The research community is exploring innovative ways to leverage large language models (LLMs) for cybersecurity purposes. A recent study has demonstrated the potential of LLMs to identify vulnerabilities in real-world code. The study’s findings suggest that LLMs can be trained to detect flaws in software by analyzing vast amounts of code data. This approach represents a promising advancement in automated vulnerability detection, potentially leading to improved software security and reduced exploitation risks. This research indicates the potential of LLMs to play a crucial role in proactive vulnerability identification and mitigation, enhancing the security of software systems.