Root Causes: A PKI and Security Podcast

Since frontier-model AIs have been trained on a large portion of published human knowledge, widespread publication of incorrect information can taint AI results. As more AI-generated slop finds its way onto the internet, this runs the risk of further poisoning AI results. This ultimately can result in completely unusable information.

It is possible to use common tools like OpenSSL to create your own ML-DSA private CA. This is a great tool for development and research projects, but Jason explains the pitfalls with trying to do this for production systems.

We are replacing RSA with the combination of ML-DSA and ML-KEM. We explain the naming convention and specifically what these two algorithms do.

Jason explains de-quantization, which is the practice of using our knowledge of how to use a quantum computer to reframe problems for processing using traditional computing architecture.

There is no CABF or root program rule preventing public CAs from implementing new requirements earlier than their assigned due dates. We discuss reasons to implement a rule early and how early it should be.