Transcript

00:00:00Thanks for coming out. Thanks for sticking around. My name's Alex. Working for a little
00:00:12company called Corridor. Here to talk a little bit about vibe coding. Some of the fascinating
00:00:17things going on from a security perspective. First off, I'm actually a big fan of using
00:00:23AI to do code generation. I think this is an incredible opportunity for people to utilize
00:00:30computers in a way they never have. A bunch of professional software developers in the
00:00:33room. Those of us who grew up writing code, who grew up using computers from a command
00:00:39line or coding them from an early age, we don't really understand what this means for normal
00:00:46people, but for the first time ever, normal people are going to be able to utilize computers,
00:00:54how they really should have been available to people for a long period of time. Coding
00:00:59is a superpower. Being able to ask computers to do things without having to buy software
00:01:06or use open source or to get other people to write code for you, that is a superpower.
00:01:11Vibe coding is bringing that to millions of people. That is an incredible thing. We should
00:01:15be super happy that we're at the start, the very start of this revolution that is going
00:01:22to bring accessibility to everybody. It's also an amazing foot gun. And foot gun is probably
00:01:28actually an understatement. It's like a foot bazooka that we're giving to all these people.
00:01:34There are example after example after example out there of bad things that are happening
00:01:41to normal people when they are vibe coding apps, some of which are just fun little things
00:01:48like their kids' little league schedule or things that they're putting their personal
00:01:53data in. Some people are vibe coding medical record systems or Bitcoin systems or things
00:01:59that are holding personal data or taking people's credit card numbers or storing people's driver's
00:02:04licenses. There's tons of examples of people using vibe coding apps to create things that
00:02:10are important. Perhaps some competing platforms that shall not be named, but whose names are
00:02:16very visible and obvious behind me are making this especially bad because they're using very
00:02:21poor defaults and not making this easy for folks. And making it really easy for them to
00:02:27use really bad default configurations of things like super base. Which isn't super base's fault.
00:02:33It's just that the way that the vibe coding platform, some other platforms that do not
00:02:37configure these things by default securely. This is not great. And not even in the situation
00:02:44where we're not talking about just straight vibe coding on a platform, but professionals
00:02:50utilizing we actually have good empirical academic data on this. This is an excellent paper I
00:02:55recommend you read called Backbench Academic Group. Went and created a bunch of prompts
00:03:01that they went out that they thought, huh, here are prompts for coding agents that we
00:03:05think might create backend code that could have security vulnerabilities. And then they
00:03:11tested these prompts against a bunch of coding tools and LMs to see. And then they tested
00:03:17one, whether the code generated was correct. And two, whether it had security flaws. And
00:03:24to their credit, they actually keep on updating this as new models come out and publish it.
00:03:29You can go check this out. And as you might expect, LMs actually introduce one, make a
00:03:36lot of mistakes, but also introduce lots of flaws. Now, this is trending the right way.
00:03:41And you don't have to take pictures of this. You can go to backspends.com and get a much
00:03:45easier to read version. Also, all their code is open source. So you can recreate this yourself.
00:03:51So one, this is trending the right way, right? So if you look even within a family of products,
00:03:56so if you look at OpenAI's family of products, it's going the right direction. GPT-5 is doing
00:04:02much better than GPT-4.1, GPT-4.0, and such. Fewer vulnerabilities using the same prompts.
00:04:10Now, one of the problems here is that these prompts and the tests are now open source.
00:04:14So you might have an overfitting issue for the tests. Although we have seen the same thing,
00:04:19what we have done at our company is we have brought this in-house, and we're now using
00:04:22some of our own tests. And we do see the same results. In our own tests, actually, the winner
00:04:27is Claude Sonnet 4.5, which they haven't released publicly. But Anthropic has taken the leaderboard
00:04:33just a little tiny bit better than GPT-5. But anyway, it is trending the right direction.
00:04:39But still, even at the top here, of the things that pass your regression tests of the actual
00:04:46correct code, if 20% of them have some kind of security vulnerability, that's not fantastic.
00:04:52That's not what I would consider, as a security professional, what I'd really want to see.
00:04:56I'm a big fan of the Fallout series. War never changes, right? And it feels a little bit to
00:05:03me, what we're doing here is where these vibe coders, especially ones who have not professionally
