As AI/ML adoption rises, addressing zero-day vulnerabilities in AI/ML systems is crucial. AI zero-days, exploiting unknown security flaws, pose unique risks in AI environments. Vulnerabilities in AI systems may include prompt injection or training data leakage, highlighting the importance of adapting traditional security best practices for AI
The current state of AI security lacks robust measures due to prioritizing speed and innovation over security. Security teams can tackle AI zero-days by integrating MLSecOps, conducting proactive security audits, and employing automated tools to scan for vulnerabilities. As AI evolves, security strategies must encompass AI-specific considerations to combat constantly evolving threats. The security community needs to refine best practices to effectively respond to the emerging challenges posed by AI zero-days. ```https://www.darkreading.com/vulnerabilities-threats/4-ways-address-zero-days-ai-ml-security