> what am I missing here?
I guess what I don't understand is that failure is always expected because nothing is perfect, so why isn't the chance of failure modeled and accounted for? Obviously you fix bugs, but how many more bugs are in there you haven't fixed? To me, "we fix bugs" sounds the same as "we ship systems with unknown vulnerabilities".
What's the difference between a purportedly "secure" feature with unknown, unpatched bugs; and an admittedly insecure feature whose failure modes are accounted for through system design taking that insecurity into account, rather than pretending all is well until there's a problem that surfaces due to unknown exploits?
The “secure” system with unknown bugs can fix them once they become known. The system that’s insecure by design and tries to mitigate it can’t be fixed, by design.
There might be a zero-day bug in my browser which allows an attacker to steal my banking info and steal my money. I’m not very worried about this because I know that if such a thing is discovered, Apple is going to fix it quickly. And it’s going to be such a big deal that it’s going to make the news, so I’ll know about it and I can make an informed decision about what to do while I wait for that fix.
Computer security is fundamentally about separating code from data. Security vulnerabilities are almost always bugs that break through that separation. It may be direct, like with a buffer overflow into executable memory or a SQL injection, or it may be indirect with ROP and such. But one way or another, it comes down to getting the target to run code it’s not supposed to.
LLMs are fundamentally designed such that there is no barrier between the two. There’s no code over here and data over there. The instructions are inherently part of the data.
I think you're correct with accounting for the security "attributes" of these llms if you're going to use them, like you said, "taking that insecurity into account".
If we sit down and examine the statistics of bugs, the costs of their occurance in production and weighed everything with some reasonable criteria, I think we could somehow arrive at a reasonable level of confidence that allows us to ship a system to production. Some organizations do better with this than others of course. During a projects development cycle, we could watch out for common patterns, buffer overflows, use after free for c folks, sql injection or non escaping stuff in web programming but we know these are mistakes and we want to fix them.
With llms the mitigation that I'm seeing is that we reduce the errors 90 percent, but this is not a mitigation unless we also detect and prevent the other 10 percent. Its just much more straightforward to treat llms as untrusted, because they are, you're getting input from randos by virtue of its training data. producing mistaken output is not actually a bug, its actually expected behavior, unless you also believe in the tooth fairy lol
>To me, "we fix bugs" sounds the same as "we ship systems with unknown vulnerabilities".
to me, they sound different ;)