AI Is a Double-Edged Sword: Startups, Reverse Engineering and Website Security

By Hitesh Mahay · 2 November 2026 · Hitudios

Today I am thinking about how much AI has helped us, and how uncomfortable the other side of that progress can feel. It helps us solve problems, understand code, and turn ideas into working products. The same capabilities can make software easier to analyse, features easier to reproduce, and security weaknesses easier to investigate. What does that mean for startups, existing websites, and the businesses trusting these systems?

I like AI. I use it, and I can see how much it has changed the way we approach difficult work. As someone working across web development, e-commerce, and AI workflows, I find it useful for exploring a problem, understanding unfamiliar code, and working through possible solutions. A confusing error becomes easier to investigate. An idea becomes easier to prototype. Documentation becomes easier to navigate.

That is real progress. More people can learn, experiment, and build things that would previously have required a larger team or a bigger budget. Small businesses can explore better digital tools, and developers can spend less time getting stuck on routine work.

But I keep coming back to the same thought: the capabilities that help builders can help attackers too. When understanding software gets cheaper, examining a website for mistakes gets cheaper as well. That makes me optimistic about what we can create and more careful about how we release it.

AI is not automatically safe or unsafe. Risk depends on the task, the data it can access, the permissions it receives, and the checks around its output. An assistant that suggests draft text has a different risk profile from an agent that can change customer records or deploy code.

There is also a distinction between a website built with AI assistance and a website that contains an AI feature. Generated code still needs the usual engineering review. A chatbot or agent adds further questions about untrusted instructions, sensitive information, connected tools, and operating costs.

My view is that confidence should come from evidence: tested permissions, reviewed changes, monitored behaviour, and a clear recovery path. The fact that a demo works is only the beginning of that process.

Sometimes it feels as though everything is becoming available to everyone: open-source tools, reusable components, public examples, and AI that can explain how a product might work. That is exciting when you are learning or building. It feels different when you are the founder wondering how quickly someone could recreate your idea.

One uncomfortable question is what happens to startups when it becomes easier to understand and reproduce software. AI can assist with analysing visible interfaces, public documentation, and code someone is permitted to inspect. That can reduce the effort needed to recreate familiar features. Reverse engineering also has legitimate uses, such as compatibility work and authorised security research; the purpose and permissions matter.

It does not mean every startup disappears or every private product becomes open source. Open source is a licensing choice; a public website does not grant permission to copy its private code, content, or brand. Reproducing an interface also does not reproduce a company's customer relationships, operational knowledge, distribution, or service quality.

I do not think this means there will be no new startups. I think it changes what a startup has to prove. If a product's entire advantage is one easily reproduced feature, AI may make that advantage harder to defend. Understanding a specific customer problem, delivering reliably, and earning trust become even more valuable. That is my view of the competitive pressure, rather than a prediction that every business will face the same outcome.

For website security, there is a practical rule here: assume visitors can inspect what their browser receives. Frontend code and hidden interface buttons cannot be the place where you protect secrets or enforce access. Those controls belong on the server.

This concern is already part of real defensive security work. In its May 2026 Project Glasswing update, Anthropic describes using AI to identify vulnerabilities in important software and highlights the work required to verify, disclose, and patch findings. This is evidence of capability, rather than a reason to assume every reported finding is correct. Read Anthropic's update.

There is also evidence of misuse. Anthropic's September 2026 threat-intelligence report describes actors using its models for activities including reconnaissance, reverse engineering, and exploit research. These are the vendor's reported observations, not a measurement of every attack or proof that AI caused every recent breach. They do show why the question deserves attention beyond hypothetical future scenarios. Read the September 2026 report.

For a business, the implication is straightforward: finding a weakness is useful only when someone can confirm it, prioritise it, and repair it safely. A long automated report can still contain false positives or miss a problem that depends on your business rules.

I would treat AI as an assistant in a website security audit. It can help investigate and organise work, while accountable people define the scope, evaluate evidence, and verify fixes. Testing should take place only on systems the owner has authorised.

When I read about new hacks, bugs, and unexpected agent behaviour, I keep asking: are we exploring the edge cases as quickly as we are adding features? That question does not require claiming that all incidents are new or caused by AI. Familiar weaknesses can still create unfamiliar outcomes when more systems connect.

Security problems often live outside the happy path. A customer follows an old password-reset link. A staff account changes roles while its session remains active. An integration retries the same event twice. A form accepts input that the interface never expected.

Consider a customer portal: the screen may hide another customer's invoice, but does the server also refuse a direct request for it? Consider a payment integration: if a webhook is delivered twice, does the business process the same event twice? These are illustrative scenarios, not vulnerabilities I am claiming to have found in a particular client website.

AI features introduce additional failure paths. A document retrieved by a chatbot might contain instructions that conflict with the user's request. An agent might receive broader permissions than the task needs. An unchecked response might reach another system in a form that causes harm.

OWASP's guidance for generative AI applications identifies prompt injection, information disclosure, unsafe output handling, and excessive agency among its risk categories. Those are useful starting points for a review; they are not evidence that a specific application is vulnerable. See the OWASP Gen AI guidance.

Age alone does not determine whether a website is secure. An older site with active maintenance can be better managed than a newly launched site with weak access controls. What matters is what has changed, what is exposed, and whether someone is responsible for keeping it current.

A website security review is especially useful if you cannot identify who maintains the site, which plugins or packages it uses, who still has admin access, or whether backups can actually be restored. New customer accounts, payment flows, integrations, or AI features are also good reasons to reassess the risk.

OWASP's web application guidance includes access control, configuration, software supply chains, authentication, and exceptional conditions. AI does not remove the need to address these established areas. See the OWASP Top 10:2025.

The scope should match the business and the systems you own. A brochure website, a Shopify store, and a custom customer portal require different work. Start with the important data and actions, then review the controls protecting them.

• Accounts and permissions: who can sign in, what each role can do, and how access is revoked.
• Server-side checks: whether requests are authorised independently of the visible interface.
• Dependencies and configuration: maintained packages, supported software, deployment settings, and secret handling.
• Forms and integrations: validation, abuse controls, uploads, and duplicate-event handling where relevant.
• AI features: prompt injection exposure, permitted tools, sensitive data access, and spending limits.
• Recovery and evidence: useful logs, a tested backup process, prioritised findings, and verification after repairs.

An automated scan can support this work, but it cannot prove a site is completely secure. A useful audit explains what was reviewed, what was found, what remains uncertain, and which fixes matter first.

New businesses have an opportunity to establish sensible controls from the start: individual accounts, limited permissions, secure configuration, maintained dependencies, and a clear owner for updates. Building those habits into delivery is easier than discovering later that nobody knows how the site is operated.

This connects to the broader digital foundations I build through Hitudios. For example, my portfolio documents work for Suraj Enterprises covering a website, domain, professional email, and Google Business Profile. That project illustrates connected business delivery; it is not presented as a penetration-testing case study. Explore my work.

I want to keep using AI because it helps solve real problems. I also want the review process to keep pace with the speed of building. More generated code, more integrations, and more autonomous actions mean more situations to think through before customers depend on a system.

If you have an older website and need help understanding its maintenance and security risks, contact me to discuss a scoped review. If you are starting a business, I can help plan and build your digital presence with those questions considered from the beginning.

I am Hitesh Mahay, the developer behind Hitudios. This article was written for my portfolio. Tell me what your website does, what you are concerned about, and what systems you own. Contact me through my portfolio or write to hitesh@hiteshmahay.com to discuss the next step.