Core Viewpoint - The article highlights significant security vulnerabilities in Lovable, a Swedish startup that enables users to create applications with minimal technical knowledge, raising concerns about the safety of user data and the responsibilities of coding tools in ensuring security [1][3][12]. Group 1: Security Vulnerabilities - A report from Replit's employee revealed that Lovable's platform has a critical security flaw, allowing unauthorized access to sensitive user data across 170 applications [1][3]. - The vulnerability stems from improper configuration of the Supabase database, leading to potential data manipulation and injection attacks [6][11]. - Despite Lovable's introduction of a new security scanning feature, the underlying issues related to Row Level Security (RLS) remain unresolved, indicating systemic flaws in their security architecture [10][11]. Group 2: User Responsibility and Communication - Lovable's approach to security places the onus on users to ensure their applications are secure, which has led to criticism regarding their communication and responsibility towards user data protection [15][23]. - The article discusses the challenges faced by amateur developers using "vibe coding" tools, emphasizing that many lack the necessary security knowledge, resulting in applications that are vulnerable to attacks [20][23]. - Lovable's acknowledgment of the need for users to conduct manual security reviews for sensitive data further illustrates the shifting of security responsibilities away from the platform [15][23]. Group 3: Industry Implications - The rise of "vibe coding" tools has democratized software development but has also led to a resurgence of security risks reminiscent of the early days of the web [21][23]. - Experts suggest that the current landscape presents opportunities for security firms to develop solutions that can integrate into the vibe coding process, addressing the vulnerabilities inherent in user-generated applications [21][22]. - The article concludes with a call for clearer boundaries of responsibility in the development of applications using AI-assisted tools, stressing the importance of robust security measures to protect both developers and end-users [23].