Vibe Coding Security: 5 Questions to Ask Before Trusting an AI-Built App

Vibe coding has arrived in Spanish businessesSince the term was coined in early 2025, AI-assisted development — often called vibe coding — has spread...

Vibe coding has arrived in Spanish businesses

Since the term was coined in early 2025, AI-assisted development — often called vibe coding — has spread quickly through startups, agencies and in-house teams across Barcelona, Lleida, Tarragona and Girona. The appeal is obvious: a founder with an idea can ship a working prototype in a weekend, and a small company can test a new service without hiring a full development team. What used to take months of planning now happens in a few prompts.

The problem is that speed comes at a price. AI assistants are optimised to produce something that works, not something that is secure. When you download or commission an app built this way, you are inheriting decisions that nobody may have reviewed. For system administrators, hosting providers and SMEs running their own servers, that inheritance can turn into a real operational risk.

Why AI-generated code hides its flaws

Traditional code review assumes a human wrote the logic and can explain it. Vibe-coded applications often arrive as a black box: the developer may not fully understand why the AI chose a particular library, pattern or configuration. Common weaknesses include:

Hardcoded secrets. API keys, database passwords and tokens left directly in the source code, where automated scanners can find them within minutes.
Missing input validation. Forms and endpoints that accept anything, opening the door to injection attacks and corrupted data.
Weak or absent access controls. Users able to read or modify records that belong to someone else.
Open default settings. Profiles, dashboards or storage buckets exposed to the public internet by default.
No rate limiting. Login and API endpoints that allow unlimited attempts, making brute-force attacks trivial.
Poor or missing encryption. Data readable in transit or at rest if it is intercepted or leaked.

There is also a newer class of risk: prompt injection. If an AI assistant processes web content or user messages while holding access to private data, a malicious instruction hidden in that content can redirect it. The consequences range from data leakage to unauthorised actions on connected accounts.

The five questions to ask before you trust an app

You do not need to be a security engineer to ask the right questions. Whether you are evaluating a SaaS tool for your company or reviewing a supplier's platform, these five checks will filter out most of the danger.

1. Where are the secrets? Ask how API keys and credentials are stored. If the answer is "in the code" or "we are not sure", treat the app as compromised until proven otherwise.
2. Who can see whose data? Request a clear explanation of access controls. A serious provider will describe roles, permissions and how tenant isolation works.
3. What happens under abuse? Ask about rate limiting, account lockouts and monitoring. An app with no protection against repeated login attempts is an open invitation.
4. How is data protected? Confirm encryption in transit and at rest, and check how the provider handles GDPR obligations, including data processing agreements and breach notification.
5. Who reviews the code? Find out whether a human security review happens before release, and whether the provider runs periodic penetration tests.

What can go wrong if you skip the checks

The consequences are not abstract. In one well-documented case, a security researcher found sixteen vulnerabilities — six of them critical — in a single application built on a popular AI development platform. Some of those flaws exposed sensitive user information, and the app had already been viewed by more than a hundred thousand people. The platform patched the issues afterwards, but the lesson stands: distribution does not equal verification.

For a business, the fallout can include leaked customer records, identity fraud, compromised payment data, stolen session tokens and, in the worst case, malware installed on internal systems. In Spain, a serious data breach also triggers GDPR obligations: notification to the supervisory authority, communication to affected users and potentially significant fines. The reputational cost in a market as relationship-driven as Catalonia is often harder to recover than the technical one.

Vibe coding is not the enemy — unmanaged risk is

None of this means you should avoid AI-assisted development. It means you should treat every new application as an untrusted component until it has been reviewed. The same principle applies to the servers those applications run on. A vulnerable app is only one part of the attack surface; the infrastructure behind it is the other.

That is where centralised protection pays off. Abuse Shield, our managed security service, brings together automatic blocking of malicious IP addresses, managed fail2ban across multiple machines and a shared IP reputation feed between all your servers. When one machine detects an abusive source, the rest learn about it immediately. For hosting companies and SMEs running their own infrastructure in Lleida, Barcelona or anywhere else in Spain, that means fewer manual firewall rules, faster response times and a consistent security posture across every node.

Pair that with the five questions above and you have a practical routine: verify the software, then harden the platform it runs on. In a market where AI can produce an app in an afternoon, the discipline of asking hard questions is what separates a useful tool from an expensive incident.

Put these ideas into practice

Talk to ALMC about a solution for your business. Explore your options or contact our team.

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