Vibe Hacking: When AI’s Coding Revolution Becomes a Cybercrime Superpower

In early 2025, the idea of “vibe coding” started gaining attention. Coined by AI expert Andrej Karpathy, it described a new way to build software using AI. Instead of writing every line of code by hand, developers could give high-level instructions, and AI would handle the details. This made creating apps faster, more fun, and easier for non-experts.

Soon, this approach spread beyond software.

People started talking about “vibe marketing” and other AI-powered workflows. The core idea stayed the same: move fast, trust your instincts, and let AI do the heavy lifting. This new mindset, called the “vibe ethos,” became popular because it delivered quick results with less effort.

But this rush toward speed came with serious risks.

The same tools that helped people innovate also made it easier to cheat, scam, or build unsafe systems. This is where Vibe Hacking begins. Vibe Hacking is when someone misuses these AI tools—either on purpose or through carelessness—to create harmful or unethical outcomes.

This isn’t just a theory. Vibe Hacking is already happening. Some people are using AI to write fake websites, launch scams, and hide their tracks. Because the tools are so easy to use, even beginners can now pull off complex cybercrimes. What started as a creative shortcut has become a real cybersecurity threat.

Vibe Hacking: Playful Prototypes to AI-Powered Exploits

The evolution of “vibe coding” started as a fun and informal way to build software. But in just a few months, what began as a light-hearted experiment turned into a powerful—and sometimes dangerous—approach to working with AI.

To understand the risks of Vibe Hacking, we first need to understand how the original idea of “vibes” took off, and how easily it has been twisted for harmful use.

The Birth of Vibe Coding: Karpathy’s Experimental Style

In February 2025, Andrej Karpathy shared an idea he called “vibe coding.”

His version wasn’t a strict method. It was more of a mindset. He described a process where you just “see stuff, say stuff, run stuff, and copy-paste stuff.”

Using tools like SuperWhisper and AI coding assistants, he could talk to the computer and quickly build something functional.

He made it clear this approach wasn’t meant for serious production software. It was good for small projects or weekend experiments. Karpathy even warned that AI often struggled with debugging and fixing issues.

Still, the process felt magical—it made coding feel fast and intuitive, even casual. The key was: don’t overthink it, just vibe.

The Buzzword Effect: From Idea to Hype

What happened next is something we often see in tech. A simple idea got picked up, amplified, and rebranded as a major shift.

“Vibe coding” became a hot term across Silicon Valley. Articles described it as the future of development. It even made it into the dictionary as a trending new word.

But with that hype came a loss of context.

People forgot Karpathy’s original caution—that vibe coding wasn’t perfect or professional-grade. Instead, many started using it as a shortcut for fast development. Even beginners, inspired by the trend, began using AI tools without always understanding what the code did.

This rapid adoption widened the gap between what vibe coding was meant to be and how it was being used. It became less about fun experiments and more about moving fast, regardless of risk.

The Rise of Vibe Marketing: Speed Over Precision

Soon, the same vibe philosophy moved into the business world. One of the biggest shifts was in marketing. In early 2025, “vibe marketing” took off.

The idea? Replace human workers with AI agents across the entire marketing stack. AI would generate content, test ideas, and run campaigns—all while humans focused on strategy and emotional tone.

This wasn’t just theory. Big brands like Coca-Cola and Spotify used AI in major ad campaigns before the term vibe marketing existed.

For example, Coca-Cola invited fans to create art using DALL·E 2. Heinz used AI-generated images of ketchup bottles to spark social media buzz. Spotify’s AI DJ kept users listening longer by hosting playlists with a cloned human voice.

The results were impressive.

Fewer people could do more, faster. But there was a catch. In all this excitement about speed and automation, people began to ignore the need for review, ethics, and careful decision-making.

That’s when the trouble started.

The Shift to Exploits: When Vibes Go Wrong

The very things that made vibe coding and vibe marketing successful—speed, simplicity, and scalability—also made them dangerously easy to abuse.

That’s where Vibe Hacking enters the picture.

Vibe Hacking happens when someone misuses these AI tools, either by acting carelessly or with clear intent to harm. One major example is VibeScamming, a practice uncovered by cybersecurity researchers. It involves using AI to build entire scam campaigns—from fake websites to phishing text messages to infrastructure for stealing data.

