The Rise of “GPT Kiddies”: A New Breed of Security “Researchers”

In the early days of cybersecurity, the term “script kiddie” was coined to describe individuals who lacked genuine technical skills, yet ran prefabricated scripts to exploit known vulnerabilities. Today, we’re witnessing the emergence of a new, curious parallel: the “GPT kiddies.” These aspiring security researchers are turning to large language models like ChatGPT, relying on them not just as tools, but as their primary — often only — source of expertise. The result? A surge in hastily assembled, half-baked vulnerability reports that offer little evidence, minimal context, and rarely stand up to scrutiny.

The appeal of GPT-based code analysis is undeniable. With a few keystrokes, anyone can have an AI comb through a GitHub repository and generate a detailed-sounding “assessment” of potential weaknesses. At a glance, these automated outputs look polished, peppered with technical jargon that can impress the casual observer. But dig beneath the surface, and cracks begin to appear. The tools, while powerful, frequently hallucinate security findings — highlighting non-issues as critical vulnerabilities or proposing exploits that don’t actually work in practice.

For seasoned professionals, it’s become increasingly easy to spot these GPT-driven security “reports.” They often omit vital details like verifiable proof of concept code, realistic attack vectors, or concrete paths to weaponization. Instead, they’re padded with generic suggestions or dramatic language about “severe implications,” never quite getting to the heart of how, exactly, a system can be compromised.

As with script kiddies before them, the problem isn’t the technology itself — AI-based tools can be tremendously beneficial in expert hands. The real issue emerges from the unwarranted flood of AI-generated “findings” that security professionals must wade through on a daily basis. These experienced researchers, already juggling a relentless stream of legitimate threats, now find themselves forced to pick through a swarm of nonsensical vulnerability claims. Hours that could be spent hunting true weaknesses or refining defenses are instead lost double-checking flimsy evidence and debunking alarmist language. The fatigue is palpable: it’s exhausting to constantly justify why a so-called exploit reported by a GPT kiddie doesn’t hold water, even when the AI-driven commentary sounds convincingly professional at a glance.

In light of this, the community must refocus on what truly matters in vulnerability research: solid methodology, critical thinking, and proven expertise. We can’t rely on AI-generated text as a shortcut to understanding complex codebases or discovering meaningful exploits. Rather, we must encourage genuine education, hands-on training, and careful mentorship. Only by doubling down on genuine human skill — supported, rather than overshadowed, by AI tools — can we shield dedicated professionals from the deluge of dubious reports and keep the security industry moving forward with integrity.

And yes, you’ve guessed correctly — this post was generated by GPT.

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