When looking for sensitive information and other valuable assets, attackers rarely access their target directly. Instead, they find vulnerabilities in other components and use them to weave through the system and escalate privileges where they can. Because containers add a layer of complexity to already large and complex applications, the attack surface is increased, giving threat actors more to work with.

Just a few weeks ago, we wrote about how the National Vulnerability Database (NVD) is seriously behind in enriching CVEs. On LinkedIn, Mastodon, and other social sites, the NVD’s mounting backlog and what should be done about it has become a hot topic of conversation within the cybersecurity community.

Published in 2023, the OWASP Top 10 for LLM Applications is a monumental effort made possible by a large number of experts in the fields of AI, cybersecurity, cloud technology, and beyond. OWASP contributors came up with over 40 distinct threats and then voted and refined their list down to the ten most important vulnerabilities.

The risk both to and from AI models is a topic so hot it’s left the confines of security conferences and now dominates the headlines of major news sites. Indeed, the deluge of frightening hypotheticals can make AI feel like we are navigating an entirely new frontier with no compass. And to be sure, AI poses a lot of unique challenges to security, but remember: Both the media and AI companies have a vested interest in upping the fright hype to keep people talking.