Here’s what makes it so dangerous: unlike traditional cybercriminals, these scammers don’t need to write complex code. They just need to know how to “talk” to AI in the right way.

With a few prompts, they can generate everything they need. And because AI works fast, they can launch these attacks quickly and at scale.

Breaking Down the Anatomy of Vibe Hacking

Vibe Hacking isn’t a vague threat—it’s powered by specific tools, real tactics, and proven methods. To stop it, we need to first understand how it works.

The AI Tools Behind Vibe Hacking

The same powerful AI tools used in vibe coding and marketing are now being misused for cybercrime. At the heart of this is a group of large language models (LLMs) like ChatGPT, Claude, Gemini, DeepSeek, and others.

These models understand natural language and can write real code, fast. That means people can just describe what they want in plain English—and the AI writes the software.

Tools like Cursor, GitHub Copilot, Replit, and Lovable are built on these models. They help people build apps, websites, and more with little or no coding experience. Karpathy once described this shift by saying, “The hottest new programming language is English.” And he was right. You no longer need to know Python or JavaScript—just explain your idea, and the AI builds it.

This is great for startups and indie developers. But it’s also great for scammers.

Since these tools are so easy to use, even someone with no tech background can now create harmful software or scam websites. For example, researchers showed how Lovable, a tool made to simplify web app development, could also be used to create realistic fake login pages to steal passwords.

Worse, as companies rush to make their AI tools more powerful and user-friendly, security sometimes falls behind. Many tools don’t have strong protections in place, making them easier to abuse.

This is how Vibe Hacking becomes possible: the tools are fast, simple, and not always safe.

Techniques Used by Vibe Hackers

Vibe Hackers use a mix of fast automation and clever tricks. They take the vibe approach—speed and simplicity—and aim it at harmful goals. Here are the most common methods:

VibeScamming

This is a major tactic. Attackers use AI to create entire scam campaigns. They make fake websites that look like Microsoft login pages, write phishing text messages, and even hide their actions from security systems.

Sometimes, these platforms go so far as to automatically host the scam site, collect stolen passwords, and show the hacker all the stolen data in a clean dashboard.

Insecure AI-Generated Code

LLMs often write code with built-in flaws. They can accidentally include dangerous bugs like:

• SQL Injection (SQLi) and Cross-Site Scripting (XSS) because they don’t always clean up user input properly.
• Weak access controls, like putting admin checks only on the front end, which users can easily bypass.
• Hardcoded secrets, like passwords or API keys, right in the code—especially risky if the code is made public.

Because many users don’t double-check what the AI creates, this insecure code ends up running live on the internet.

Jailbreaking and Prompt Engineering

More advanced hackers go a step further. They “jailbreak” the AI—tricking it into breaking its own safety rules. They do this by crafting special prompts, or using storytelling tricks to fool the AI into writing malicious code, like keyloggers or phishing tools.

Some of these methods include:

• Bad Likert Judge: Gradually pushing the AI into giving riskier responses.
• Immersive World: Building a fictional world in the prompt where the AI thinks it’s okay to break rules.

These tricks are clever—and they often work. The AI tries to be helpful, so it follows the instructions, even if they lead to harmful results.

Real-World Case: The Lovable Exploit

One of the clearest examples of Vibe Hacking comes from the AI platform Lovable. It was built to help users create web apps with simple text commands. But researchers found they could use it to:

• Generate fake Microsoft login pages.
• Automatically host those pages on Lovable’s own web address.
• Collect stolen login data in a ready-made admin dashboard.

Even worse, Lovable reportedly didn’t block the scam or fix the issues right away. The platform had a security scanner, but it reportedly gave false positives—making users think their app was safe when it wasn’t. For months, personal and financial data on the platform remained exposed.

Lovable also scored poorly on the VibeScamming Benchmark, a tool that rates how easy it is to misuse AI platforms. Lower scores mean more danger. Lovable scored 1.8, while Claude scored 4.3, and ChatGPT scored 8 (the higher, the better).

This case shows what happens when speed and ease-of-use are put above security: AI tools meant to help users can just as easily help scammers.

