- Buzz Staff
Tools that can build software can now quietly break it too, exposing hidden weaknesses across systems we rely on every day
Honestly, when I first came across an essay in the New York Times about the internet’s safety net, I thought it was just another tech‑y rant. But as I kept reading, the whole thing felt like a personal story about how the digital world we all use daily is shifting under our feet. It reminded me of those moments when a favorite chai stall suddenly runs out of milk you didn’t expect it, and it throws your whole routine off.
For the longest time, the internet operated on an unspoken balance. Writing software was hard, so only a relatively small group of trained developers could do it. Finding bugs was just as difficult, which meant many vulnerabilities stayed buried for years, sometimes decades. It wasn’t perfect, but the difficulty itself acted like a safety buffer. That buffer, my friend, is now cracking.
Raffi Krikorian, the chief technology officer at Mozilla, wrote an essay that really hit home. He warned that new AI systems are changing both sides of that equation at once. They are making it easier than ever to create software, and at the same time, they’re making it far easier to find what’s wrong with it. I could feel the weight of those words because, in India, the buzz around AI and its impact on the tech scene is everywhere from the latest news India feeds to local meet‑ups.
What happened next is interesting. A powerful AI model from Anthropic managed to uncover vulnerabilities that had gone unnoticed for years. In one case, it identified a 27‑year‑old flaw in OpenBSD a piece of open‑source software that quietly powers many internet services. In another, it found a 16‑year‑old issue in FFmpeg, the library that streams video to your mobile, TV or laptop. These aren’t some obscure academic projects; they sit behind the streaming services we binge‑watch on weekends and the secure networks that banks rely on.
Many people were surprised by this because the same kind of vulnerabilities can be weaponised for ransomware attacks or to breach sensitive systems. The fact that an AI could sniff them out without any human tinkering felt both awe‑inspiring and a little scary especially when you think about how quickly such findings can become viral news among security circles.
At the same time, AI is lowering the barrier to building software itself. I’ve seen shop owners in Delhi describe their inventory needs, and within minutes an AI tool churns out a working app. Clinics in Mumbai outline a patient portal, and poof the code appears. This trend, sometimes called “vibe coding,” feels like a digital version of ordering a custom tiffin; you simply tell the chef (or AI) what you want, and it serves it up.
But here’s the catch most of this code is being created without deep security checks. Picture a friend building a house with cheap bricks; the walls may look fine, but the foundation is shaky. The same risk applies to the software being rolled out across the country.
That creates a new kind of danger. The same tools that make it easier to build software also make it easier to break it. In most cases, the difficulty of both writing and exploiting code used to act like a safety net. Now, that net is fraying.
There’s another layer to the problem, and it’s something I keep hearing in tech‑talks across Bangalore and Hyderabad. Much of the internet runs on open‑source software code that isn’t maintained by giant corporations, but by small teams and volunteers. These projects often have limited budgets, even though they power systems used by millions of Indians every day.
What really struck me was the gap between large companies and these smaller developers. Big players can get early access to advanced AI tools to protect themselves, while the humble developers behind critical infrastructure may not. It feels a bit like the difference between getting the latest iPhone versus using an old Nokia the disparity could leave parts of the internet far more exposed.
Krikorian argues that the solution isn’t to slow down innovation. That would be like telling everyone to stop using smartphones because they’re too clever. Instead, we need to rethink how security is built into these AI‑driven workflows. AI tools that generate code should also be designed to secure it think of a chef who not only cooks but also sanitises the kitchen.
Because the real shift isn’t just technological, it’s structural. The internet is no longer being built solely by experts; it’s being built by everyone from a student in Pune experimenting with a chatbot to a farmer in Kerala using a simple app to track weather. As this democratisation speeds up, the systems that protect it need to evolve just as quickly.
Imagine you’re watching a trending news India feed about a new AI‑generated app that promises to solve traffic woes in Delhi. You click, you install, and everything works fine until a hidden flaw, discovered by the same AI, gets weaponised by hackers. That scenario, while sounding like a plot from a thriller, is becoming a realistic possibility. The question now isn’t whether AI will change the internet it already is. The question is whether the protections keeping it stable can keep up.
From a personal perspective, I’ve started paying more attention to how I write code, even for tiny scripts. I double‑check security practices, because the line between building and breaking is thinner than ever. If you’re following breaking news about cybersecurity, you’ll notice an uptick in stories about AI‑found bugs and AI‑generated exploits. Those stories are becoming part of the viral news cycle, and they underline the urgency of the issue.
So, what can we, as everyday internet users and budding developers, do? First, stay informed keep an eye on India updates that talk about AI and security. Second, support open‑source projects; a small donation or even a simple pull request can help fortify the foundations that many services rely on. Third, when using AI‑powered code generators, ask yourself: does this tool also check for security holes? If not, treat the output as a draft, not a final product.
In the end, the story feels like a big family dinner where everyone’s invited to cook, but the chef still needs to watch the stove. The internet’s safety net is being rewoven, and we all have a role in making sure it’s strong enough for the next generation of digital experiences.
