SnoopR updated version (2.0.1) brings exciting new features, including mesh networking for collaborative wardriving, aircraft tracking for aerial monitoring, and performance optimizations for smoother operation.
SnoopR updated version (2.0.1) brings exciting new features, including mesh networking for collaborative wardriving, aircraft tracking for aerial monitoring, and performance optimizations for smoother operation.
Aggressively capture handshakes with two modes: Tactical (smart and efficient) and Maniac(unrestricted, rapid attacks). Enhanced with client scoring, adaptive attacks, ML-based channel hopping, intelligent retries, and resource management.
A plugin that fetches aircraft data from an API using GPS coordinates, logs it, prunes old entries, and provides a webhook with aircraft type and origin country visualization.
This updated version (2.0.0) brings a host of new features, including richer data collection, smarter snooper detection, whitelisting, automatic data pruning, and an improved web interface.
This updated version (2.0.0) brings a host of new features, including richer data collection, smarter snooper detection, whitelisting, automatic data pruning, and an improved web interface.
An enhanced plugin with frequent titles, dynamic quotes, progress bars, random events, handshake streaks, personality evolution, and secret achievements. The UI is optimized to avoid clutter, ensuring a clean and engaging experience.
An enhanced plugin with frequent titles, dynamic quotes, progress bars, random events, handshake streaks, personality evolution, and secret achievements. UI is also optimized to avoid clutter.
Neurolyzer 1.5.2 elevates Pwnagotchi’s stealth and privacy with advanced WIDS/WIPS evasion, hardware-aware operations, realistic MAC generation, and flexible modes. Compared to earlier versions, it offers superior reliability (via retries and error handling), deeper stealth (traffic throttling, probe sanitization), and better usability (enhanced UI and logging). Whether you’re testing security or keeping a low profile, Neurolyzer 1.5.2 is a significant upgrade—more versatile, stealthy, and robust than ever.
Key Features (Enhanced from v1.1.2)
ProbeNpwn v1.1.3 builds on the solid foundation of v1.1.2, enhancing these core features:
Efficient Attacks: Launch both simultaneously for maximum handshake potential.
Concurrent Attack Threads: Handle multiple networks and clients with multi-threading.
Dynamic Attack Tuning: Adjusts delays and aggression based on signal strength and performance.
Whitelist Support: Exclude specific networks or clients from attacks via config.toml.
Comprehensive Logging: Detailed logs track every attack and capture.
Watchdog Recovery: Monitors and restarts Pwnagotchi if the Wi-Fi interface fails.
Lightweight Integration: Seamlessly works with your existing Pwnagotchi setup.
Real-Time UI Feedback: Displays attack counts and successes on your Pwnagotchi screen.
New Enhancements in v2.0.3:
Documented Training Logic:
In on_epoch, a comment explains why train_epochs increments every 10 epochs: # Increment train_epochs every 10 epochs to simulate slower training progress.
Enhanced File I/O Safety:
In on_handshake, handshake logging is wrapped in a try-except block to handle file writing errors gracefully.
Refined Decay Mechanics:
In apply_decay, decay calculation uses floating-point division for smoother, more proportional point reduction.
Increased Logging:
Added debug and info logs for better transparency:
on_epoch: Logs epoch number and points (logging.debug).
check_achievements: Logs new titles (logging.info).
apply_decay: Logs points lost due to decay (logging.info).
on_handshake: Logs captured handshake details (logging.info).
Thread Safety:
Imported threading and added a data_lock in __init__. Used in save_data to ensure thread-safe file writing.
Accurate Achievement Notifications:
Tracks previous titles and stars to ensure new achievements are detected and announced correctly.
Robust Handshake Handling:
Adds type checking and error logging to prevent crashes from unexpected data, making the plugin more stable.
Seamless New Installations:
Fully initializes all attributes when starting fresh, improving reliability for new users.
Persistent Progress:
Saves achievement states to the data file, maintaining continuity across sessions.
New Enhancements in v2.0.3:
Documented Training Logic:
In on_epoch, a comment explains why train_epochs increments every 10 epochs: # Increment train_epochs every 10 epochs to simulate slower training progress.
Enhanced File I/O Safety:
In on_handshake, handshake logging is wrapped in a try-except block to handle file writing errors gracefully.
Refined Decay Mechanics:
In apply_decay, decay calculation uses floating-point division for smoother, more proportional point reduction.
Increased Logging:
Added debug and info logs for better transparency:
on_epoch: Logs epoch number and points (logging.debug).
check_achievements: Logs new titles (logging.info).
apply_decay: Logs points lost due to decay (logging.info).
on_handshake: Logs captured handshake details (logging.info).
Thread Safety:
Imported threading and added a data_lock in __init__. Used in save_data to ensure thread-safe file writing.
Accurate Achievement Notifications:
Tracks previous titles and stars to ensure new achievements are detected and announced correctly.
Robust Handshake Handling:
Adds type checking and error logging to prevent crashes from unexpected data, making the plugin more stable.