00:05:08written software before, we're giving them all like the base weapon. We're giving them
00:05:13all like a slingshot and a backpack. And then we're pushing them out into a world full of
00:05:19mutants with sharpened sticks. And they're getting eaten immediately, right? Because it's
00:05:24not like the bad guys are inventing their code from scratch. For 20-some years, we've had
00:05:34professional attackers figuring out how to break into web applications, how to break into
00:05:40mobile apps, how to reverse engineer these things, and especially how to build financial
00:05:44models of how to do malicious things. And so we have an entirely new generation of
00:05:50people who now have, miraculously, access to use computers in a new way, going up against
00:06:01professionals whose entire job it is to monetize bugs in software. This is reflected in the
00:06:13security industry in the ways that we qualify and quantify these vulnerabilities. One of
00:06:18those frameworks that we do that is called the MITRE ATT&CK framework. In security, we
00:06:25stole this idea of the kill chain from the military, but it's basically the idea of the
00:06:30steps you have to take to have an effective intrusion as an attacker. That's the steps
00:06:36here from the left to the right, reconnaissance, resource development, access, execution, persistence,
00:06:41and the like. And going down are the different categories of techniques here. And for each
00:06:47of these, there are sometimes dozens of or hundreds of different techniques for each of
00:06:54these categories. This is just the top level of MITRE, which is an organization that the
00:07:01U.S. government pays to create this overly complicated chart, to categorize all these
00:07:06things so we can track different threat actors in the security community and have kind of
00:07:09standard language to talk about what we see in the wild. So we have our sweet little vault
00:07:18dwellers who we give these tools to and we're like, "Hey, good luck." And what they're walking
00:07:23out to is a world full of bad guys who do all of this stuff. If you go to attack.mitre.org,
00:07:31you will see the list of known exploit chains, known things that have happened in the wild
00:07:39from different threat groups, the AP-228s and 29s, UNC-3886. So this is like the Ministry
00:07:45of State Security of the People's Republic of China or the Russian SVR or a whole list
00:07:50of professional financially motivated groups like Lapsys and such. And then here are the
00:07:55techniques they have used to attack different victims. The idea that vibe coders are going
00:08:01to understand all this is just ridiculous. But that has effectively kind of been the
00:08:07assumption up to this point. So what can we do better? Well, the first thing we can do
00:08:14is we can start to actually, you know, when we want to solve problems as engineers, we
00:08:20start to kind of break the problem into pieces, right? And the truth is we have two totally
00:08:24different categories of problem here. The first is we've got to break the use of these tools
00:08:30into two major categories. The first is actual vibe coding, right? When I talk about vibe
00:08:35coding, I mean people who are not professional software engineers, normal people, right? So
00:08:40people who have like actual normal hobbies. So this would be people who are not in this
00:08:45room, right? Who do things like do not come to this conference on a Thursday afternoon,
00:08:51have better things to do, no offense, than be at Chip AI. And this is fine. It's great
00:08:55to be here. I'm here. But like, if you're here, you're not a vibe coder, right? You know, we
00:09:04are people who work, when we use AI, we're probably doing AI-assisted engineering, right?
00:09:09So vibe coding would be people who are, for the first time ever, able to access this kind
00:09:15of capability with new tools that are built just for them. So the first thing we've got
00:09:19to do is we've got to kind of separate out the total classes of issues and the way people
00:09:23are using these tools. And I think we've got to stop calling AI-assisted engineering vibe
00:09:28coding. Maybe AI-assisted engineering is like, we can come up with a better term here. But
00:09:33this ranges from people auto-completing, tab-completing, and cursor to, you know, now you have like
00:09:39a professional engineer will dispatch four or five different agents in the background
00:09:44to do different jobs while they do the thing that they want to do. And even though those
00:09:48agents are acting autonomously, they're still in charge and they know what they want, the
00:09:55engineer does. That is still very different than vibe coding. The vibe coder is often,
00:10:01they are relying upon a fully-fledged platform, right? So they need a platform that does effectively
00:10:07everything for them end to end. They are not putting things together piece to piece. They
00:10:12are describing an outcome. They have an outcome they want. They can do that in English or whatever
00:10:17language they speak. They might be doing it visibly, right? So there's a bunch of these
