ElastiFlow VS Installation

As a matter of fact, I played with the now deprecated Elastiflow, however I couldn't get my head around managing ELK, scrapped it pretty quickly, and Netflow did not reach the meaningful stage at that time. OpenNMS looks pretty massive that I can't run it at the moment. Thanks for suggestion though.

One thing I ran for a while was security onion and utilized port mirroring to mirror the uplink port from my primary switch to my LAN on my router, so I was catching anything coming into/out of my network destined for internet. I've also used ElastiFlow ( https://github.com/robcowart/elastiflow ) which is absolutely phenomenal and awesome, I did the same and it provides some great data. You could also leverage IntelOwl ( https://github.com/intelowlproject/IntelOwl ) , one thing I have added to all my VMs is a OSSEC agent, Wazuh to be specific which is free ( https://github.com/wazuh/wazuh ) and while I am not using it to its full potential such as monitoring file deletions/modifications etc it is a powerful tool.

I'd recommend taking a look at Elastiflow (link is to the legacy version, I haven't used the pay structured tier version that replaced it) as a flow collector. Do it in a docker container, dump netflow to it, and use a sample rate that doesn't fill your collector box with flow packets after a single day. Depends on your traffic rates. We use 1 out of 250 for our rate.

https://github.com/robcowart/elastiflow/issues/201 https://github.com/robcowart/elastiflow/issues/52

Where as the newer version is (https://github.com/robcowart/elastiflow/) is called:

"The site" is actually just their blog. The github repo at https://github.com/netbox-community/netbox is more like the real homepage and has a good presentation.

Sweet! If it ends up anything like Netbox it will be so sweet. By looking at the screenshots I am very excited to see this implemented!

NetBox Release v3.6.6 is now live (as of November 29, 2023)!

Take a look at netbox. https://netbox.dev/

Pre-trained systems dominate AI today (as deep as the P in GPT). My team and I have been researching and building alternatives given how the hallucination, blackbox and other problems don't seem solvable within* the current paradigm.

One of our first applications is a network automation solution for Netbox-- locally trained AI Agents unique to each Netbox account to predict roles of newly added devices given the current local list of devices, like a context-aware autocomplete.

Agents are lightweight by design, this particular Netbox Agent is 40-neuron, and when hooked up demo.netbox.dev and consistently gets 80%+ accuracy predicting device roles even when trained on ~60 devices only.

Try it out: https://aolabs-netbox.streamlit.app/

You can use dummy data from demo.netbox.dev. More on Netbox: https://github.com/netbox-community/netbox

We'd keen for feedback, if this is useful, how we could extend it if it is, or if it sparks other application ideas.

* Somebody has to be the pre-trainer, leaving an irreducible gap of misunderstanding between AI and its application which we are trying to diminish by adding a layer of local training.

Before upgrading, please: 1. Verify in release notes changelog if any new breaking changes might affect you. You can also review the NetBox Issues on GitHub to see if any new issues have arisen that might affect you. 2. Next, refer to the Upgrading to a new NetBox Release guide for steps to upgrade your instance.

I've been looking into some projects for some opensource software i use and noticed a few of them have empty __init__.py files (for example https://github.com/netbox-community/netbox/blob/develop/netbox/core/__init__.py)

IT wise, It's been a fair few years since I've been in a department that does asset management, we used to use GLPI with it's warts and all, which got replace with https://github.com/netbox-community/netbox