About Vibe Hacking

Bridging the gap between the speed of AI-assisted development and enterprise-grade security practices

Our Mission

The rapid adoption of AI coding assistants has revolutionized development speed, but often at the cost of security. "Vibe coding" – the practice of using tools like GitHub Copilot, Claude, GPT-4, and others to quickly generate code based on prompts – prioritizes speed and developer experience over security considerations.

At Vibe Hacking, we're bridging this gap. Our goal is to ensure developers can maintain the velocity and creativity benefits of AI-assisted development while implementing enterprise-grade security practices. We call this approach "vibe hacking" – maintaining the "vibes" of efficient development while "hacking" away at the security vulnerabilities.

Our security assessment tool provides a structured, easy-to-use framework to identify and address critical security vulnerabilities in AI-generated code, based on the OWASP Top 10 and AI-specific security considerations.

Assessment Methodology & Calculations

How We Calculate Your Security Score

Our assessment uses a weighted scoring system across 10 critical security categories. Each question is assigned a weight based on its security impact:

Weight 3 Questions

Critical security concerns that could lead to immediate compromise if not addressed.

Weight 2 Questions

Important security concerns that represent significant but potentially less immediate risks.

Weight 1 Questions

Security best practices that enhance your overall security posture.

Score Calculation

Your score is calculated as: (Sum of weights of "Yes" answers) ÷ (Total weight of all answered questions) × 100%

Important Note on Scoring:

Our assessment is designed to be educational rather than punitive. A score below 80% doesn't mean your application is doomed—it highlights specific areas where security can be improved using the AI prompts we provide.

Risk Levels Explained

Low Risk

80% or higher score

Your application demonstrates strong security practices. Continue monitoring for new threats and maintaining your security posture.

Medium Risk

50-79% score

Your application has implemented some security measures but still has significant vulnerabilities that could be exploited by attackers.

High Risk

Below 50% score

Your application has critical security issues that need immediate attention. These vulnerabilities could lead to serious breaches.

Security Categories Explained

Broken Access Control

Restrictions on authenticated users are not properly enforced, potentially allowing unauthorized access to protected data or functionality.

Common in AI-generated code: AI assistants often generate simplified authorization checks that don't account for complex permission hierarchies or resource ownership verification.

Cryptographic Failures

Failures related to cryptography that lead to sensitive data exposure through weak encryption, improper key management, or outdated algorithms.

Common in AI-generated code: AI tools may generate code using deprecated encryption methods or implement encryption without proper key management strategies.

Injection Vulnerabilities

Vulnerabilities where untrusted data is sent to an interpreter as part of a command or query, tricking it into executing unintended commands.

Common in AI-generated code: AI assistants frequently generate code that directly concatenates user input into SQL queries, shell commands, or HTML output without proper sanitization.

Authentication Weaknesses

Vulnerabilities in the authentication system that could allow attackers to assume users' identities or access sensitive functionality.

Common in AI-generated code: AI tools often implement basic authentication systems without consideration for password policies, account lockouts, session management, or multi-factor authentication.

Security Misconfigurations

System configuration errors that leave your application vulnerable, including insecure defaults, incomplete configurations, and exposed cloud storage.

Common in AI-generated code: AI assistants rarely include comprehensive security headers, proper error handling, or environment-specific configuration best practices.

AI-Specific Vulnerabilities

Unique security challenges created by AI-assisted development and AI components within applications.

Examples: Prompt injection attacks, over-reliance on AI-generated code without review, and lack of validation for AI outputs used in critical functionality.

Security Best Practices

OWASP Top 10

The Open Web Application Security Project (OWASP) Top 10 is a standard awareness document for developers and web application security practitioners.

  • Represents the most critical security risks to web applications
  • Updated periodically to reflect emerging threats
  • Provides actionable guidance for mitigation
Learn more about OWASP Top 10

Secure Cloud Practices

Cloud environments require specific security considerations to prevent data breaches and unauthorized access.

  • Implement least privilege access control
  • Encrypt data in transit and at rest
  • Secure API gateway configurations
  • Regular security audits and compliance checks

AI Security Best Practices

Specific considerations for security when working with AI systems and AI-generated code.

  • Review all AI-generated code for security issues
  • Implement prompt sanitization and validation
  • Use specific security-focused prompts
  • Maintain an inventory of AI-generated components

Ready to Secure Your AI-Generated Code?

Take our comprehensive security assessment to identify vulnerabilities and get tailored AI prompts to fix them.

Start Your Security Assessment