Santandersecurityresearch/CurrentSense-TinyML
Spying on Microcontrollers using Current Sensing and embedded TinyML models
This project helps security researchers understand the behavior of microcontrollers by analyzing their electrical current draw. By monitoring power fluctuations, it can detect specific operations, like an LED flashing, on a target circuit board. It takes raw current data as input and produces insights into the target device's actions, which is useful for reverse engineering or security analysis.
No commits in the last 6 months.
Use this if you need to non-invasively observe the internal operations of a microcontroller for security analysis or reverse engineering without direct code access.
Not ideal if you need to analyze software-level application behavior or if you don't have access to specialized hardware for current sensing and embedded machine learning.
Stars
84
Forks
7
Language
C++
License
MIT
Category
Last pushed
Mar 23, 2021
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/Santandersecurityresearch/CurrentSense-TinyML"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
pytorch/executorch
On-device AI across mobile, embedded and edge for PyTorch
catalyst-team/catalyst
Accelerated deep learning R&D
z-mahmud22/Dlib_Windows_Python3.x
Dlib compiled binaries (.whl) for Python 3.7-3.14 and Windows x64
mit-han-lab/mcunet
[NeurIPS 2020] MCUNet: Tiny Deep Learning on IoT Devices; [NeurIPS 2021] MCUNetV2:...
gigwegbe/tinyml-papers-and-projects
This is a list of interesting papers and projects about TinyML.