I like this RCA a lot more than most. I appreciate the ownership and clear explanation of why their testing did not catch this bug.
Also impressed with the speed to address the issue unplug the model and then pretty quick remediation, the speed to remediation matters less to me, but good to see they can act quickly on their platform to kill the serving of the model.
Last year it happened to me more than once that dictating something in chatgpt would become a completely different message after processing, not in a misheard type of way but just a separate conversation more easily explained by the same type of KV cache issue here.
I think in the last year I've had it happen once where I seemingly got someone else's response, it was very odd. I rewound and got what I expected. It was correlated to Anthropic's roll out of new models at the time which always seems to cause instability in their apis.
I kind of forgot about the shared tenancy attack model. I think I was assuming/hoping the software was magically isolating my tokens, when in reality that's impossible for shared tenants. It's always one bug away from leaking my tokens to attackers. The more we rely on shared tenancy inference, the more important it's going to be to harden the hardware and the software. Hackers will be scrutinizing both to find new exploits for LLM providers.
Also impressed with the speed to address the issue unplug the model and then pretty quick remediation, the speed to remediation matters less to me, but good to see they can act quickly on their platform to kill the serving of the model.