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jaithree
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reacted to RiverRider's post with 🔥 about 3 hours ago
Black Window — a chat model in your browser tab, on your hardware. A memory that stays on the device that opened the page.
https://blackwindow.xyz
Open the site, pick a model (about 0.6B to 8B), hit Load. The weights run in that tab, on that computer. After they load, the network can drop. The context window is a working set, auto-sized to that device, up to ~32K tokens.
Behind the window is the Weave. Every file, picture, recording, link, lookup, and reply is embedded as it arrives. Drop in audio and it is transcribed. Drop in an image and it is described. A question pulls the nearest passages back as notes. A long document is walked once so later questions can use the whole file, not the first pages.
Nothing leaves that tab unless you turn on live lookup or connect a rented GPU box, and the chat says so each time. Prompts can go to the box. Files and the Weave stay in the tab.
Console on that page: bw.ask, bw.search, bw.digest, bw.notes. A local relay exposes /v1/chat/completions on localhost so other tools on the same computer can talk to the tab. The tab polls the relay. That is the boundary.
Not a server with a policy. Your hardware, a window, a Load button.
If on mobile add to home-screen for best performance. If you break it lmk. It can serve a few hundred of you at a time before I have to buy a real server. reacted to tegridydev's post with 🔥 3 days ago
What can you actually build with a cybersecurity dataset?
I've been updating a few of mine on Hugging Face, and they now cover some pretty different parts of the security workflow.
- open malsec has 1,104 defensive security scenarios across 20 subsets covering phishing, malware, scams, cloud security, API security, AI security and more
- opensec triage has 50,000 contextual alert examples, plus compact model and edge training sets for testing whether models classify from the evidence around an event
- infosec tool output has 1,004 examples across 19 tools for turning raw security output into evidence backed explanations, limitations and defensive next steps
You could use them for:
* phishing and scam explainers
* alert triage tools
* SOC assistants
* scanner output explainers
* analyst training
* model comparisons
* grounding and hallucination tests
* small specialised security models
* edge and local model experiments
Or combine them into something like:
scenario → evidence → triage → explanation → next action
You also don't need to train anything straight away.
Grab a few examples, run them through whatever model you already use and see where it gets confused :)
Datasets:
https://huggingface.co/datasets/tegridydev/open-malsec
https://huggingface.co/datasets/tegridydev/opensec-triage
https://huggingface.co/datasets/tegridydev/infosec-tool-output
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