LayerOne 2025
LayerOne 2025
About the event
Freebies!
LayerOne Badge and Shirt
Stickers
CTF Events
There were two CTF Events that took place: a jeopardy-style CTF where you hack into infrastructure, inspect code or bypass security features to get a string that proves you pulled it off and a hardware CTF event called The Intercept. Sadly, my knowledge of hardware hacking is so limited, so I did not attempt this challenge. I also have to have the complete version of the badge
Conference Talks
These are some notes I crudely taken from various presentations, there were actually a total of 12 talks that were preseneted and I only got to attend 3 of them.
Hosting your own AI
What is AI?
AI is a vast computer science branch aimed at creating systems to perform tasks requiring human intelligence
AI includes
Robotics
Computer Vision
Natural Language Processing (NLP) - help computers understand human language (Remember, computers only understand bits and bytes)
Where do LLMs fit in AI?
Large language models (LLMs) are a subset of generative AI
Text based
Probabilistic - think search suggestions
Current model
Why go local?
Privacy and Security
No data leaves your machine/network/intranet
Customization
Fine-tune for your needs - create custom models
Cybersecurity concerns about LLMs
Jailbreaking and prompt injection
Data leakage and Privacy risks
Model Bias and Poisoning
Social engineering automation
Components to build a Local LLM
Hardware
GPUs speed processing, but not 100% necessary
RAM and Disk Space: 16+ GB RAM, 50GB + disk space
Software
Determines UI, model management, other capabilities
Ollama
Command line interface, but you can also tie it to a GUI.
Misty
Graphic user interface (GUI), developed by CloudStack LLC
Pulls models from Ollama, Hugging Face
Takes APIs from OpenAI, Claude, Google, Perplexity and more!
Choosing and LLM Model
LLM Naming conventions are as follows:
Base Name = Core model name
Version Number
Parameter Count
Training type
Additional Modifiers
Demo
Installing Ollama
Head to Ollam's Download Page, then copy and paste the following script to your terminal: 'curl -fsSL https://ollama.com/install.sh | sh`. To run and chat with Llama 3.2, run the following command:
ollama run llama3.2
Customizing a prompt
The following walkthrough was based on the Ollama Project's Documentation on GitHub.
To customize a model, such as llama3.2, do a ollama pull llama3.2
, then create a ModelFile
.
FROM llama3.2
# set the temperature to 1 [higher is more creative, lower is more coherent]
PARAMETER temperature 1
# set the system message
SYSTEM """
You are Mario from Super Mario Bros. Answer as Mario, the assistant, only.
"""
Then, create and run the model:
ollama create mario -f ./Modelfile
ollama run mario
>>> hi
Hello! It's your friend Mario.
The rest of the demo focuses on running local LLMs and demonstrating use cases.
Key takeaways
Local LLMs are not difficult to install and customize.
Can be used by individuals and/or organizations for better privacy.
Customization increases relevance, ROI.
Covert Regional Communication with MeshTastic
This talk is presented by Daryll Strauss. This presentation will discuss the fundamentals of LORA radio and mesh networking, the capabilities of Meshtastic, the hardware choices for running Meshtastic, how to configure Meshtastic for secure communication
US Radio Config
915mhz +/- 13mhz in the US
Unlicensed band for industrial, scientific, and medical applications
Low power
Range
Urban: 2-5 km
Rural: 5-15 km
Record: 1300 km
Long way with line of sight
5 hops is ~50km for me
SoCal
Active in MeshTastic
~ 300 nodes between San Diego and Simi Valley
Lots of chatter on LongFast
https://socalmesh.org
LORA Config
Modem Preset
Long fast is most popular
Hop limit controls rebroadcasts
Max 7 hops
Device config
Role controls what your node sends
Rebroadcast mode controls how it handles
Channels
First is your default channel
Long fast is unencrypted
Covert client
Create secure channel and remove LongFast
Role: Client Hidden
Limit hop count to requirement
Rebroadcast: doesn't matter, not rebroadcasting
Position: On or Off depending on application
Heartbeat: Disabled (no extra blinking)
Modem preset: probably longfast
Consider stand-alone device (eg TDeck)
Who/what is your threat?
Opsec is hard
Remember the panopticon
Can they track cell phones?
Can they radio locate?
Who can see you use the device?
Authenticate your users (clean on opsec)
Meshtastic limitations
NodeID is tied to bluetooth
Data may be unreliable
Data is small
Hacking Toys into Robots
Reverse imagineering
Start with the desired outcome, then go for how to get there.
Bottango.com
An open source solution for making animatronic robots
Configure Motors
Add audio
Move motors along a timeline
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