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Vibe Coding Vulnerabilities

Concerns about AI-generated code introducing massive security holes. Research found thousands of vibe-coded apps with exposed data, though debate exists whether these represent true vulnerabilities versus poor app design.

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The debate over "vibe coding" centers on whether AI is actively introducing new security risks or if its "slop" simply makes vulnerabilities easier to discover by creating a larger target. While researchers have identified thousands of AI-generated applications exposing sensitive medical and financial data due to a total lack of authentication, some argue these cases reflect poor individual design choices rather than systemic flaws in the AI tools themselves. This influx of AI-assisted code is reportedly overwhelming manual review processes, yet critics note that many high-impact vulnerabilities still stem from legacy logic errors that predate the AI era. Ultimately, the consensus suggests that while mature projects remain relatively stable, the sheer volume of low-effort, vibe-coded apps is creating a massive and poorly-secured new surface area for potential exploitation.

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That's correlation, not causation. It could equally be argued that the AI slop that's being produced makes for a lot more vulnerabilities being shipped. The bigger target makes for the easier discovery.
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But don't we know that some of the vulnerabilities being discovered predate ai coding?
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Certainly, and some discoveries have been attributed to AI (I was reading that mozilla firefox were praising mythos recently) But that's not accounting for all of the discoveries, not at all. I've also seen the npm people talking about the surge in AI code overwhelming the ability to properly review what's being distributed, and a large number of vulnerabilities being attributed to that
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It's likely varies enormously between projects. Linux remains extremely low in slop, and the vulnerabilities being fixed are quite old, so it's improving. Many vibe coded projects are very sloppy, and are adding a lot of vulnerabilities. Total number of vulnerabilities likely goes up over time weighting all projects equally, but goes down over time weighting by usage.
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Is there evidence serious vulnerabilities are the result of vibe coding already? I haven’t seen any so if you have some references, please share.
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Security researcher Dor Zvi and his team at the cybersecurity firm he cofounded, RedAccess, analyzed thousands of vibe-coded web applications created using the AI software development tools Lovable, Replit, Base44, and Netlify and found more than 5,000 of them that had virtually no security or authentication of any kind. Many of these web apps allowed anyone who merely finds their web URL to access the apps and their data. Others had only trivial barriers to that access, such as requiring that a visitor sign in with any email address. Around 40 percent of the apps exposed sensitive data, Zvi says, including medical information, financial data, corporate presentations, and strategy documents, as well as detailed logs of customer conversations with chatbots. https://www.wired.com/story/thousands-of-vibe-coded-apps-exp...
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That’s quite different. Vibe coded apps are not normally even meant to be secure, it’s meant to be used by the creator only. Bad app security is not the same as a vulnerability. A vulnerability would be a library providing some functionality it claims is secure, but in reality it’s not.
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> That's correlation, not causation. Pragmatically, correlation *is* evidence of causation in favour of the best explanation, until somebody finds a better explanation. > It could equally be argued that the AI slop that's being produced makes for a lot more vulnerabilities being shipped. This is also true, and does not exclude the other, because for the moment the vast majority of production software in the world (and therefore the bulk of enticing targets) was written before AI. If LLM software will become prevalent in commercial setups, then LLM-generated code will eventually become the majority of targets.
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Trying to reframe this as 'not science' after being caught on a logical fallacy doesn't change the record. You started with a definitive claim ('We know') to shut down a question. When challenged on the lack of causation, you pivoted to 'educated guesses.' My point remains: if we misattribute the cause of the rising vulnerability rate (discovery vs. creation), our 'educated guesses' will lead to solutions that address the symptoms while the underlying problem continues to fester. Calling precision 'blabbering' is exactly how we end up with the 'false sense of security' mentioned earlier. Exhibit A: ragall 2 hours ago | root | parent | prev | next [–] > How do you know? We know because we could see the effects of the average rate of vulnerabilities discovery and exploitation, and it's definitely going up very fast. Until recently, vulnerabilities were relatively hard to find, and finding them was done by a very restricted group of people world-wide, which made them quite valuable. Not any more. Exhibit B: ragall 2 hours ago | root | parent | next [–] Very often you only have limited time for investigation and you have to act now. Action is almost always based on educated guesses. reply
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I am looking at the results of a mass vulnerability scan as I type this. Half of the bugs in one case are in fact (binary) parser errors for hand-written parsers. These really should not exist in any language - but in C it's particularly bad. Kaitai Struct or something similar would broadly have prevented these. Rust would help here, but less than a parser generator (because it could automate error checking insertion for things that aren't just out of bound access). However, half of the vulnerabilities are logic errors in terms of what I would call RBAC enforcement, incorrect access permissions, and so on. Rust won't help at all with any of these.