The rapid evolution of generative AI is spurring interest in finding ways to prevent these technologies from creating more bad than good. This is a key concern in cybersecurity as organizations wrestle with the role GenAI might play in creating or supporting a security breach.
One way to combat such attacks is to establish a cybersecurity policy that includes AI. Let’s discuss some key security issues GenAI presents and examine what to include in a generative AI security policy.
How does AI affect cybersecurity measures?
AI, and GenAI in particular, introduces a number of cybersecurity risks. Cyberadversaries use GenAI to craft convincing social engineering and phishing scams, including deepfakes. Organizations unable to manage AI-associated risks open themselves to data loss, system access by unauthorized users, and malware and ransomware attacks, among others.
GenAI is also subject to prompt injection attacks, where malicious actors use specially crafted input to bypass a large language model’s normal restrictions, and data poisoning attacks, in which attackers alter or corrupt the data training an LLM.
Organizations must also be aware of other challenges related to GenAI,…