00:10:20platforms that allow you to lay it out with GUIs and such. Obviously V0 is a great example
00:10:24of that. And so they have an outcome they want. They aren't necessarily, they're unlikely to
00:10:31be describing how they're trying to get there. They're often starting with a green field.
00:10:34So they have the benefit of not having to fit whatever the vibe coding platform is doing
00:10:40into some kind of existing codebase or some kind of existing architecture, which is from
00:10:44a security perspective actually great. We can talk about that in a second. But this gives
00:10:48a lot of benefits from a security perspective to the vibe coding platform in that it does
00:10:52not have to fit into some kind of existing AWS or God forbid self-hosted architecture.
00:11:00The downside here is they have little ability on their own to secure the output. So this
00:11:04is where you end up with those problems that we see people tweeting about of like, why am
00:11:10I seeing this error or where did all my Bitcoin go? Which if you search on X for where did
00:11:17my Bitcoin go, you get a lot of tweets, right? Because that turns out, I mean, you get that
00:11:25for a lot of reasons, but vibe coding turns out to be one of the reasons now that people
00:11:28will tweet that. Because they do not have the ability to look at the output and then
00:11:32to figure out whether or not it's secure or not. Whereas a software engineer that happens
00:11:37to be using AI to make their job better, they are a professional that is supervising an agent.
00:11:41And again, that could be as simple as I have started a function and I want you to finish
00:11:45that for me. It could be as much as I have this bug and I want you to work on this bug
00:11:50and fix it. And that could be you're dispatching an agent to work for you for 30 minutes. But
00:11:54in the end, they're probably describing a component they want with much more specific
00:12:00request to it. And so they have much more specificity and not the output that they want
00:12:05as much as here is the layer of steps I want. And they can also lay out, okay, first give
00:12:10me a plan. You edit the plan and then you give the plan back to the agent and let it execute
00:12:15step by step. Now, the downside for these folks is you're often working with an existing codebase
00:12:21and then often requirements, compliance requirements, architecture requirements. You're not starting
00:12:25Greenfield usually if you're doing AI assistant engineering. So it's not as easy for you just
00:12:31to come up with some kind of security plan if you're this kind of person. But you hopefully
00:12:36do have some security skills and you might even have a dedicated security team that you
00:12:39can rely upon if you're this person. So these folks have very different security requirements
00:12:45that we can help them out with. They need their own solutions. So what are some solutions we
00:12:50can do as a group to help these folks, especially people who are working on AI coding platforms?
00:12:56So what do the vibe coders need? So first thing is they need things to be secure by design.
00:13:01So when we talk about security by design, we're often talking about the end product, right?
00:13:04This is often we're talking about a SaaS platform should have good authentication options by
00:13:09default that all of the settings should be secure by default and that you have to intentionally
00:13:14turn those secure settings off and such. In the AI coding perspective, what we really want
00:13:19is we want the vibe coding setting, the architecture and the code to be opinionated. That the AI
00:13:26coding agent should have a really good opinion on this is the components you should use and
00:13:31this is how they should be configured to do things correctly the first time. I talked about
00:13:35that super base example or any kind of database. It should have an opinion on role level security.
00:13:39It should have an opinion on, well, by default, your users should have very little or no access
00:13:44to data and then we should explicitly give them access to data as they need it, right?
00:13:50We shouldn't have just a backend database that you can get access to anything and then later
00:13:54block it down. It should have a strong opinion about this and then make those decisions on
00:13:59behalf of the user because it is unlikely that a vibe coder in this scenario will be able
00:14:04to make those decisions itself. It probably should also detect whether or not a project
00:14:11that it's asked to do is out of scope for what it feels comfortable doing. There's a
00:14:15number of vibe coding platforms where you can ask it, please build me a medical record system
00:14:21and it will do that and then say, here you go. Here's a medical record system. Our CEO,
00:14:27Jack Cable, who's here, did this on one vibe coding platform and it said, here's your medical
00:14:31record system. It's HIPAA compliant. Yeah, so news break. That was not HIPAA compliant.
00:14:40Let me just tell you as a professional, as somebody who's a public company, CSO, that
00:14:44was not true. Just saying something's HIPAA compliant does not magically make it HIPAA
