The Genesis and Definition of Vibe Coding
Vibe coding is an AI-dependent programming technique where developers describe what they want in natural language, and AI tools (typically large language models) generate the actual code. The term was introduced by Andrej Karpathy, co-founder of OpenAI and former Tesla AI leader, in February 2025.
In his viral post, Karpathy described this approach as "not really coding - I just see things, say things, run things, and copy-paste things, and it mostly works".
This approach represents a paradigm shift from traditional programming, where developers write code manually, to a model where developers act as guides, testers, and refiners of AI-generated code.
The concept elaborates on Karpathy's 2023 claim that "the hottest new programming language is English," suggesting that humans would increasingly use natural language rather than specialized programming languages to instruct computers.
What Makes Something "Vibe Coding"?
A key aspect of vibe coding is the developer's relationship with the code. As AI researcher Simon Willison noted, "If an LLM wrote every line of your code, but you've reviewed, tested, and understood it all, that's not vibe coding in my book—that's using an LLM as a typing assistant".
True vibe coding involves accepting code without full understanding, prioritizing speed and creativity over technical precision.
How Vibe Coding Differs from Traditional Coding
The contrast between vibe coding and traditional programming approaches is stark across multiple dimensions:
| Aspect | Traditional Coding | Vibe Coding |
|---|---|---|
| Skill Level Required | High – Requires coding expertise | Lower – AI assists with code generation |
| Speed | Slower – Developers write everything manually | Faster – AI automates code writing |
| Flexibility | Full control, but requires deep knowledge | Easier to iterate, but depends on AI's accuracy |
| Use Cases | Complex, custom-built applications | Rapid prototyping, automation, and simple software solutions |
| Cost | Higher – Requires skilled developers | Lower – Reduces development time and resources |
As the comparison shows, traditional coding offers precision and control but at the cost of speed and accessibility, while vibe coding dramatically accelerates development but introduces potential quality and security concerns.
Critical Security Vulnerabilities in Vibe Coding
Despite its advantages, vibe coding introduces significant security concerns that demand attention. For organizations offering security audits to vibe coding teams, understanding these vulnerabilities is essential:
AI-Generated Vulnerabilities
AI can produce insecure code that leaves applications exposed to cyber threats. The most common issues include:
- Logical errors that developers miss since they didn't write the code themselves
- Security vulnerabilities arising from AI not thinking "adversarially" like hackers would
- Common web vulnerabilities such as SQL injection, XSS, and CSRF in AI-generated code
- Unverified dependencies that might contain known security vulnerabilities
- Hardcoded credentials exposing sensitive information in the codebase
- Non-compliant code that doesn't follow industry best practices or regulatory requirements
Lack of Explainability
Developers might not fully understand the logic behind AI-generated code, making debugging and security assessments difficult.
This knowledge gap becomes particularly problematic when security issues arise.
Legal and Regulatory Issues
Compliance with security and privacy laws becomes complicated when code is generated autonomously, creating potential liability issues for organizations.
VibeCured's Security Testing Capabilities for Vibe Coding
Static Analysis Security Testing
Our static analysis examines source code repositories for security vulnerabilities, including:
-
Code-Level Vulnerabilities
- Insecure coding patterns and anti-patterns
- Hardcoded credentials and secrets
- Buffer overflows and memory safety issues
- Path traversal vulnerabilities
- Input validation weaknesses
-
Dependency Analysis
- Vulnerable third-party libraries and packages
- Outdated dependencies with known CVEs
- Supply chain security risks
-
Code Quality Issues
- Resource leaks
- Race conditions
- Deadlock scenarios
- Improper error handling
-
Configuration Weaknesses
- Insecure default configurations
- Environment-specific security issues
- Permissions and access control misconfigurations
Dynamic Analysis Security Testing
Our dynamic analysis tests live websites and applications for runtime vulnerabilities:
-
Injection Vulnerabilities
- SQL injection
- Command injection
- LDAP injection
- NoSQL injection
-
Cross-Site Vulnerabilities
- Cross-Site Scripting (XSS)
- Cross-Site Request Forgery (CSRF)
- Cross-Origin Resource Sharing (CORS) misconfigurations
-
Authentication and Session Management
- Broken authentication flows
- Session fixation
- Insecure session handling
-
Web Infrastructure Security
- Missing or misconfigured security headers
- SSL/TLS issues and certificate problems
- Insecure cookies
- Content Security Policy weaknesses
- HTTP security directives
-
Information Exposure
- Sensitive data exposure
- Directory listing
- Information leakage in error messages
- Server information disclosure
Conclusion
Vibe coding represents a seismic shift in software development, offering unprecedented speed and accessibility while introducing new security challenges. For organizations and developers embracing this approach, balancing innovation with security is paramount.
By understanding what vibe coding is, how it works, and the security implications it presents, teams can harness its power while mitigating risks.
Implementing robust security practices—from code reviews to automated testing—ensures that the benefits of vibe coding don't come at the expense of security and reliability.
As vibe coding continues to evolve, those who can navigate its potential and pitfalls will be best positioned to leverage this revolutionary approach to software development.
For security professionals, this emerging field offers new opportunities to provide value through specialized security audits and risk mitigation strategies tailored to the unique characteristics of AI-generated code.