Vibe coding, the practice of generating code via AI by relying on intuition rather than rigorous analysis, is appealing for its apparent speed. However, behind this ease lie three major structural vulnerabilities that can seriously compromise a project's viability: security vulnerabilities, lack of scalability, and degradation of code quality. These are not minor issues, but fundamental flaws that often transform a promising prototype into a technical nightmare. For a complete introduction to the topic, check out our article on vibe coding as a revolution or mirage.
1. Security Vulnerabilities
AI Replicates Past Mistakes
The artificial intelligence models used for vibe coding are trained on millions of lines of public code, particularly from GitHub. The fundamental problem is that this corpus contains an alarming proportion of vulnerable, obsolete, or poorly secured code. AI, lacking qualitative judgment capabilities, learns and reproduces these bad practices indiscriminately. To learn more about security risks and hidden costs, read our article on hidden costs and security risks of vibe coding.
SQL Injections and XSS: Classic Attacks That Return
One of the most common vulnerabilities generated by AI concerns SQL injections. Generated code often assembles queries by directly concatenating user input, without using parameterized queries or secure ORMs. A malicious user simply needs to enter a string like
'; DROP TABLE users; --Similarly, XSS (Cross-Site Scripting) attacks are frequent. AI often generates code that directly displays user data without escaping it, allowing malicious scripts to execute in other users' browsers.
Authentication and Authorization: Missing Controls
AI tends to generate API endpoints without implementing necessary authentication and authorization controls. Critical routes can thus be publicly exposed, allowing anyone to access, modify, or delete sensitive data. It's common to see generated APIs that accept all requests without verifying JWT tokens, sessions, or user roles.
Hardcoded Secrets and Key Management
A particularly dangerous practice that AI regularly reproduces is hardcoding secrets directly in source code. Passwords, API keys, access tokens: everything ends up in plain text in the Git repository, exposed to anyone with code access. These secrets can then be compromised if the repository is made public, even temporarily, or if a malicious collaborator gains access.
Vulnerable Dependencies and Supply Chain Attacks
AI often suggests integrating third-party libraries without verifying their security. The risk of library hallucination is particularly insidious: AI can invent the name of a package that doesn't exist. Malicious actors can then create and publish a malicious library under that name, knowing that unsuspecting developers will install it, creating a direct attack on the software supply chain.
Even when libraries exist, AI doesn't check if they contain known vulnerabilities (CVEs). Obsolete dependencies, unmaintained for years, can introduce critical flaws into the application.
To identify these vulnerabilities in your AI-generated code, use our free security audit that detects the most common vulnerabilities.
2. Scalability: An Invisible Wall Waiting
Unplanned Monolithic Architectures
Vibe coding naturally generates monolithic architectures, where all code is interconnected without clear separation of responsibilities. This approach works for a prototype with a few users, but quickly becomes a bottleneck when the application must handle load.
AI doesn't design distributed systems, microservices, message queues, or caches. It generates code that works "locally", without consideration for large-scale performance constraints.
Absence of Caching Strategy
A recurring problem is the complete absence of a caching strategy. Every request generates database calls, even for data that rarely changes. As the number of users increases, the database becomes a single point of failure, saturated by redundant queries.
AI doesn't generate Redis or Memcached caching mechanisms, no server-side HTTP cache, no CDN for static assets. The system is designed to function, not to perform.
Concurrency and Transaction Management
Applications generated by vibe coding handle concurrency problems poorly, if at all. Race conditions can occur when multiple users simultaneously modify the same data. The absence of locks or atomic transactions can lead to critical data inconsistencies.
Similarly, database transaction management is often absent or incorrect. Operations that should be atomic can be partially executed in case of error, leaving the system in an inconsistent state.
No Horizontal Scaling Plan
Generated code provides no strategy for horizontal scaling. It's designed to run on a single machine, with no possibility of replication or load distribution. When the application must handle more users, the only solution is to increase machine power (vertical scaling), a costly and limited approach.
The absence of load balancing, database replication, or geographic distribution makes the application vulnerable to traffic spikes and failures.
Need help making your application scalable? Contact us to discuss your project and scalability needs.
3. Code Quality: Progressive Degradation
Unmaintainable and Unreadable Code
Code generated by vibe coding is often functional but unreadable. Variable names are generic (data, result, temp), functions are too long and do too many things at once, comments are absent or useless. This opacity makes maintenance extremely difficult.
When a bug occurs, the developer must decipher code they didn't write, without documentation or tests. Resolution time explodes, and each correction becomes a risk of introducing new bugs.
Absence of Tests and Validation
AI rarely generates unit, integration, or end-to-end tests. Code is delivered "raw", with no guarantee it works correctly in all use cases. Edge cases aren't covered, errors aren't handled, and input validation is minimal or absent.
This absence of tests creates massive technical debt. Every modification becomes risky because there's no safety net to detect regressions. Code becomes progressively more fragile and harder to modify.
Duplication and Violation of SOLID Principles
Generated code systematically violates object-oriented programming principles. There's massive code duplication (DRY - Don't Repeat Yourself is ignored), responsibilities are mixed (violation of the Single Responsibility Principle), and dependencies are rigid (no dependency injection, no interfaces).
This structure makes code difficult to extend. Adding a new feature often requires modifying multiple places, creating a high risk of introducing bugs.
No Robust Error Handling
Error handling is generally minimal or absent. Exceptions are not caught, user errors are not handled gracefully, and logs are insufficient for debugging. When something fails, it's difficult to understand why and where.
This lack of robustness makes the application fragile. An unexpected error can crash the entire application, rather than being handled locally with an appropriate error message.
Is your AI-generated code suffering from quality issues? Contact us to migrate to maintainable, professional-quality code.
Conclusion: Vibe Coding Requires Expertise to Be Viable
The three major vulnerabilities of vibe coding – security, scalability, and quality – are not minor issues that can be fixed afterward. They are structural flaws that become deeply embedded in the code and become increasingly expensive to fix over time.
Vibe coding can be a powerful tool when used by experienced developers who understand these risks and refactor, secure, and optimize the generated code. But used "blindly", it produces applications that appear to work but are actually technical, financial, and security time bombs. If you're facing AI coding loops, discover how to break out of the infernal loop and regain control.
The solution is not to abandon these tools, but to migrate generated code to human, maintainable, secure, and scalable code. This is precisely AI2H's mission: transforming your AI code into professional-quality code that you fully master.