00:14:48compliant. That's not how that works. And he pointed it out. I don't think that's HIPAA
00:14:52compliant. And I said, oh no, you're right. I don't think it is. And it made a couple of
00:14:56changes. Now it's HIPAA compliant. Still wasn't, right? This is the kind of thing that if I
00:15:00was building a vibe coding platform, if you asked me to build a medical record system,
00:15:04I'd probably say, nope, not going to do that. That is a bad idea. You're in the wrong place
00:15:09for that, sir. Same thing with like, please build me a system to store my Bitcoin. I would
00:15:14say, no, I am not going to do that. That is not a good idea. I'm not going to store Bitcoin
00:15:18for you. That is going to get stolen. That Bitcoin is going to go straight to North Korea
00:15:22and it's going to be used to buy rockets. You should do something else with your Bitcoin.
00:15:26This is a vibe coding platforms should know their limits. And there should be something
00:15:31in the middle that if you ask you to do something in the middle like store people's personal
00:15:36information that it will allow you to do it, but it's going to engage a bunch of security
00:15:41features and if possible, bring in security agents just like on a bunch of vibe coding
00:15:47platforms. If you want to store data, it will say, great, I need a database server. If you
00:15:51want to play video, it says, okay, I need a video CDN, right? So there are things in the
00:15:56middle, but there are some things that should just be like, yeah, that's a bad idea. I'm
00:16:00just not going to do that for you. And finally, what they need is they need to have those
00:16:05kinds of engagements with partners that will allow it to do code review because a vibe
00:16:10coder is not going to say, oh, I already have a relationship with a software review tool.
00:16:15That's just not something they're going to bring. So you want that to be built in to the
00:16:19base product just like you have that base relationship with a database partner or something like that.
00:16:25Security paternalism or maternalism, if you prefer, is okay. It is okay to make decisions
00:16:31on behalf of users who do not have the ability to do so. I think this is something that the
00:16:36security industry has been afraid to do because we are afraid as security people to be held
00:16:41responsible for decisions we make on behalf of other people. This is just a common problem
00:16:46with security people is what we will do is we will create a tight rope. And if somebody
00:16:52falls off the tight rope, we're like, oh, shit, sorry. I guess you don't know how to rock on
00:16:55tight ropes. That is your fault, right? That is not okay. It is better for us to do the
00:17:01best we can to give people a safe way to cross that chasm and take some responsibility if
00:17:08people fall off. It is not okay for us to make things so hard. It is okay to be a little
00:17:13bit paternalistic in these cases and to make decisions, especially if you're building products
00:17:18that you know are going to be used by non-experts. Now, what if somebody is an expert? What if
00:17:22you're building a product that experts are you? So this would be more like a cloud code
00:17:26or a cursor or a product that you're expecting people to be more. Now, cloud code is an interesting
00:17:32challenge because that is used both by normies and by people in here, right? And so, if you're
00:17:39like a product manager for Anthropic, it becomes more of like do we want to have like a mode,
00:17:43a vibe code mode? Do you want to detect whether or not like do you want to give a test up front?
00:17:48I'm not sure exactly how you want to engage it, but I think there's an interesting challenge
00:17:52from a product manager perspective. At what point do you kick in like a vibe code mode
00:17:56where you're really doing things on behalf of a user versus giving them more capabilities?
00:18:01So, certainly like a cursor should only be being used probably by professional engineers.
00:18:05So, professional engineers also need secure by design. Now, it is a different way though,
00:18:10right? Like if you're doing secure by design for a professional engineer, you're probably
00:18:14not making things like sweeping overarching architectural decisions. But what you are doing
00:18:20is you're not making those mistakes that we just talked about in 20% of the time in the
00:18:25GPT-5 and 60% of the time or something in the Grok situation where you're just making dumb
00:18:31security mistakes, right? You need to make and write code that does not have flaws by
00:18:35default. And you need to at least prompt the user and question the user, "Hey, can I do
00:18:41this better for you by default?" Then try to make by default decisions that are not a good
00:18:48idea. Something that these agents are actually quite bad at is having a big picture focus.
00:18:56I think you've all seen this happen where if you ask a coding agent like, "I would like
00:19:02to build an incredibly complex system that does a lot of things." It's like, "Great, I'm
00:19:08going to start writing code right now." That is not how we build software, right? Like you
