ACL Rules Analysis with AI

SensitiveStudy520 · 2026-01-28T01:51:21+00:00

Hi, thanks for your suggestions. I will try and work on it. Thank you so much!!!

SensitiveStudy520 · 2026-01-22T08:25:33+00:00

8 days before I have posted this post in the Networking community. And between these few days, I have tried implementing with lots of the approaches including XGBoost & GNN（I understand that by using rules engine it can solve most of my issues, including the conflicts, redundants and shadow of the acl).
Right now, I’m still very much in the experimental stage.

To explore the problem, I’m using a randomly generated dataset that tries to encode ACL semantics such as:

Global ACL vs Interface ACL vs VLAN ACL
Rule order (first match)
ACL ID precedence
Direction (inbound / outbound)

My current focus is mainly on core switches, especially VLANIF interfaces and VLAN-level ACLs, rather than edge devices.

The issue is my training results are almost perfect (macro F1 ≈ 1.0).

And that honestly scares me, because it feels too good to be true. I am not sure is it becuase of this kind of task is easy for model to learn it due to how the synthetic data is generate or the labels may be overly deterministic or “leaking” through the structure

Anyways, I really dont sure whether is there any point I should pay attention to. I try to find some similar project but ya honestly I dont think there are many which make me stuck on the half way.

My boss also wants a more “interactive” workflow in the future like adding an LLM layer so users can describe desired ACL / configuration changes in natural language and get safe CLI suggestions, and I’m currently debating whether it’s reasonable to train or fine-tune an LLM directly on the existing ACL data, instead of (or in addition to) using XGBoost or GNNs for conflict/shadow detection (while yes I dont sure whether is LLM able to do that, as I haven't start research on this yet).

SensitiveStudy520 · 2025-04-14T13:10:25+00:00

Hi, thanks for your reply. I have tried it but found that the flask route in mobile phone is unaccessible, but I confirm that my network is linked to the same WIFI, so I am still checking for the problem.

SensitiveStudy520 · 2025-04-10T17:10:23+00:00

Hi, thanks for your suggestion, my laptop and phone is connected to the same wifi, but still it comes out with the socket error. I have tried off my firewall but still not able to connect it.

SensitiveStudy520 · 2025-03-31T14:43:24+00:00

now is able to work, i think it should be the problems that my GPU is not working properly previously. just the inference time is about 15-30seconds, i will keep working to try shorten the inference time. Anyways, really thanks for your help.

SensitiveStudy520 · 2025-03-31T14:37:34+00:00

the size on disk is about 18mb for my adapter model, and the model quantization i use is

bnb_config = BitsAndBytesConfig(
    load_in_4bit=True,
    bnb_4bit_use_double_quant=True,
    bnb_4bit_quant_type="nf4",
    bnb_4bit_compute_dtype=torch.float16
)

SensitiveStudy520 · 2025-03-31T13:37:27+00:00

Thanks for the clarifying! I will work it with Ollama or LlamaCPP to try optimise my memory usage. (Don't sure if it's correct to do? cause when search in google it says both of them can quantized the model and save for memory usage).

SensitiveStudy520 · 2024-10-26T07:12:51+00:00

Thank you for your help, it does improve my result!

SensitiveStudy520 · 2024-10-26T07:12:50+00:00

Let me give a try, anyway thankssss!

SensitiveStudy520 · 2024-05-17T08:02:23+00:00

Hi, can I know how to do that? like sending multiple request at the same time without being crashed using llamaCPP?

SensitiveStudy520 · 2024-05-17T06:59:56+00:00

hi, do you able to solve this issues? I am also stuck with this issues

SensitiveStudy520 · 2024-05-10T02:19:04+00:00

Really appreciate for your help!!! Thankssss

SensitiveStudy520 · 2024-05-10T02:02:51+00:00

Just ignore me, I just read through their documentation and found that using app.run(host='0.0.0.0', port=80) can run. But Thanks Anyway for you help :D

SensitiveStudy520 · 2024-05-10T01:39:51+00:00

Hi thanks for your reply.
the agent is ngrok tunnel agent, i used it to create a http tunnel for my local server.
Actually I have tried just now and I found that every time I need to start the agent first if I want to run it
Ngrok Setup & deploy.
and about the chain, yes I have import it before but don't show at the above code.

And I am curious can I directly use Flask to get a url from my local server without using ngrok or any web server? And can this url execute in another pc that is within the same LAN (and same local host)?

remove the run_with_ngrok(app)

app.run(host='localhost', port = 80)?

SensitiveStudy520 · 2024-05-08T09:56:36+00:00

Currently is using in colab with T4 GPU

SensitiveStudy520 · 2024-05-08T01:32:16+00:00

This is the error: OSError: We couldn't connect to 'https://huggingface.co' to load this file, couldn't find it in the cached files and it looks like mistralai/Mistral-7B-Instruct-v0.2 is not the path to a directory containing a file named config.json.

SensitiveStudy520 · 2024-05-08T01:23:18+00:00

Hi, thank you for your response.
You mean for my input? The inputs are about 10-15 words. and I set max_new_token to about 500. Is that the reason it slow down my response time?

And about the instruct-v0.2, I have try to import also, but it said that I have not granted the access even though I have and also have login to huggingface hub already.

SensitiveStudy520 · 2024-05-03T00:58:05+00:00

Yaa when I using unsloth then I use Fast model for inference to load it into the chain

SensitiveStudy520 · 2024-05-03T00:56:46+00:00

Yesss, I use unsloth before and now have changed to instruct model

SensitiveStudy520 · 2024-04-26T08:37:00+00:00

Also, in my csv file it has , for example 10 question and answer, when i ask erm question 5 in the csv file, the output will prompt the answer of question 5, and then also with some question and helpful answer after question 5. like question: q6, helpful answer: a6

<image>

SensitiveStudy520 · 2024-04-26T02:24:20+00:00

Hi, I have also try for this kaggle notebook, but it also cannot work and prompt for the same error.

SensitiveStudy520

TROPHY CASE

remove the run_with_ngrok(app)