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CipherStash Stack – Data Level Access Control in TS/JS

Hacker News

CipherStash Stack – Data Level Access Control in TS/JS

Hi HN, I'm Dan Draper, founder of CipherStash. We've spent 5 years building per-value searchable encryption tech. We realized that encryption like this is incredibly powerful but the engineering required is generally not worth the effort. So we built a platform and opensource SDK to take the cry out of cryptography :) CipherStash Stack is: * A searchable encryption SDK for TS and Postgres * Fast, key management with Zerokms (backed by HSM) * A transparent SQL proxy * Auth library and OIDC federation service * Skills for data security Integrations include Prisma Next, Drizzle, Auth0, Clerk and Supabase. Install and setup is done via a single npx stash init command. And can handoff implementation to your agent. You can start by encrypting just a single field and we've got the whole process down to around 15 minutes. Oh and its fast: most queries run in a few ms with many faster than that. We published our full benchmarks here: https://github.com/cipherstash/benches#headline-numbers I'd love to know what you think!

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Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: agent, single, open · Missing: mac, agents, macos
82%82% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
81%81% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released
59%59% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoMay struggle as an AppSumo deal · Strong signals: platform · Missing: plus, intuitive, reviews
41%41% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
37%37% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
14%14% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: crypto · Missing: web3, chat, cryptocurrency
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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