Weedout
Find risky dependencies before they reach production
What it does
Weedout watches your dependency manifests and only tells you about vulnerabilities that are actually exploited in the wild or actually reachable in what you ship.
Weedout turns vulnerable dependency data into a clear project security queue, prioritised by exploit and reachability signals instead of raw CVE volume.
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Does a similar job
all alternatives →- MUMost users won't report bugs unless you make it stupidly easy2025 · ▲335
Most feedback tools are built like people actually want to report bugs. They don’t. Unless you make it dead-simple, or better yet - a little fun. After shipping a few SaaS products, I noticed a pattern: Bugs? Yes. Bug reports? No. Not because users didn’t care but because reporting bugs is usually a terrible experience. Most tools want users to: * Fill out a long form * Enter their email * Describe a bug they barely understand * Maybe sign in or create an account * Then maybe submit it Let’s be real: no one’s doing that. Especially not someone just trying to use your product. So I built…

- NFNotifications for security vulnerabilities in your dependencies2014 · vuln.pub · ▲10



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OpenTrailPaper is open-source bike computer firmware for the LilyGO T5S3 4.7" E-Paper PRO. It supports offline maps, GPX routes, FIT recording and Bluetooth sensors.
Dev tools · 2d ago · opentrailpaper.com

Open-source GTM skills for technical founders
Dev tools · 30d ago · gtmcofounder.com

Launched alongside, August 2026
the whole month →- TL
Life & fun · 11d ago · louisabraham.github.io



Hello HN! I found that picking out plausible but diverse skin tones for my digital art and game development projects was kind of difficult, and I got curious about if there was a way to define a color space that made it easy. I've built a color picker and procedural generation algorithm based on the space as well as a bunch of other fun js features and demos throughout the page that use the equations. If you find it interesting, I have lots of explanations of how I built it and what properties the space has. The methodology might be a bit shaky, but hopefully the result is as helpful for…
Life & fun · Aug 2026 · toneyalexander.github.io


I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
AI · 17d ago · simedw.com