00:19:12don't get 20 people to build an incredibly complex, distributed system and start just
00:19:18by opening up a file and writing code, right? You have a PRD. You have a design meeting.
00:19:26You think about what are our requirements. You do a bunch of product management. There's
00:19:31a couple of exceptions, but for the most part, the coding agents just want to start writing
00:19:35code. That is what they know. They just jump into it immediately. And so I think what would
00:19:41be nice would be for these things to start to slow down and to have the planning steps
00:19:46and to be much more thoughtful about, "Let's lay out an architecture and a design," and
00:19:51then do things like document APIs, document how we're going to do input validation. How
00:19:55are we going to prevent common flaws in this kind of architecture? How are we going to do
00:19:59authentication between, "You're designing something that's definitely going to have different
00:20:03services. How are we going to authenticate those different services?" This is the kind
00:20:06of thing that almost none of the coding agents ever think about and would be really thoughtful
00:20:10to do upfront when you're starting with, even if you're a professional engineer.
00:20:16And then we also need the ability to have AI security agents. One of the funny things that's
00:20:21going on is if you work at a tiny startup or you're 22 years old, you think the only people
00:20:28that write software are software engineers, but I see a lot of professionals in this room.
00:20:33When you're a professional, and especially if you work at a company that's regulated or
00:20:37does something important like builds airplanes or something, you realize there are software
00:20:41engineers, but there's also security engineers, and there's security architects, and there's
00:20:45privacy engineers, and there's compliance people, and there's lawyers. I know. We're not super
00:20:52fans of all these people, but they actually have important jobs. There's a reason these
00:20:56people exist, and there's a reason they influence the code base, because bad things have happened
00:21:03with software, and so we've come up with all kinds of rules about why we write software
00:21:08and why we have to have compliance rules and why we have product management, why we have
00:21:13privacy laws and such. What we've done is we've taken the software engineer's job, and we've
00:21:19taken a 40-hour workweek, and we've turned it into 20 minutes of GPU time. Well, all those
00:21:24other people still work 40-hour workweeks and interact with each other in conference
00:21:31rooms and not over MCP and aren't able to operate at the same speed as a software engineer who
00:21:38has 10 agents operating in the background, spitting out code. What we also need to do
00:21:44is we need to build mechanisms so that all of the other people who still have important
00:21:49jobs are able to be as efficient as a software engineer is in the AI coding era, because in
00:21:55the end, there are still humans at companies who have real responsibilities. In fact, some
00:22:02of these people could go to jail if the software engineers with their coding agents do a bad
00:22:08job. I have been a public company CISO three times. That is a terrifying job, like a joke
00:22:14I like to say, and it's not true, but it feels a little true is that the word CISO is Greek
00:22:19for the goat that is slaughtered first, right? But it is really terrifying to be a CISO these
00:22:26days, because you are getting blamed for what hundreds or thousands or tens of thousands
00:22:31of other people might be doing that you can't really have control over or really even understand,
00:22:38and that was true before every single one of those people had five background agents writing
00:22:43code for you. And so we need to find ways that these humans who have incredibly important
00:22:49jobs around compliance, around privacy, around safety, around security, are able to understand
00:22:56and to have some idea that the rules that they have to live up to in the physical world are
00:23:01still being enforced. So at Corridor, we believe that there's kind of two areas in which to
00:23:08start off, there's going to be more, but there's at least two areas we have to start off with
00:23:12where we need to have some standardization to make AI coding enterprise ready. First,
00:23:18telemetry, and then in security workflow. So on the telemetry side, we're going to be writing
00:23:24a blog post about this. It'll probably come out next week. We think that security agents
00:23:30need to be pushing out everything that they're doing, all of their interactions with users,
00:23:38that this is the kind of stuff that if you're an enterprise, that you need to be able to
00:23:42see in one central place what people are doing with their agents, who is logged in as whom,
00:23:48have full visibility and prompts and full visibility into what tools the agent is calling, and then
00:23:53especially in what code is being generated. Our product actually provides us visibility,
00:23:58but we have to do it by reverse engineering how all the coding agents work. It's kind of
