Tim Arnold
independent developer/hacker/trainer
Apex, North Carolina, United States
Actions
Tim is a retired software developer, Python programmer, and statistician who co-authored the 2nd edition of *Black Hat Python*. These days he spends his time building security tools, breaking things for fun, and teaching others how to do the same. When not sniffing LoRa packets in the wild, he's writing Python code that probably shouldn't exist.
Area of Expertise
Topics
I Know What You LoRa'd Last Summer: Introducing LoRecon
Meshtastic, Helium, and LoRaWAN have quietly built massive mesh networks across cities, often using default encryption keys that offer little more than security theater. This talk introduces an open-source ESP32-based passive reconnaissance tool that scans 26 LoRa configurations, captures packets, and automatically decrypts traffic using 23 known default PSKs.
We'll walk through building a budget friendly Heltec WiFi LoRa 32 V3 into a field-deployable sniffer with:
- Real-time packet capture with interrupt-driven reception
- Multi-protocol detection (Meshtastic, LoRaWAN/TTN, Helium Network)
- Automated PSK testing against default keys, including "AQ==" and legacy admin keys
- GPS coordinate extraction from position broadcasts
- Mobile-friendly web UI with threat-level network visualization
- PCAP export compatible with Wireshark
Live demo: We plan to power up the sniffer at CackalackyCon and see what's transmitting in in the nearby area, possibly discovering Meshtastic nodes, IoT sensors, and devices broadcasting with default encryption.
Key takeaways:
1. Why default PSKs in consumer mesh networks are a research goldmine
2. How to identify vulnerable devices using RSSI and traffic patterns
3. Defense strategies: key rotation, firmware updates, network segmentation
4. Ethics of passive RF reconnaissance (receive-only, legal framework)
All code is MIT-licensed open source. Attendees leave with a shopping list, flash instructions, and the knowledge to build their own reconnaissance platform tonight.
No prior LoRa experience required, just curiosity about what's transmitting around you.
Your AI, Your Way: Creating a Custom and Private Hacking Assistant
Abstract:
This talk shows you how to build your own local hacking assistant using uncensored large language models (LLMs, e.g. ChatGPT).
We'll build custom Retrieval Augmented Generation system (RAG) from 100 local PDFs about hacking, whip up an interactive app running locally and you'll walk away with skills.
Mainstream LLMs are useful, but they're also neutered. As a hacker it would be nice to get some AI hacking help without restrictions.
That's where uncensored LLMs come in.
We'll take a hands-on approach, showing you:
Local LLMs: Running them yourself (and why you'd want to).
RAG: Giving your LLM a brain (and a library).
Chainlit: Making it all interactive.
Demos:
OpenAI with RAG (the baseline).
Local LLM with RAG (taking control).
Uncensored LLM on RunPod (the real deal.
Building Your Own RAG: From PDF to interactive app in minutes.
Outline:
Intro: Terms, current state of LLMs for hacking
The Toolkit: Local LLMs, RAG, Chainlit
Demos: Building Unrestricted Assistants
DIY RAG: From PDF to App
Wrap-up and Q&A
Tim Arnold
independent developer/hacker/trainer
Apex, North Carolina, United States
Actions
Please note that Sessionize is not responsible for the accuracy or validity of the data provided by speakers. If you suspect this profile to be fake or spam, please let us know.
Jump to top