A brief history of oral peptides
14 by odedfalik | 6 comments on Hacker News.
Tuesday, 10 February 2026
New top story on Hacker News: Show HN: HN Companion – web app that enhances the experience of reading HN
Show HN: HN Companion – web app that enhances the experience of reading HN
8 by georgeck | 2 comments on Hacker News.
HN is all about the rich discussions. We wanted to take the HN experience one step further - to bring the familiar keyboard-first navigation, find interesting viewpoints in the threads and get a gist of long threads so that we can decide which rabbit holes to explore. So we built HN Companion a year ago, and have been refining it ever since. Try it: https://ift.tt/ifeLckB or available as an extension for Firefox / Chrome: [0]. Most AI summarization strips the voices from conversations by flattening threads into a wall of text. This kills the joy of reading HN discussions. Instead, HN Companion works differently - it understands the thread hierarchy, the voting patterns and contrasting viewpoints - everything that makes HN interesting. Think of it like clustering related discussions across multiple hierarchies into a group and surfacing the comments that represent each cluster. It keeps the verbatim text with backlinks so that you never lose context and can continue the conversation from that point. Here is how the summarization works under the hood [1]. We first built this as an open source browser extension. But soon we learned that people hesitate to install it. So we built the same experience as a web app with all the features. This helped people see how it works, and use it on mobile too (in the browser or as PWA). This is now a playground to try new features before taking them to the browser extension. We did a Show HN a year ago [2] and we have added these features based on user feedback: * cached summaries - summaries are generated and cached on our servers. This improved the speed significantly. You still have the option to use your own API key or use local models through Ollama. * our system prompt is available in the Settings page of the extension. You can customize it as you wish. * sort the posts in the feed pages (/home, /show etc.) based on points, comments, time or the default sorting order. * We tried fine tuning an open weights model to summarize, but learned that with a good system prompt and user prompt, the frontier models deliver results of similar quality. So we didn’t use the fine-tuned model, but you can run them locally. The browser extension does not track any usage or analytics. The code is open source[3]. We want to continue to improve HN Companion, specifically add features like following an author, notes about an author, draft posts etc. See it in action for a post here https://ift.tt/Io4YL8K We would love to get your feedback on what would make this more useful for your HN reading. [0] https://ift.tt/EekIqS2 [1] https://ift.tt/B5cJygp [2] https://ift.tt/oqa04ZV [3] https://ift.tt/IaUozRk
8 by georgeck | 2 comments on Hacker News.
HN is all about the rich discussions. We wanted to take the HN experience one step further - to bring the familiar keyboard-first navigation, find interesting viewpoints in the threads and get a gist of long threads so that we can decide which rabbit holes to explore. So we built HN Companion a year ago, and have been refining it ever since. Try it: https://ift.tt/ifeLckB or available as an extension for Firefox / Chrome: [0]. Most AI summarization strips the voices from conversations by flattening threads into a wall of text. This kills the joy of reading HN discussions. Instead, HN Companion works differently - it understands the thread hierarchy, the voting patterns and contrasting viewpoints - everything that makes HN interesting. Think of it like clustering related discussions across multiple hierarchies into a group and surfacing the comments that represent each cluster. It keeps the verbatim text with backlinks so that you never lose context and can continue the conversation from that point. Here is how the summarization works under the hood [1]. We first built this as an open source browser extension. But soon we learned that people hesitate to install it. So we built the same experience as a web app with all the features. This helped people see how it works, and use it on mobile too (in the browser or as PWA). This is now a playground to try new features before taking them to the browser extension. We did a Show HN a year ago [2] and we have added these features based on user feedback: * cached summaries - summaries are generated and cached on our servers. This improved the speed significantly. You still have the option to use your own API key or use local models through Ollama. * our system prompt is available in the Settings page of the extension. You can customize it as you wish. * sort the posts in the feed pages (/home, /show etc.) based on points, comments, time or the default sorting order. * We tried fine tuning an open weights model to summarize, but learned that with a good system prompt and user prompt, the frontier models deliver results of similar quality. So we didn’t use the fine-tuned model, but you can run them locally. The browser extension does not track any usage or analytics. The code is open source[3]. We want to continue to improve HN Companion, specifically add features like following an author, notes about an author, draft posts etc. See it in action for a post here https://ift.tt/Io4YL8K We would love to get your feedback on what would make this more useful for your HN reading. [0] https://ift.tt/EekIqS2 [1] https://ift.tt/B5cJygp [2] https://ift.tt/oqa04ZV [3] https://ift.tt/IaUozRk
Monday, 9 February 2026
Sunday, 8 February 2026
Saturday, 7 February 2026
Friday, 6 February 2026
New top story on Hacker News: Show HN: Daily-updated database of malicious browser extensions
Show HN: Daily-updated database of malicious browser extensions
7 by toborrm9 | 3 comments on Hacker News.