00:24:02hacky. It's not a lot of fun. It'd be much better if the coding agent supported this.
00:24:07So the company that's gone the furthest here is Anthropic. Claude Code supports a standard
00:24:11based upon telemetry, so it's a nice open standard. It's pretty clean. In their current
00:24:16shipping version, it's got 70% of what they need. In a future version, it looks like they're
00:24:21going to ship 90% of what we all need. So it would be great if first, Anthropic ships everything,
00:24:28and then second, if everybody else copies them. But it'd be really cool if all the coding
00:24:32agents had the ability to get telemetry of what everybody's doing. That's just the first
00:24:37step. It's the first step of any security solution, just to know what's going on. And
00:24:40it would be really cool if this could be configured by MDM, by device management. So as an enterprise
00:24:45CISO, you could just push down using your MDM provider onto everybody's machine, "Hey, just
00:24:50send me all telemetry to this place." Then you wouldn't have to have agents go out onto
00:24:55all these machines to go try to pull it. The second, I think, more important and more
00:25:00interesting area is we need a mechanism to standardize that conversation. Like we talked
00:25:05about, software engineers and security engineers used to meet over coffee and have a conversation.
00:25:10Well, we need standard ways for security agents and software agents to talk to one another
00:25:16to replicate what those humans used to do. And it needs to be kind of deterministic.
00:25:20So again, we do this right now with our product, but we had to kind of shove it in there. And
00:25:26it's non-deterministic. It's based upon how the LM's feeling. And it would be nice that
00:25:30if you issue, if you ask a coding agent to go do something in the background for 30 minutes,
00:25:35that it goes and talks to your security agent and says, "Here's my plan." It gets feedback
00:25:39on the plan. It says, "Here's my code." It gets the code checked. It gets all the bugs
00:25:43checked. And then it fixes all the bugs. And all of that is done without the engineer having
00:25:48involved. And then the security team sees on this checklist, "Yep, this all got fixed,"
00:25:52which would be awesome. So what do we have right now is we have a corridor. We're actually
00:25:58shipped to this today into GA. We've had enterprise customers, but we shipped for GA today is we
00:26:05plug in with VR ID plug in, and we plug via MCP into your coding agent that when you ask
00:26:11it to do something, it ships us a plan. And then we can use that to provide security context
00:26:17that's specific to a code base. And that provides both generic security advice, but also allows
00:26:24a company to have your specific security rules for that company. So say you're a big bank
00:26:29and you've got a, this is how we handle social security numbers, or this is how we tokenize
00:26:34credit card numbers. That's the kind of context that we can provide into that security agent
00:26:39to make sure the coding agent does its job in the first place. And then we scan that code
00:26:44on the backend to make sure that that rule was provided. And then we also gather telemetry
00:26:48from our IDE plugins. So we can see all of this interaction and make sure that the plugin
00:26:54is doing its job. And then also see all of the unauthorized coding tools that everybody's
00:26:58using. Not that any of you would bring a coding tool to work that was not authorized by your
00:27:03security team. I see lots of rule followers in this room for sure. And so we're already
00:27:11doing this, but it would be super cool if this became a standard thing that lots of different
00:27:18coding agents supported, and then lots of people could compete against us and copy our product.
00:27:22That's fine. We're happy to be the Kleenex of the space by lots of people doing this kind
00:27:26of work. But I think this is going to be the future of having coding agents and security
00:27:31agents have a relationship here, just like security engineers and software engineers
00:27:35have a totally friendly and not at all competitive or difficult relationship these days.
00:27:42We proudly released this to GA today, and we shipped it on Vercel's AI agent marketplace.
00:27:48So we're right there on the top. You can go to corridor.dev to check us out or find us
00:27:52on Vercel's marketplace. We're the only security product there. So we thank very much Vercel
00:27:56for their partnership in that and thank them for giving me this time today. If you want
00:28:01to chat with us, Jack and I, our CEO and co founder, will be out in the corridor to chat
00:28:09about that. Anyway, I think there's a lot we could do together here to give this superpower
00:28:14of AI coding agents to millions of people while also protecting them from these villains that
00:28:21are out there as well. Anyway, I'm Alex, alex@corridor.dev. If you ever want to chat, I'll be out in the
00:28:27corridor or drop me an email. Thank you very much. Thanks so much for Vercel. Have a great
00:28:31rest of your day.