A Broader Pattern: Insecure AI Apps Everywhere

While Lovable is a clear example, the problem isn’t limited to one tool. Studies show that AI-generated code is often “remarkably insecure.”

In fact, a benchmark test called BaxBench found that 62% of AI-written code had major flaws. Even when users asked the AI to write secure code, many vulnerabilities still slipped through.

Reports describe projects built entirely with AI that were quickly hacked due to simple mistakes—like missing input checks or exposed passwords. This happens because some developers trust AI too much. They assume the code is safe, even if they don’t fully understand it.

This overconfidence is part of the problem. AI can write code in ways that don’t make sense to humans. So if you don’t check carefully, hidden flaws can sneak in—and attackers know how to find them.

Inside the Vibe Hacker Mindset: Who’s Exploiting What—And Why

Vibe Hacking isn’t just about the tools—it’s about the people who use them.

These human actors, with different goals and skill levels, are the real drivers behind the misuse of AI for scams, cyberattacks, and unsafe software. To defend against Vibe Hacking, we need to understand who these people are, what motivates them, and how they think.

Script Kiddies 2.0: Novices with AI Superpowers

The largest and fastest-growing group of Vibe Hackers are beginners.

These are people who don’t know how to write code the traditional way. But thanks to AI tools, they don’t need to. With just a few prompts in plain language, they can generate scam websites, phishing messages, or even working malware.

In the past, these types of attackers were called “script kiddies”—people who used tools made by others. Today, they’ve evolved into what we might call Script Kiddies 2.0.

The difference? Now they can create their own attack tools using AI, even without understanding how they work.

Guardio Labs described this clearly in their report on VibeScamming: AI tools today can fulfill “every scammer’s wishlist.” That means even low-skill attackers can launch convincing scams at scale. While each scam might be simple, the total volume of attacks is growing—and that’s what makes them dangerous.

Opportunistic Attackers: Scaling Up with AI

More skilled attackers are also using AI—but for different reasons. These are people who already know how to hack or scam, and they see AI as a new way to move faster. They might use AI to:

• Write more realistic and grammatically correct phishing emails.
• Generate malware variants that can bypass security software.
• Automate boring tasks like scanning for weak websites or creating fake accounts.

For these actors, AI isn’t replacing skill—it’s multiplying their output. They can now run bigger, faster, and more complex operations with less effort.

The Negligent Vibe Coder: Not a Hacker, But Still a Risk

Not every danger comes from someone with bad intent. There’s another group that causes harm without meaning to: the negligent vibe coder.

These are developers who use AI to write code and trust it too much. They might skip testing or reviewing the code, because the process feels fast and easy. They may fully embrace the idea of “forgetting the code exists,” which was originally meant for quick experiments—not production apps.

While they don’t intend to harm anyone, their work can still introduce serious risks. If they release an app with security flaws, it can be exploited by real attackers. That makes their impact similar to a hacker’s—even if they didn’t mean to cause problems.

Looking Ahead: From Amateurs to Advanced Threats

So far, most public examples of Vibe Hacking have involved low-skill users or platforms with weak security. But that might not always be the case. In the future, we could see more advanced players—like organized cybercrime groups or even state-sponsored attackers—use the same AI techniques.

They could apply the vibe approach to scale attacks, discover new exploits, or automate parts of complex operations. Because AI is so flexible and powerful, its use in cybercrime may only grow.

Defending Against the Vibe: Strategy, Ethics, and Responsibility

The rise of Vibe Hacking demands more than just quick fixes. It calls for a complete shift in how we build with AI, how platforms are secured, and how people interact with AI-generated content. This isn’t about slowing down innovation. it’s about making sure we build safely, responsibly, and intelligently.

Below, we explore how we can achieve that.

Smarter Detection Tools

Traditional security tools, which rely on known threats, can’t always detect scams built by AI. That’s why we need AI-powered defenses. Tools should be able to spot AI-generated phishing websites, scam campaigns, or insecure code.

The VibeScamming Benchmark is one early example. It tests how easily different AI models can be misused, and these insights can help shape better detection systems going forward.

