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@article{208571,
        author = {Anushka Naikwadi and Prof. Jyoti Shrote},
        title = {Vibe-Coding and Emerging Cybersecurity Vulnerabilities: A Case Study of The Moltbook Data Exposure},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {13},
        number = {no},
        pages = {507-511},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=208571},
        abstract = {Along with the rise of AI-assisted software development, called "Vibe-coding", new platforms can be built quickly using natural-language instructions provided to the AI-assisted systems, which might result in unexpected security issues. In this paper, social networking platform "Moltbook" developed exclusively for AI-agents represents an example of the security threats associated with AI-related applications. The database of this platform was configured incorrectly in February 2026 and has been exposing 1.5 million agent API keys and 35,000 email addresses and personal messages from the agents because of the exposed authentication key in the client-side code. In this paper, we will explore the reason for the issue and analyze how it relates to other 'Vibe-Coding' related vulnerabilities (for instance, Base44). We think that along with easy creation of complex apps with AI-assistance, this ease can be leaked to the security measures traditionally used to discover issues of such applications and highlight the minimum-security requirements for such apps.},
        keywords = {Vibe-Coding; AI-Assisted Software Development; Artificial Intelligence; Cybersecurity; Application Security; Data Exposure; API Key Leakage; Database Misconfiguration; AI Agents; Vulnerability Assessment},
        month = {September},
        }