Remote Code Execution (RCE) is a significant cybersecurity threat that enables attackers to execute arbitrary code on a target system without prior access, potentially leading to full system compromise, data theft, and the spread of malware. The rise of interconnected devices has increased the risk of RCE attacks, which exploit software vulnerabilities like improper input validation and buffer overflows. High-profile vulnerabilities, such as Log4Shell, demonstrate the widespread impact and ease of exploitation that can affect millions of systems globally. Organizations are advised to adopt a multi-faceted approach to mitigate RCE risks, including regular software updates, secure coding practices, vulnerability scanning, and penetration testing. The integration of AI and Large Language Models (LLMs) in cybersecurity introduces both opportunities and vulnerabilities, with prompt injection attacks posing a particular threat to AI systems. Rigorous security measures, such as input validation and layered security architectures, are essential to protect against these threats. As AI technologies continue to evolve, the community must balance algorithmic accuracy with ethical considerations to ensure the safe and responsible deployment of AI systems.