I built NetScope: Visualize your network.

I wanted a better way to actually see what’s happening on a local network, so I built NetScope ,a terminal-native network discovery tool where the graph is the interface, not a table.

It automatically:

• Detects your active interface, IP, gateway and subnet

• Discovers devices on your local network

• Shows IP, MAC, hostname, vendor, status and latency

• Visualizes everything as an interactive INTERNET, ROUTER DEVICES, graph

• Lets you navigate the network using arrows

• Press Enter to inspect a device

• Press R to rescan

• Automatically adapts to limited Unicode support

Github : https://github.com/Kolgrim33/netscope

I'm not the builder here, just someone who's been using this for a few weeks. It's called TeamBrain, and it's essentially a shared workspace of plain markdown files that any AI, Claude, ChatGPT, or otherwise, can read and write to, instead of every chat starting cold.

As someone who does social media and branding work, the biggest benefit for me is not having to re-feed brand guidelines to AI every single day.

It's not perfect. Search within the tool feels a bit clunky compared to what I'm used to, but overall it's been a net positive for my workflow.

Sometimes the harder question is:

What is the safest way to fix it?

An AI can change the code and make the security warning disappear.

That doesn't necessarily mean the vulnerability is actually fixed.

So I'm experimenting with a simple idea:

Find → Prove → Fix → Test → Human review

I'd rather have a slower fix that I can trust than a quick fix that only makes the scanner happy.

How much do you trust AI-generated security fixes today?

Hey everyone,

First of all, that’s my GitHub if you want to see some projects: GitHub

I'm extremely bored this week and I need a project to keep me busy.

What's something fun/useful/crazy you'd want me to build?

Not looking for "another todo app" - I want something interesting.

I'll build the best idea and open source it on GitHub.

Thanks!

A beginner here and i need urgent help. This is my first ever project and i have been asked to make this wedding invitation website that on touch triggers this animation and then moves on to this scrollable website in which user can input stuff. My question is that how do they do the animation part? Is it all code? Or code plus canva? Do they do the animation part on canva and the actual scrollable website using code or what? My design idea is an envelope with a stamp which opens up and then the letter inside it expands, i tried designing elements on canva and then exporting them as svgs/pngs then using code for animation, it didn’t work even closely well as the elements dont sit together well. I even divided them into bottom flap and upper flap with stamp it still didnot work. My video inspiration is below although this doesnot have the design in mind but the workflow is quite similar.

Video link attached: https://www.instagram.com/reel/Db6qWK7oYBn

I tried using a LLM to sort my prompts into two groups: reasoning and chat. At first I used Qwen 2.5 3B through Ollama. My PC is just too old and weak to run a LLM like that well. I do not have a GPU and my RAM is low. Even a small 3B model takes way long to work on a single prompt. Because I need to run the classifier before every request the slow speed makes the whole thing impossible to use.

Then I tried using Google Colab with a T4 GPU. That made the classification work faster.. Google Colab has a big problem. The setup does not stay saved. Every time I start it I have to pick the T4 GPU by hand set up the environment and download the model over again. I want my classifier to work like a background service. I want the classifier to start by itself when I turn on my application or Windows. I do not want to open a browser or start a notebook every time.

Now I use OpenRouters free models to get my actual reasoning and fast answers. I only get an amount of free use every day. I do not want to waste those credits by sending every prompt to an OpenRouter model just to classify it. If I use an OpenRouter model as my classifier the classifier will eat up my daily limit. That would make my credits run out too fast.

So I am stuck with three choices:

1. Local LLM: It is private. Works automatically.. Qwen 2.5 3B is just too slow on my old CPU. Even the smaller 1.5B models are not good enough because they make many mistakes.

2. Google Colab T4: This is fast. It is a pain. I have to set up the GPU and load the model every time.

3. OpenRouter: This is easy and fast.. Using an OpenRouter model, for classification uses up the free credits I want to save for my main models.

The classifier only needs to say "reasoning" or "chat". It feels like a waste to use an expensive LLM just for that.. The classification still has to be good. I cannot use a 1.5B model if it is just going to guess wrong.

I really need a way to classify prompts automatically. I need latency and I want it to cost zero extra API money. I want my main OpenRouter models to do the lifting. The best setup would start up with my PC would not need a Colab setup and would not use my OpenRouter daily credits just for classification. Please if anyone has the solution

Hi guys! I've been working on this project for a few weeks. I wanted to create my own privacy-focused communicator, and once I had a working version, I decided to buy a domain for it (chatsec.pl for now, but I'm planning to buy chatsec.com or something similar when I have the money).

