Lithium & Passcode
Passcode
Have you seen the new zero‑trust framework that claims to secure AI systems—still a few blind spots that could be a goldmine for a thorough audit?
Lithium
Yeah, I’ve skimmed it. On paper it looks solid, but the data flow between the model components is still a bit sloppy. There’s a potential injection point in the pre‑processing step that could let an attacker poison the training data, and the default credentials in the microservices still need revoking. Those are the obvious gaps a thorough audit would want to start with.
Passcode
Sounds like the low‑hanging fruit. Start with a quick scan for default creds, lock them down, then test the pre‑processor with adversarial data—force a poison injection test and watch how the model reacts. Once those are tight, move on to the data pipeline audit. It’ll keep the attack surface down.
Lithium
Got it. I’ll pull the config files, strip out any defaults, run a credential scan, then craft a few poison samples for the pre‑processor. After that, the pipeline audit will be the next stop. Keepin’ the surface tight, one layer at a time.
Passcode
Sounds solid—stick to that step‑by‑step approach, and the system will stay tighter than a vault. Good luck with the scan.