DALL-E for coders? That's the promise behind vibe coding, a term describing the use of natural language to create software. While this ushers in a new era of AI-generated code, it introduces "silent killer" vulnerabilities: exploitable flaws that evade traditional security tools despite perfect test performance. A detailed analysis of secure vibe coding practices is available here. TL;DR: Secure Vibe Coding Vibe coding, using natural language to generate software with AI, is revolutionizing development in 2025. But while it accelerates prototyping and democratizes coding, it also introduces "silent killer" vulnerabilities: exploitable flaws that pass tests but evade traditional security tools. This article explores: Real-world examples of AI-generated code in production Shocking stats: 40% higher secret exposure in AI-assisted repos Why LLMs omit security unless explicitly prompted Secure prompting techniques and tool comparisons (GPT-4, Claude, Cursor, etc.) Regulatory pressure from the EU AI Act A practical workflow for secure AI-assisted development Bottom line: AI can write code, but it won't secure it unless you ask, and even then, you still need to verify. Speed without security is just fast failure. Introduction Vibe coding has exploded in 2025. Coined by Andrej Karpathy, it's the idea that anyone can describe what they want and get functional code back from large language models. In Karpathy's words, vibe coding is about "giving in to the vibes, embrace…Read More