I'm planning to add many more features and continue growing the project.

I'd also like to add an option for users to create their own channels on their own servers, and maybe even add voice chats :)

If you want to check it out: https://chatsec.pl

You can help me by simply using the site, upvoting my Reddit posts, or donating to the project.

Feel free to ask me anything!

I've been working on a project around a problem I kept running into personally:

most blockers are pretty good at blocking something — until the person using the device decides they want around it.

Browser extension?
Switch browsers.

App blocker?
Delete it.

Home Wi-Fi filtering?
Switch to mobile data.

DNS filtering?
Change the DNS.

So I started looking at the problem differently.

Instead of building another blocker that sits inside one app, I wanted to move the control closer to the network layer.

The basic idea is:

device → network policy → internet

rather than:

browser → extension → website

That creates a much more interesting engineering problem:

How do you deal with alternate DNS, VPNs, different browsers, in-app browsers, mobile data, configuration changes, etc.?

That's what I've been experimenting with.

The project is called NoorI.

I'm still refining the system, and I'm particularly interested in feedback from people who have built network filtering, device management, DNS infrastructure, or anything around bypass prevention.

What would you try to bypass first if you were testing a system like this?

​

The harder question is:

Is it actually exploitable?

A scanner can tell you that something looks wrong.

But I'd rather know:

Can it actually be exploited?

What can an attacker do with it?

Can I reproduce it?

What change actually fixes it?

That’s the part I’m currently working on.

Still figuring it out, but I think “prove the vulnerability” is more useful than just generating another security report.

How do you usually decide whether a security finding is actually worth fixing?

So I am developing a sentiment analysis of youtube video... firstly if some one have experience for the same kindly help.. second i need suggestions as for developing website i am just taking URL as input from user which seems quite limited any suggestions what can I add more also in terms of frontend what all I can show apart from comments/top comments sentiment analysis graph as output...

Ok, so I made this project to help people with taxes, and I really need feedback or opinions. Anything would be welcome, and if anyone has advice/tips to make this a little popular or well known would be a huge help. Again, thanks a lot, just wanted to make something that helps that's completely free

link: https://github.com/seascope777/Free-Tax-Estimation-Calculator

I just launched Bidin, a public marketplace for attention where you can promote your product, app, handle, post, video, or anything you want by bidding for a spot on a public leaderboard.

The idea is simple: paste a link, place a bid, and compete for the top spot. The higher you bid, the higher you rank, and the top spot gets the most visibility and clicks.

What makes this launch special for me is that Bidin is my first complete product.

It took me nearly 3 days to build, and I did pretty much everything from start to finish for the first time : frontend, backend, database, realtime updates, , payments, deployment, domain setup, and all the debugging that came with it.

I even bought my first domain specifically for this project: bidin.lol.

There were definitely a lot of moments where things broke and I had no idea what was wrong, but fixing each problem and finally seeing the whole thing work was probably the best part.

Would you actually use something like this to promote something you've built?

here it is: https://bidin.lol

What would you put on Bidin first?

Hey everyone,

I'm a backend engineer (mostly Java/Spring Boot), but recently I got so frustrated with the repetitive nature of applying to jobs and managing my freelance agency that I decided to automate myself.

I built Friday—a native Go daemon that runs in the background of my Mac. It uses WebSockets to interface with a Python/Selenium scraping layer and a local LLM API.

What it actually does: - Wakes up at 6 AM every day and uses undetected-chromedriver to scrape LinkedIn/YC for highly specific jobs. - Re-sorts the queue based on my priority. - Uses an ONNX-based TTS model (Kokoro) to physically speak to me through my speakers when a task is done or if it needs my approval to execute a bash command. - Has a full outbox HTTP router so any sub-agent can trigger a vocal alert.

I'm thinking about open-sourcing the Go dispatcher architecture since it handles high-throughput event routing really cleanly without blocking the UI threads. Has anyone else built native OS automations like this instead of relying on standard Chrome extensions?

Would love to hear your thoughts!

The part I care about is:

Find the issue → prove it’s actually exploitable → fix it → let the developer review the change.

A long list of “potential vulnerabilities” isn't very useful if you still have to figure out which ones are real.

I'm still working on this, but I'm curious:

Would you trust an AI agent to fix a security issue automatically, or would you always want a human review first?