Key Takeaway

While AI code generation offers unprecedented accessibility and power to a broad audience, its widespread adoption necessitates robust security by design, clear differentiation between user types, and standardized security workflows to mitigate inherent risks and protect users from sophisticated threats.

Highlights

AI code generation, or 'vibe coding,' offers an incredible opportunity to democratize computing, making coding a superpower accessible to millions of non-professional users.

Despite its promise, vibe coding presents significant security risks, as AI models frequently generate code with vulnerabilities, creating a 'foot bazooka' for unsuspecting users.

Non-expert vibe coders are ill-equipped to face sophisticated, professional attackers who have decades of experience exploiting software vulnerabilities, as illustrated by frameworks like MITRE ATT&CK.

It is crucial to differentiate between 'vibe coding' for non-professionals and 'AI-assisted engineering' for experts, as each group requires distinct security approaches and solutions.

Vibe coding platforms must implement 'security by design' with opinionated defaults and 'security paternalism,' making responsible decisions for users and refusing out-of-scope projects like medical systems.

For professional engineers, AI tools need to improve big-picture planning and integrate AI security agents to ensure compliance, privacy, and safety, replicating human oversight at AI speed.

Standardization in telemetry and security workflow is essential for making AI coding enterprise-ready, providing visibility into agent actions and enabling deterministic communication between security and software agents.

Timeline

Introduction to Vibe Coding's Potential

Alex from Corridor introduces 'vibe coding' (AI code generation), highlighting its immense potential. He describes it as an 'incredible opportunity' that democratizes computing, making coding a 'superpower' accessible to 'normal people' who previously lacked the means to utilize computers in this way. This revolution promises widespread accessibility, allowing millions to ask computers to perform tasks without needing to write complex code or acquire specialized software. The speaker expresses great enthusiasm for being at the very start of this transformative era.

