## 1 Introduction
#### Research Hypothesis and Objectives  
This manuscript focuses on the study of the prevalence and effects of vulnerabilities with self-generative tools in software development, which are particularly relevant for industrial applications where reliability and safety are crucial. Industrial environments often rely on software to monitor complex processes, machinery, and systems [15]. Software failures can have serious consequences--including workplace accidents, production disruptions, and financial losses--highlighting the importance of software security. LLMs represent a paradigm shift in code generation, offering efficient and automated code creation capabilities. The selection of LLMs as the focal point of this study is justified, due to its increasing adoption in various fields, including industry. For this reason, the approach followed in this work involves the review of a case study related to an LLM. By examining a vulnerability associated with a self-generated tool, this work aims to provide valuable information for engineers tasked with implementing control and monitoring systems in industrial environments, thereby contributing to greater reliability and security in industrial applications. In this regard, the present manuscript proposes the term \"self-generative vulnerability\", to characterize scenarios where AI-based tools can facilitate the automatic creation of security weaknesses, as evidenced in the methodology and experimentation carried out. Specifically, the implications included in this study cover a security vulnerability related to SQL injection attacks. While the notion of AI-generated code having security issues may not be ground-breaking in itself, the novelty of this manuscript lies in its practical demonstration of how such vulnerabilities manifest, particularly through the provided case study involving the MySQL and PHP code generated by ChatGPT. The research goes beyond simply identifying security issues and provides detailed information on how these issues can arise in real-world scenarios. It provides specific recommendations to address these concerns, including training programs, error analysis, responsible practices, tool integration, software development audits, regulation and legislation, and collaboration with third parties. \begin{table}
\begin{tabular}{l l l l l} \hline \hline
**Provider** & **Tool** & **LLM** & **Data Size** & **Availability** & **Year** \\ \hline OpenAI (San Francisco, CA, USA) & ChatGPT-3 & Transformer & 100 terabytes & Public & 2020 \\ Tabnine (Tel Aviv, Israel) & Tabnine & CodeDaVinci & 25 petabytes & Public & 2022 \\ GitHub (San Francisco, CA, USA) & Copilot & Transformer & 100 petabytes & Public & 2022 \\ Microsoft and NVIDIA (Santa Clara, CA, USA) & Megaton & Turing NLG & 1.75 exabytes & Limited & 2022 \\ Microsoft AI (Redmond, WA, USA) & DeepCoder & Transformer- & 1.2 exabytes & Public & 2022 \\ Codesmith Software (Los Angeles, CA, USA) & ([[https://www.codesmith.io/](https://www.codesmith.io/)]([https://www.codesmith.io/](https://www.codesmith.io/))) & LaMDA & 1.2 exabytes & Public & 2023 \\ Meta (Menlo Park, CA, USA) & Code Llama & Llama & 1.5 exabytes & Public & 2023 \\ Google AI (Mountain View, CA, USA) & Bard/Gemini & LaMDA & 1.56 exabytes & Public & 2023 \\ GotHub and Google AI & Codex & Transformer & 1.6 exabytes & Public & 2023 \\  & ([[https://openai.com/blog/openai-codex](https://openai.com/blog/openai-codex)]([https://openai.com/blog/openai-codex](https://openai.com/blog/openai-codex))) & Transformer & 1.6 exabytes & Public & 2023 \\ OpenAI & ChatGPT-4 & Transformer & 45 terabytes & Public & 2023 \\ OpenAI & ChatGPT-4.5 & Transformer & 75 terabytes & Beta & 2023 \\ DeepMind & AlphaCode & Transformer & 100 exabytes & Beta & 2023 \\ (London, UK) & ([[https://alphacode.deepmind.com/](https://alphacode.deepmind.com/)]([https://alphacode.deepmind.com/](https://alphacode.deepmind.com/))) & Transformer & 1.2 exabytes & Beta & 2024 \\ Microsoft AI & Ada & Transformer & 1.2 exabytes & & \\ \hline \hline \end{tabular}
\end{table}