try any of the top models that I talk about on the show, I would love for you to check out my platform, which is called AIbox.a. It's a platform where you have the top 40 different AI models all in one platform for one price. You get access to Gemini, Claude, |
| 1:11.7 | Grock, a whole bunch of image and text models that you may not have tried before. And it's only |
| 1:16.2 | $20 months. So you can try all of them. If you're interested, you can go check it out. There's a |
| 1:20.6 | link in the description to AI Box AI. All right, let's get into what's going on with these |
| 1:25.7 | AI swap fake reports that are basically |
| 1:29.6 | exhausting some security bug programs. |
| 1:32.3 | Pretty much what's happening is there's been a problem in the past, of course, with hackers |
| 1:36.4 | finding a vulnerability, exploiting it, and, you know, causing great financial harm to a company. |
| 1:42.0 | And so in response to this, a lot of companies have created these bug bounty programs are basically if you go and see like a bug or you see a security vulnerability, you can report it. And if it was a big one, you'll get paid for it. And I think meta's been kind of famous for this in the past, but a lot of companies do this. Basically, like, don't hack us. If you found a breach, we'll just pay you and you can, |
| 2:02.7 | you know, go away quietly, basically without having to breach our, breach our customers, whatever. |
| 2:08.3 | So what's interesting, though, is here's a quote from Vlad Eonsk, who kind of talks about this |
| 2:13.0 | problem. He said, people are receiving reports that sound reasonable. They look technically correct. And then you end up digging into them trying to figure out where is the vulnerability. And then, of course, it turns out there is no vulnerability. It turns out it was just a hallucination all along. The technical details were just made up by an LLM. And of course, these LLMs are so good at making up these issues. And it goes beyond just like, I think if your average person tried, this is their side hustle. They tried to submit these for like bounties. I don't know if it would be a very great side hustle. But because of course they, you know, they just don't know that much. But I think if you are already perhaps a hacker, this would probably seem like a really, you would basically know potential vulnerabilities. |
| 2:51.6 | And so you could prompt chat ChupD to be like, hey, I found a vulnerability in this platform |
| 2:57.6 | for XYZ reasons. Please write a detailed report of the vulnerability, how it works, and here's some |
| 3:02.6 | code and how it could have implemented, you know, been integrated into their code base. |
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