ChatGPT, a generative AI tool, can speed up development workflows and boost productivity, but its security and quality of generated code aren't guaranteed. While some developers believe AI-generated code is more secure than human-written code, this isn't always the case. In fact, ChatGPT's output is entirely reliant on training data and prompt engineering, making it insecure from the start if vulnerabilities or mistakes exist in the training data. Developers should assume that any AI-generated code is insecure and take steps to remediate vulnerabilities before deployment. The reliability of ChatGPT-generated code depends on the task it performs and the underlying training data, and nearly 80% of developers admit to bypassing security measures as they believe AI-generated code is "secure enough." To ensure secure coding practices, other security safeguards should exist within a developer's workflow, such as comprehensive security tools and measures. Using large language models like ChatGPT raises significant data security concerns, and companies should assume that no data within GenAI is secure. A dedicated security analysis tool like Snyk Code can help mitigate these risks by integrating seamlessly into a developer's workflow and scanning code in real time for vulnerabilities.