Congratulations @0xPolygon with your 6 years anniversary, up to the next trillions!
And thanks for the nice gift from https://t.co/tgvXodR20D
P.S. Whatever you do, don't ask your LLM to search for an easter egg
It's not the end, it's still living on in the LLM data training sets. That's why you see so many zero-address check suggestions and inflated severities. (My feeling is that it has improved with recent models though?)
The very early 2021 days with @0xRajeev@gpersoon@sockdrawermoney were peak fun.
What ruined contests from an SR's POV was:
Fewer real bugs because devs and tooling got a lot better, once foundry came along devs started actually testing their code with high coverage. This led to more (arguably) out-of-scope bug submissions which made the highest-impact move arguing about your own & others' issues. The difference between a high and a medium was not well defined in practice & there were some incompetent judges (sorry). Pool sizes also never kept up with the increase in participants.
In the end, the audit contest payout structure changed so much that many were just pre-deployment bug bounties (different pool size unlocks for H/M).
Ironically, now would be a great time for contests again as everyone is boasting about their AI being the best. Would love to see more real results instead of vagueposting.
Cool idea. Why not use the exact bounty amount as liquidity? That removes the uncertainty if the white hat pays back the 90%. And that is the amount that the protocol should reserve anyway.
prompt injection is social engineering for software.
we've long given up trying to harden humans. instead we built systems that assume people will be fooled.
we haven't done this for LLMs. not really.
here's why and how we can close the gap:
Cool idea by @sockdrawermoney : Label data, enforce policies to manage AI security & prompt injections. See https://t.co/6LCidT0xcC https://t.co/AMAK2ofJOh
I've spent every day for the last 14 months building a language for scripting LLMs because I believe we need new primitives to defend against prompt injection.
Here's why:
https://t.co/6EKVdbb1jt
@thedaofund There is a lot of reinventing the same thing. This could potentially be improved with more generic modules / libraries, which are well tested and reviewed.