Hey HN, I built an automated system that tracks malicious Chrome/Edge extensions daily. The database updates automatically by monitoring chrome-stats for removed extensions and scanning security blogs. Currently tracking 1000+ known malicious extensions with extension IDs, names, and dates. I'm working on detection tools (GUI + CLI) to scan locally installed extensions against this database, but wanted to share the raw data first since maintained threat intelligence lists like this are hard to find. The automation runs 24/7 and pushes updates to GitHub. Free to use for research, integration into security tools, or whatever you need. Happy to answer questions about the scraping approach or data collection methods.
7 by toborrm9 | 3 comments on Hacker News.
Hey HN, I built an automated system that tracks malicious Chrome/Edge extensions daily. The database updates automatically by monitoring chrome-stats for removed extensions and scanning security blogs. Currently tracking 1000+ known malicious extensions with extension IDs, names, and dates. I'm working on detection tools (GUI + CLI) to scan locally installed extensions against this database, but wanted to share the raw data first since maintained threat intelligence lists like this are hard to find. The automation runs 24/7 and pushes updates to GitHub. Free to use for research, integration into security tools, or whatever you need. Happy to answer questions about the scraping approach or data collection methods.
Thursday, 5 February 2026
Wednesday, 4 February 2026
Tuesday, 3 February 2026
New top story on Hacker News: Show HN: PII-Shield – Log Sanitization Sidecar with JSON Integrity (Go, Entropy)
Show HN: PII-Shield – Log Sanitization Sidecar with JSON Integrity (Go, Entropy)
5 by aragoss | 0 comments on Hacker News.
What PII-Shield does: It's a K8s sidecar (or CLI tool) that pipes application logs, detects secrets using Shannon entropy (catching unknown keys like "sk-live-..." without predefined patterns), and redacts them deterministically using HMAC. Why deterministic? So that "pass123" always hashes to the same "[HIDDEN:a1b2c]", allowing QA/Devs to correlate errors without seeing the raw data. Key features: 1. JSON Integrity: It parses JSON, sanitizes values, and rebuilds it. It guarantees valid JSON output for your SIEM (ELK/Datadog). 2. Entropy Detection: Uses context-aware entropy analysis to catch high-randomness strings. 3. Fail-Open: Designed as a transparent pipe wrapper to preserve app uptime. The project is open-source (Apache 2.0). Repo: https://ift.tt/7GJU65M Docs: https://pii-shield.gitbook.io/docs/ I'd love your feedback on the entropy/threshold logic!
5 by aragoss | 0 comments on Hacker News.
What PII-Shield does: It's a K8s sidecar (or CLI tool) that pipes application logs, detects secrets using Shannon entropy (catching unknown keys like "sk-live-..." without predefined patterns), and redacts them deterministically using HMAC. Why deterministic? So that "pass123" always hashes to the same "[HIDDEN:a1b2c]", allowing QA/Devs to correlate errors without seeing the raw data. Key features: 1. JSON Integrity: It parses JSON, sanitizes values, and rebuilds it. It guarantees valid JSON output for your SIEM (ELK/Datadog). 2. Entropy Detection: Uses context-aware entropy analysis to catch high-randomness strings. 3. Fail-Open: Designed as a transparent pipe wrapper to preserve app uptime. The project is open-source (Apache 2.0). Repo: https://ift.tt/7GJU65M Docs: https://pii-shield.gitbook.io/docs/ I'd love your feedback on the entropy/threshold logic!
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