ChatGPT’s Security Risks and Benefits: Offensive and Defensive Use-Cases, Mitigation Measures, and Future Implications

Abstract

ChatGPT has been acknowledged as a powerful tool that can radically boost productivity across a wide range of industries. It reveals potential in cybersecurity-related tasks such as social engineering. Nevertheless, this possibility raises important concerns regarding the thin line separating moral use of this technology from its harmful usage. It is imperative to address the challenges of distinguishing between legitimate and malevolent use of ChatGPT. This research paper investigates the many concerns of ChatGPT in cybersecurity, privacy and enterprise settings. It covers harmful attacker uses such as injecting malicious prompts, testing brute force attacks, preparing and developing ransomware attacks, etc. Defenders’ proactive activities are also addressed, highlighting ChatGPT’s significance in security operations and threat intelligence. These defensive operations are classified based on the National Institute of Standards and Technology cybersecurity framework. They involve analyzing configuration files, inquiring about authoritative server, improving security in various systems, etc. Moreover, secure enterprise practices and mitigations spread through five classes are proposed, with an emphasis on clear usage standards and guidelines establishment, personally identifiable information protection, adversarial attack prevention, watermarking generated content, etc. An integrated discussion digs into the interaction of offensive and defensive applications, covering ethical and practical concerns. Future attacks are also discussed, along with potential solutions such as content filtering and collaboration. Finally, a comparative analysis with recent research on ChatGPT security concerns is directed. The paper provides a thorough framework to comprehend the range of implications associated with ChatGPT, enabling the navigation of cybersecurity and privacy challenges.

Ähnliche Arbeiten