A phone number can reveal whether a device is active, in standby or offline (and more). This PoC demonstrates how delivery receipts + RTT timing leak sensitive device-activity patterns. (WhatsApp / Signal)
## Overview
If you're concerned about privacy and the potential vulnerabilities in messaging applications, you'll find the Careless Whisper project particularly intriguing. This tool highlights the significant privacy risks associated with popular platforms like WhatsApp and Signal by measuring the Round-Trip Time (RTT) of message delivery receipts. The insights gathered can reveal a lot about user activity, device status, and even location changes, making this a powerful demonstration of how surveillance could be conducted through seemingly harmless messaging features.
Furthermore, the implementation revolves around a well-researched paper, which adds credibility to the findings and emphasizes the need for robust privacy safeguards in our digital communications. The web interface for tracking device activity presents a user-friendly approach to understanding these risks while showcasing the technology behind it.
## Features
- **Real-Time Monitoring**: The tool provides live RTT measurements that allow you to determine whether a device is actively in use, in standby, or offline.
- **User Activity Detection**: By measuring RTT, the application can differentiate between low latency when the device is in use and higher latency when it's idle, revealing user behavior patterns.
- **Location Change Insights**: The tool can detect whether the device is on a mobile data connection or WiFi, which can indicate when a user changes location.
- **Web Interface**: A user-friendly web interface allows easy interaction with the tool, including real-time tracking of device activity and state detection.
- **Flexible Probe Methods**: Users can switch between different probe methods (send a "delete" request or a reaction emoji), allowing for adaptability based on user needs or preferences.
- **Continuous Median Updating**: The tool adapts to different network conditions by continuously updating the median RTT, improving detection accuracy over time.