Seamless New Installations:
Fully initializes all attributes when starting fresh, improving reliability for new users.
Persistent Progress:
Saves achievement states to the data file, maintaining continuity across sessions.
Probenpwn improvements.
move toml reading by standard function on_config_changed()
removed unnecessary _agent and _ui => Those variables were already availables
properly exit watchdog loop (_watchdog_thread_running + join) => The plugin was waiting for the never coming threads end.
retrieve debug log path from config => Cleaner if this files is moved in conf for some reason (new version, new plateform, etc.)
simplify name changing => pwnagotchi's name is in main.name retrieved in on_config_changed() and the old one could mess the displayed name is another plugin wanted to change it.
remove sudo to restart as pwnagotchi is already root
shoutout to fmatray
Realistic MAC Address Generation
Improvement: The updated version uses a more realistic MAC address by incorporating an OUI (Organizationally Unique Identifier) and randomizing the last three bytes within a restricted range.
Flexible Randomization Interval
Improvement: The randomization interval is now flexible, varying between 30 minutes and 2 hours. Randomizing the interval adds unpredictability, making the MAC address changes harder to detect. This increases stealth.
Improved MAC Randomization for Monitor Mode
Improvement: When the Wi-Fi interface is in monitor mode, the plugin temporarily switches to managed mode to change the MAC address and restores monitor mode afterward.
Updated UI Handling
Improvement: The UI is now updated more effectively by directly modifying the value attribute of the UI components in on_ui_update().
Better Error Handling and Logging
Improvement: The plugin now has enhanced error handling for subprocess calls, such as bringing the interface down or changing the MAC address. More detailed logs are provided for different stages.
Initial MAC Address Randomization
Improvement: The plugin now performs an initial MAC address randomization when it is loaded (self.randomize_mac() in on_loaded()). This ensures that the device's MAC address is randomized as soon as the plugin starts, providing enhanced privacy from the start.
Time-Dependent MAC Randomization
Improvement: The next MAC address change time is now dynamically calculated based on the random interval. This ensures the MAC address change schedule follows the random interval, making it harder to predict.
1. Realistic MAC Address Generation
Improvement: The updated version uses a more realistic MAC address by incorporating an OUI (Organizationally Unique Identifier) and randomizing the last three bytes within a restricted range.
2. Flexible Randomization Interval
Improvement: The randomization interval is now flexible, varying between 30 minutes and 2 hours. Randomizing the interval adds unpredictability, making the MAC address changes harder to detect. This increases stealth.
3. Improved MAC Randomization for Monitor Mode
Improvement: When the Wi-Fi interface is in monitor mode, the plugin temporarily switches to managed mode to change the MAC address and restores monitor mode afterward.
4. Updated UI Handling
Improvement: The UI is now updated more effectively by directly modifying the value attribute of the UI components in on_ui_update().
5. Better Error Handling and Logging
Improvement: The plugin now has enhanced error handling for subprocess calls, such as bringing the interface down or changing the MAC address. More detailed logs are provided for different stages.
6. Initial MAC Address Randomization
Improvement: The plugin now performs an initial MAC address randomization when it is loaded (self.randomize_mac() in on_loaded()). This ensures that the device's MAC address is randomized as soon as the plugin starts, providing enhanced privacy from the start.
7. Time-Dependent MAC Randomization
Improvement: The next MAC address change time is now dynamically calculated based on the random interval. This ensures the MAC address change schedule follows the random interval, making it harder to predict.
Dynamic Attack Strategy: The plugin now adjusts the aggressiveness of its attacks based on real-time performance, leading to better handling of different APs and more successful attacks.
Enhanced Logging and Feedback: The plugin logs success and failure rates for handshakes, providing clear insight into its effectiveness. The added performance stats help in tuning attack strategies over time.
Improved Robustness: The watchdog is more resilient, with checks for additional errors (e.g., missing wifi.interface) and the ability to restart the service when necessary.
Adaptability: By adjusting the attack parameters based on success rates, the plugin can adapt its behavior, making it more intelligent and resource-efficient.
Overall, this version is more intelligent and self-correcting. It can now analyze its own performance and adjust its strategies dynamically, leading to better overall efficiency and fewer failed attacks over time. It’s also more robust in dealing with errors, ensuring smoother operation in case of interface or service failures.
Update Summary:
Dynamic Attack Strategy: The plugin now adjusts the aggressiveness of its attacks based on real-time performance, leading to better handling of different APs and more successful attacks.
Enhanced Logging and Feedback: The plugin logs success and failure rates for handshakes, providing clear insight into its effectiveness. The added performance stats help in tuning attack strategies over time.
Improved Robustness: The watchdog is more resilient, with checks for additional errors (e.g., missing wifi.interface) and the ability to restart the service when necessary.
Adaptability: By adjusting the attack parameters based on success rates, the plugin can adapt its behavior, making it more intelligent and resource-efficient.
