Comment by nickwrb
Probably the heavy AI-generated feel to the article.
Probably the heavy AI-generated feel to the article.
...and the question what an Next.js audit has to do with "expert blockchain security audits", as advertised by BlockHacks (OP).
That’s a fair question.
Blockchain security work is rarely just cryptography in isolation. Web3 applications are still web applications. Wallets, dashboards, admin panels, and APIs are part of the system, and many of them are built with frameworks like Next.js.
Many of our clients building decentralized applications use Next.js as the frontend and sometimes as the backend-for-frontend layer. In real audits, issues often span both sides: smart contracts and the web stack that exposes them.
This article focuses on the web execution side of that reality, not on-chain cryptography. If you are only interested in protocol-level or cryptographic audits, we publish separate articles that focus specifically on those topics.
The point here is that compromises do not respect category boundaries. They usually start at the web layer and move inward.
Out of curiosity, in your experience, do you usually see real-world compromises starting at the contract layer itself, or at the surrounding web and infrastructure layer that interfaces with it?
Just to address the “AI-generated” point directly:
This isn’t something you can realistically get out of an LLM by prompting it....
If you ask an AI to write about Next.js RCE, it will stay abstract, high-level, and defensive by default. It will avoid concrete execution paths, real integration details, or examples that could be interpreted as enabling exploitation — because that crosses into dual-use content.
This article deliberately goes further than that line: it includes real execution ordering, concrete framework behaviors, code-level examples, deployment patterns, and operational comparisons drawn from incident analysis. That’s exactly the kind of specificity automated filters tend to suppress or generalize away.
It’s still non-procedural on purpose — no payloads or step-by-step exploitation - but it’s not “AI vague” either. The detail is there so defenders can reason about where execution and observability actually break down.
Whether that level of detail is useful is subjective, but the reason it reads differently is because it’s grounded in real systems and real failure modes, not generated summaries.