tomasphilippart / evil_charger

Evil Phone Charging Station

Evil Phone Charging Station

Codebase for Research Project 2 - Building an Evil Phone Charging Station. Author: Tomás Philippart

Attack and threat model/setup:

TODO:

• Make EasyOCR perform single character recognition, fine tune settings for it.
• Experiment with other OCR engines (doctr, Google Cloud Vision, etc.)

Installation:

Simply install the requirements necessary by running:

$ pip3 install -r requirements.txt

NOTE: All of the development was done on MacOS Ventura, I cannot confirm that all of the code is cross-platform.

Usage:

$ python3 main.py [--mode <usb, video>] --filename <FILENAME> [--framerate <FRAMERATE>, --mode <tesseract|easyocr|google_vision>, --keywords <x,y,z>]

Check .txt under /results folder for the processed text.

Examples

Using change_detect.py

$ python3 change_detect.py --frame_dir media/google_login-frames [--interactive] [--ocr {easyocr|tesseract}]

Use --interactive first to see how this program actually works. User input:

• "a": previous frame
• "d": next frame
• "q": quit
• " " (spacebar): for now nothing really, but will do something one day

Not using it simply prints out the OCR'd text of the character difference, without requiring user input.

Note that EasyOCR currently performs better than tesseract.

Capturing from a USB device (like in the attack and threat model setup)

$ python3 main.py --mode usb --filename HDMI_Capture --capture_time 15 --ocr_mode tesseract
Starting frame capture... Press CTRL+C to stop recording frames.
Converting frames to text using tesseract mode...
Writing results to results/HDMI_Capture.txt...
Done!

Converting pre-existing video (screen recording) to processed text

$ python3 main.py --mode video --filename media/instagram_login.mp4 --framerate 5 --ocr_mode tesseract
Converting video to frames: 100%|██████████████████████████████████████████████| 805/805 [00:26<00:00, 30.57frame/s]
Filtering duplicate frames: 100%|████████████████████████████████████████████| 805/805 [00:00<00:00, 1776.90frame/s]
Converting frames to text: 100%|███████████████████████████████████████████████| 515/515 [05:00<00:00,  1.71frame/s]
Results writen to results/instagram_login.txt.

Results

WIP!