Responsibility at the Platform Level

Platforms that let users build apps with AI—like Lovable—must take more responsibility. They need stronger safeguards to stop users from creating and sharing malicious content.

This means better content review systems, smarter security checks, and active monitoring of how their tools are used. Safety features can’t be just for show—they need to actually work.

Making AI Models Safer by Design

LLMs must be trained to resist abuse. Right now, it’s too easy to jailbreak a model with clever prompts. Developers need to focus on improving alignment—making sure the AI understands not just what the user asks for, but whether that request is ethical or safe. This includes better internal filters, more secure training methods, and ongoing testing for loopholes.

Educating the Human Firewall

Even the best tools won’t work if people are easily fooled. Since AI can now generate scam websites that look completely real, users must learn to stay alert. Education and awareness are key. People need to understand that not everything that looks legit actually is, especially in the AI era.

Stop Trusting AI Code by Default

One of the biggest problems with vibe coding is blind trust. Developers often skip testing or code review because the AI “sounds right.” That mindset has to change. AI-generated code should be treated as untrusted by default—it needs the same deep review and testing as any human-written code.

Security expert Simon Willison put it best: if you’re thoroughly reviewing AI-generated code, then you’re no longer vibe coding recklessly. You’re using AI responsibly.

Keep Humans in Charge

AI can speed things up—but it shouldn’t make critical decisions on its own. Humans must remain involved, especially when it comes to security design, sensitive data handling, or final approval before code goes live. AI is the assistant—not the architect.

Train Developers to Prompt for Security

Developers should learn how to ask the right things from AI. This means writing prompts that include security requirements and asking AI to check for its own mistakes. While this won’t solve every problem, it’s a good start toward safer outcomes.

Build Security Into Every Stage

Security checks shouldn’t happen at the end. They should be built into every part of the workflow. This includes using AI-powered code scanners, setting up automated checks, and reviewing code regularly—not just when something breaks.

Upskill the Next Generation of Developers

The future belongs to the AI-augmented secure developer. This is someone who knows how to use AI effectively—but also understands security, ethics, and code. These developers don’t just build fast. They build smart, safe, and with accountability.

Training must cover AI tools, yes—but also basic secure coding practices, AI ethics, and common AI-generated risks like hardcoded secrets or weak access controls.

Use AI for Security, Not Just Speed

AI isn’t just for writing code—it can also help find bugs. Developers should use AI tools for static and dynamic analysis to catch vulnerabilities in real time. AI can help protect us, not just empower attackers.

Stick to Good Coding Habits

AI doesn’t replace the basics. Break your code into small parts. Test each part thoroughly. Keep version control tight. Never deploy anything you don’t understand. These habits are even more important when using AI.

Balance Innovation with Responsibility

AI in software development isn’t going away. In fact, nearly 97% of developers already use AI tools. And they’re here to stay. These tools can make us more creative, more productive, and more capable—if used wisely.

But Vibe Hacking is a warning sign. It shows what can go wrong when power is used without responsibility. The only way forward is to build systems, tools, and habits that balance speed with safety.

Fighting Vibe Hacking isn’t just up to developers. We need:

• AI tool vendors to build safer platforms.
• Security researchers to study vulnerabilities.
• Companies to train their teams and monitor app security.
• Policymakers to set basic rules and ethical standards.

Everyone has a role to play. This is not just a technical challenge—it’s a social and ethical one too.

Conclusion: From Hype to Responsibility—The Future of the Vibe

AI is changing the way we build, market, and create. What started as a playful idea—“vibe coding”—has grown into a powerful method for fast, intuitive development. But as we’ve seen, speed and simplicity come with real risks.

The same tools that make it easier to build apps can also be used to launch scams, steal data, and spread insecure code. This is the world of Vibe Hacking.

But this isn’t a call to slow down or reject innovation. It’s a call to grow up the vibe. That means building better defenses, training smarter developers, and holding platforms accountable. It means treating AI as a powerful partner—not a shortcut past responsibility.

The future belongs to those who can blend creativity with caution, and speed with security. Whether you’re a developer, a business owner, or an AI platform builder, the challenge is the same: move forward boldly, but with your eyes open.

Article last updated on: Last updated: June 5, 2025