OpenEntropy
47 hardware entropy sources from your computer's physics
Get picks like this daily. Today's launch numbers, the top launches, AI and tech news, and a daily opportunity pick, straight to your inbox.
Want to reach these readers? Sponsor an issue.
I built this to study something most security engineers wave off: whether external factors can nudge hardware entropy sources.Here is why. Princeton’s PEAR lab ran RNG work for about 28 years and shut down in February 2007. People in the lab tried to shift random event generator output, and they reported small deviations after tens of millions of events. https://www.pear-lab.com/The Global Consciousness Project took a similar idea outside the lab. It has run a distributed network of hardware RNGs since 1998 and looks for correlated deviations around major world events.Most people looking at hardware entropy want true randomness for crypto. I want to treat entropy like a sensor. I want to see what might perturb the underlying noise, not just consume a final stream.So I built OpenEntropy. It samples 47 physical-ish sources on Apple Silicon, like clock jitter, thermal beats, DRAM timing conflicts, cache contention, and speculation timing. Raw mode gives you unprocessed, per-source bytes so you can run your own stats on each channel.The PEAR-style question is: does output shift when “intention” is the experimental condition? With 47 sources, I can run intention vs control sessions and ask if multiple unrelated channels drift the same way at the same time. If thermal and DRAM timing both shift during intention blocks, that’s the kind of pattern I want to measure.
HN · launched Feb 17, 2026 · 6 upvotes (top 72%) · 0 views
Niche: encryption and cryptography tools · 147 launches, 21 in the last 7 days ▲ +40% · Explore this niche →
Category and tags
- Horizontal
- Data infrastructure
- Developer
- Not AI
- Hobby / open-source project
Visit website ↗ Source listing ↗
More like this: all 147 launches in encryption and cryptography tools →
Could you build this?
No Harvesting and validating 47 distinct hardware-level entropy sources from physical processor and bus jitter requires deep low-level systems programming, hardware timing analysis, and rigorous statistical cryptographic verification.
What it would actually take: This platform requires low-level C/Rust or kernel-adjacent code interacting directly with CPU instructions (e.g., RDTSC, RDRAND), cache misses, memory bus contention, thread scheduling jitter, and physical hardware sensors. The system must implement statistical validation suites such as NIST SP 800-22 and Dieharder to assess random number distribution and eliminate bias. Developing it demands specialized knowledge in computer architecture, hardware physics, and cryptographic randomness testing.
Discussion
No comments on this launch.
Competitors
Other products that read as similar to this one : 99 launches clear the similarity bar, closest 8 shown.
Attention rank: #78 of 100 (itself plus its competitors, highest first, normalized so YC and Product Hunt are compared fairly).
Launched 101 days after the earliest competitor.
- Does Information Density Cause Time Dilation? · hn · 2025-12-24 · 10 upvotes · similarity 0.46
- I built a hardware quantum RNG and wired it into a Magic 8-Ball · hn · 2026-06-26 · 13 upvotes · similarity 0.43
- Open-source distributed quantum compute network · hn · 2026-04-02 · 11 upvotes · similarity 0.42
- daosfun-source · github · 2026-10-24 · 32 upvotes · similarity 0.41
- Double blind entropy using Drand for verifiably fair randomness · hn · 2026-02-12 · 21 upvotes · similarity 0.41
- Qthermo · github · 2026-09-11 · 42 upvotes · similarity 0.39
- Fixing optical computing jitter via fluid dynamics in GPU registers · hn · 2026-08-09 · 6 upvotes · similarity 0.38
- Cuts Long Horizon Inference Costs by 50% via external KV Cache Offload · hn · 2026-07-26 · 22 upvotes · similarity 0.38
The niche, labels, vibe code rating and competitor comparison on this page are analysis by Nicheloom. If you use them, please credit nicheloom.com. How you may use our data.