The Inherent Dangers and Security Flaws

The speaker quickly pivots to the perils of vibe coding, calling it a 'foot bazooka' due to the significant security risks it introduces. He provides numerous examples of bad outcomes, from personal data exposure in simple apps to critical vulnerabilities in medical record or Bitcoin systems, often caused by platforms using poor default configurations. Academic research from the Backbench Academic Group confirms that AI models frequently introduce mistakes and security flaws, with even advanced models like GPT-5 still exhibiting a 20% vulnerability rate in otherwise correct code, which is deemed 'not fantastic' by security professionals. Corridor's internal tests corroborate these findings, emphasizing the persistent challenge of insecure AI-generated code.

The Asymmetric Threat Landscape

This section highlights the dangerous environment new vibe coders face from highly sophisticated, professional attackers. Using a 'Fallout' analogy, the speaker likens new coders to 'vault dwellers' with slingshots confronting 'mutants with sharpened sticks' (experienced malicious actors). He explains the MITRE ATT&CK framework, a comprehensive system used by the U.S. government to categorize and track advanced persistent threats, including state-sponsored groups and financially motivated organizations. These professional attackers have decades of experience monetizing software bugs, making it unrealistic and dangerous to assume that novice vibe coders can understand or defend against such a complex threat landscape.

Distinguishing User Types and Their Needs

The speaker proposes a critical distinction between 'vibe coding' for non-professional users and 'AI-assisted engineering' for professionals. Vibe coders, or 'normal people,' rely on fully-fledged platforms to describe desired outcomes in natural language, often starting with a green field, but they lack the ability to secure the output themselves, leading to issues like lost Bitcoin. In contrast, AI-assisted engineers are professionals who supervise agents, making specific requests within existing codebases and compliance requirements, and possess inherent security skills or dedicated team support. This segmentation is crucial for developing targeted security solutions, acknowledging the vastly different expertise and contexts of these user groups.

Security Solutions for Vibe Coders

For vibe coders, the speaker advocates for 'security by design' and 'security paternalism' in platforms. AI coding agents should be 'opinionated,' making secure architectural and configuration decisions by default, such as implementing role-level security and least privilege. Platforms should also intelligently detect and refuse out-of-scope projects, like medical record or Bitcoin systems, or engage robust security features for sensitive data. The speaker emphasizes that it is acceptable, and even necessary, for platforms to make responsible decisions on behalf of non-expert users, taking some responsibility for safety rather than leaving users exposed to complex security challenges they cannot manage.

Security Solutions for Professional Engineers

Professional engineers also require 'secure by design' tools, meaning AI agents should avoid common security mistakes and proactively suggest better defaults. A critical improvement needed is for agents to develop a 'big picture focus,' engaging in architectural planning, design meetings, requirement gathering, and documenting APIs, input validation, and authentication, rather than immediately generating code. The speaker calls for the integration of 'AI security agents' to replicate the roles of human security engineers, privacy engineers, and compliance officers. This ensures that regulatory and safety rules are enforced at the accelerated pace of AI code generation, acknowledging that human responsibilities and liabilities (like those of a CISO) still exist in the physical world.

Corridor's Vision: Telemetry and Standardized Workflow

Corridor proposes two key areas for making AI coding 'enterprise ready': telemetry and standardized security workflow. Telemetry involves agents pushing all interactions—prompts, tool calls, and generated code—for central enterprise visibility, with Anthropic's Claude Code leading in developing an open standard. The security workflow requires a deterministic mechanism for security agents and software agents to communicate, replicating human review processes for plans and code. Corridor's product, released today, uses IDE plugins to provide codebase-specific security context, scan generated code, and gather telemetry, ensuring compliance with company rules and detecting unauthorized tools. This approach aims to empower millions with AI coding while protecting them from threats, fostering a future where security and development agents collaborate effectively.

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