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API to Detect Prompt Injection

Hacker News

API to Detect Prompt Injection

Let me preface this by linking to simonw’s latest prompt injection blog post. [0] Geiger does not solve prompt injection, but it is biased towards false positives and the false positive rate can be curtailed by experimenting with the `task` parameter. It is a stop-gap measure that‘s meant to be used right now for services that are exposing the LLM to untrusted potentially-poisoned post-GPT information such as raw web searches. The injection test set I use is as wide as all public injections. There‘s some secret ingredient as well but it‘s not anything groundbreaking and it can be replicated independently with enough effort. This is as simple as possible. There’s as little JavaScript as possible on the website to prevent abuse and there’s no JavaScript at all in the app. Payments are handled by Stripe. Try it out and let me know what you think. Do get in touch if you find it doesn’t work for you or if you need anything specific. [0] https://simonwillison.net/2023/May/2/prompt-injection-explai...

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Indie HackersFits the IH revenue-focused audience · Strong signals: para · Missing: supports, reddit linkedin, podcasting
81%81% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Product HuntOn track for Day 1 leaderboard · Strong signals: stripe · Missing: mac, agents, macos
80%80% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: para · Missing: mobile apps, ios, personal
42%42% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released
39%39% 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 · Missing: plus, platform, intuitive
39%39% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
16%16% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

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