Executive Summary AI applications rely on vector embeddings to power search and recommendations, but these data-rich vectors introduce new security and privacy risks. This blog explains the main threats to AI embeddings, how attacks can occur, and proven strategies for protecting vector data with MySQL—covering secure storage, access controls, encryption, auditing, and compliance best practices. […]

I was talking with a client and the topic of password crypting came up. From my background as a C coder, I have a few criteria to regard a mechanism to be safe. In this case we’ll just discuss things from the perspective of secure storage, and validation in an application.

1. use a digital fingerprint algorithm, not a hash or CRC. A hash is by nature lossy (generates evenly distributed duplicates) and a CRC is intended to identify bit errors in transmitted data, not compare potentially different data.
2. Store/use all of the fingerprint, not just part (otherwise it’s lossy again).
3. SHA1 and its siblings are not ideal for this purpose, but ok. MD5 and that family of “message digests” has been proven flawed long ago, they can be “freaked” to create a desired outcome. Thus, it is possible to …