The Next Big Cyberattack Might Not Start With a Phishing Email

For years, we have been telling employees not to click suspicious links, open unknown attachments, or fall for phishing emails. But I think we are overlooking something much more dangerous.

What if your next security breach doesn't start with someone clicking a phishing link, but with someone who Googled a problem, found a GitHub repository, and pushed it, as it is into the production without understanding a single line of code?

Imagine a developer trying to implement a feature. They don't really understand how it works, so they Google it or ask ChatGPT, Claude, or whatever AI assistant they're using. A GitHub repository pops up in their recommendation and it has decent number of stars & multiple influencers recommending that git repo on social media so you know it can make your job easier right.

Perfect! Clone it. Run it. It works. Push to production. Job done.

Except nobody bothered to check what the repository was actually doing in the background & that's where things get interesting.

We're Trusting Things We Have Absolutely No Reason to Trust Just because our AI/Search engine is Recommending us to use it

The recent Binance hack is a reminder of how damaging a compromised development environment can be.

On October 29, 2026, Binance suffered a massive security breach involving approximately $6.3 billion in crypto assets. Its initial investigation pointed toward a compromised DevOps engineer's laptop, although the company has since identified additional points of compromise.

The full attack chain is still being investigated. But here's what concerns me: We spend millions securing infrastructure, implementing zero-trust architectures, deploying EDRs, configuring SIEMs, and buying every security product.And then someone with access to sensitive systems downloads random code from the internet because it has a few hundred GitHub stars.

What could possibly go wrong? I have personally come across multiple GitHub repositories with over 500 stars that were doing things they absolutely shouldn't have been doing.

Some were effectively functioning as droppers, capable of bringing in additional payloads, including command-and-control (C2) components, when the opportunity presented itself.

I'm deliberately not getting into the technical details here (part of ongoing investigation). But think about that for a moment. A repository can look completely legitimate, perform the function it advertises, and still carry something malicious.

SEO Poisoning Was Bad Enough. Now We Have AI in the Middle.

SEO poisoning is not new, but now we have AI assistants, AEO, GEO, what not… And attackers are learning how to influence those results, too.

Whether it's through traditional SEO or content designed to perform well in AI-powered answers (AEO), the objective is simple: make malicious resources look like the most relevant solution to someone's problem.

Frankly speaking, it is easier to ask influencers to promote your git repo by paying few bucks, I have came across few influencers who are promoting malwares without knowing what they are actually promoting, they are simply following the script.

End result… You ask an AI assistant. It recommends something similar.

Suddenly, you're seeing the same repository everywhere. That doesn't make it trustworthy. It just makes it easier to find. And when developers start treating AI recommendations as some sort of security validation, we are creating a problem far bigger than hallucinated code.

We're making it easier for attackers to get untrusted software into environments they could never access directly. The attacker might not even need to send you a phishing email anymore.

You'll search for their malicious code yourself, download it voluntarily, and thank the AI assistant for saving you time.

AI Can Write Code. That Doesn't Mean You Understand It. Before someone takes this the wrong way, I am not against AI. I use AI extensively myself. It's incredibly useful, and anyone pretending it isn't changing software engineering is probably living under a rock.

But there's a massive difference between using AI to become a better engineer and using AI because you have absolutely no idea what you are doing. These days, people are building entire applications with AI without understanding the underlying code. Don't get me wrong, you don't need to manually review millions of lines of dependency code to be a good developer.

But you should at least understand what you're installing, what permissions it needs, what dependencies it introduces, what scripts it executes, and why it needs to communicate with external services. If you are pushing code into production, you should be able to explain what it does.

Not what the README claims it does.

Because when something goes wrong, your AI assistant isn't going to attend the incident-response meeting and explain why production was compromised.

The Next Supply-Chain Attack Could Be One pip install Away

Here is something I wish more organizations understood. Not every malicious dependency is designed to cause immediate damage. Some components work exactly as advertised.

They might sit quietly until certain conditions are met, or until another component is fetched or updated.

And by the time suspicious behavior becomes obvious, the original code may have already been trusted, packaged, and distributed through your development pipeline. That's what makes supply-chain attacks so interesting from an attacker's perspective.

Why spend months trying to break into a heavily protected organization when you might be able to convince someone inside it to install your code?The attack surface isn't just your servers anymore. It's your developers, their laptops, their dependencies, their AI assistants, and every third-party repository they decide to trust. Organizations need to start treating external code as untrusted until there's a reasonable basis to trust it.

Review unfamiliar dependencies. Check installation scripts. Understand where code comes from. Test questionable tools in isolated environments. And for the love of security, stop assuming that a successful build means something is safe.

One Last Thing

I genuinely believe AI is going to make software development faster and more accessible. But I also think we are creating an entire generation of people who are comfortable deploying code they cannot explain. That's a dangerous combination. Attackers are already exploiting trust in open-source ecosystems, search results, and software dependencies.

Add AI-assisted development and poorly reviewed code into that mix, and you have the perfect conditions for some very ugly supply-chain incidents.

All I am saying that if you have the responsibility to deploy code, understanding what that code does should be the bare minimum.

Your next major security incident might not start with a sophisticated zero-day. It might start with a developer who found a convenient GitHub repository, asked an AI assistant how to integrate it, and never questioned what they were actually running. And the funny part?

They will probably tell everyone how much development time AI saved them.

Use AI. Automate things. Build faster. But for God's sake, learn to read the damn code.