Open-source alternatives to Pwnagotchi

This project is a WPA Wi-Fi cracking toolkit designed for capturing authentication handshakes and recovering WPA/WPA2 passwords. It provides specialized utilities for scanning wireless networks, obfuscating hardware addresses, and generating password lists to facilitate security audits. The toolkit differentiates itself through a focused workflow that combines handshake capture tools with a password wordlist generator. It enables the interception of the four-way authentication process between wireless clients and access points and utilizes these captured credentials for recovery via dictionar

airgeddon is a bash-based wireless network audit suite and security toolkit for Linux. It serves as a framework for testing wireless vulnerabilities and verifying network configurations across various encryption standards, including WPA, WEP, and WPS. The project functions as an orchestration layer that integrates a collection of third-party wireless security tools. It features a modular approach to attack vectorization, coordinating tasks such as evil twin simulations with captive portals, WPA handshake interception, and the execution of WPS vulnerability tests. Its capabilities cover a bro

Fluxion is a wireless security auditing framework that tests WPA/WPA2 networks by capturing handshakes and deploying rogue access points with captive portals. It operates by deauthenticating clients from legitimate access points, forcing them to reconnect to a cloned network where a fake authentication page collects the network passphrase. The tool distinguishes itself through a plugin-based attack lifecycle with mandatory hook functions for consistent execution, multilingual metadata scripts that load attack descriptions based on locale, and a handshake verification pipeline that validates c

WiFiBroot is a command-line utility designed for wireless network security auditing and penetration testing. It focuses on the evaluation of WPA and WPA2 network security by capturing authentication handshakes and testing the resilience of access points and connected clients. The tool incorporates a deauthentication attack framework that forces client disconnections to facilitate the interception of handshake data. It utilizes stateful reconstruction to assemble complete cryptographic exchanges from fragmented wireless traffic, which are then used for offline credential recovery. The softwar

Wifiphisher is a modular security framework designed for wireless penetration testing and social engineering auditing. It functions as a platform for security professionals to assess the resilience of Wi-Fi networks by simulating unauthorized access, performing man-in-the-middle interceptions, and executing credential-harvesting scenarios. The tool distinguishes itself through its ability to combine rogue access point deployment with dynamic phishing interfaces. By forcing wireless clients to associate with deceptive infrastructure, the framework can capture network metadata and inject it int

Hijacker is a Wi-Fi security auditing suite designed for scanning wireless networks, capturing traffic, and recovering credentials. It provides a set of tools for detecting nearby access points and clients, intercepting WPA handshakes, and recovering WPA and WEP passwords. The project features a visual security audit interface that allows for the execution of specialized tools without using a command-line terminal. It includes a dedicated WPS pin recovery tool for extracting access point pins using pixie-dust attacks via external adapters. The toolkit covers network reconnaissance, including

ESP32-DIV is a handheld wireless pentesting platform designed for analyzing and disrupting a wide range of wireless protocols. It functions as a multi-band radio analyzer, RFID and NFC tag manipulator, and GPS wardriving logger, providing a unified interface for security auditing and signal research. The project distinguishes itself through a modular radio abstraction that allows switching between Wi-Fi, BLE, Sub-GHz, RFID/NFC, and infrared hardware modules. It features a touch-driven TFT interface for navigating toolsets and managing signal profiles, as well as the ability to emulate Bluetoo

Maskphish is a comprehensive security toolkit that integrates capabilities for digital forensics, network vulnerability scanning, open-source intelligence, penetration testing, and social engineering. It functions as a multi-purpose framework for automating reconnaissance and executing security audits across diverse network environments. The project features a specialized phishing and social engineering toolkit used for cloning websites, masking URLs, and deploying deceptive pages to capture user credentials. It also includes a remote access Trojan builder for generating platform-specific exe

This firmware transforms an ESP32 device into a portable penetration testing platform by combining an embedded JavaScript runtime with multi-protocol wireless attack capabilities, USB and Bluetooth HID emulation, and a menu-driven user interface. It is designed as a unified system that integrates persistent storage, hardware abstraction for external radio modules, a serial command protocol for headless operation, and a web-based remote desktop that streams the device screen and relays button inputs for remote control. The custom JavaScript scripting environment enables users to write and run

Presidio is a PII detection and anonymization framework designed to identify and mask personally identifiable information in text. It functions as a PII recognition pipeline and a data masking engine, using a combination of machine learning, regular expressions, and rule-based logic to locate sensitive entities. The system acts as an NER model orchestrator, allowing for the integration of external named entity recognition models and PII detectors to support multi-language privacy scrubbing. It employs a plugin-based recognizer architecture that can be extended with custom recognizers, deny-li

Garak is an AI model evaluation tool and vulnerability scanner designed for red teaming large language models and auditing the security of retrieval-augmented generation pipelines. It identifies behavioral weaknesses, such as jailbreaks, hallucinations, and data leakage, by simulating adversarial attacks and executing automated testing vectors. The framework utilizes an adaptive probing loop where prompts can react to previous model behavior and be modified in flight via middleware. To ensure consistent analysis, it employs a provider-agnostic interface to interact with various model APIs and

Coraza is a web application firewall engine designed to filter malicious HTTP traffic using standardized security directives. It functions as a library for embedding request filtering and security transaction processing directly into web servers or reverse proxies. The engine implements the ModSecurity WAF engine and the OWASP Core Rule Set to identify and block common web attack patterns. It utilizes a library-first integration model, allowing security capabilities to be embedded into a host process as a dependency rather than running as a standalone proxy. The project covers rule-based pat

KeeWeb is a web-based password manager and vault that allows users to open and edit encrypted databases through a browser interface. It functions as a cross-platform tool for managing password vaults using the KeePass database format. The application provides a self-hosted password vault that can be deployed as a single HTML file or via Docker. It integrates with remote storage providers using OAuth to synchronize encrypted database files across multiple devices. The system includes capabilities for secure credential generation, two-factor authentication management through time-based one-tim

Johnny-Five is a JavaScript robotics framework and microcontroller hardware interface designed for programming robots and IoT devices. It provides a standardized library for managing pins, motors, and displays across various microcontroller platforms, allowing developers to control sensors and actuators using a consistent JavaScript API. The framework is distinguished by its use of a plugin-based hardware abstraction system, which enables communication with diverse hardware platforms and protocols. It supports real-time hardware manipulation and debugging through a read-eval-print loop that a

RIOT is a real-time operating system designed for resource-constrained microcontrollers. It provides a kernel for managing hardware peripherals, memory, and multitasking on embedded devices, featuring a microcontroller hardware abstraction layer to unify hardware access across different chipsets. The system employs a preemptive tickless task scheduler with priority-based execution to maximize energy efficiency in battery-powered hardware. It also includes an embedded security framework consisting of cryptographic APIs and secure transport protocols to facilitate authenticated over-the-air fir

Rayhunter is an IMSI catcher detection tool and cellular network monitor designed to identify cell-site simulators and fake base stations. It functions as an SDR signal analyzer that tracks tower connectivity, logs GPS locations, and monitors for network downgrades or disabled encryption on mobile hardware. The system distinguishes itself through heuristic-based traffic analysis used to detect suspicious identity requests, malformed system information, and the use of null ciphers. It includes a remote device management interface consisting of a REST API and web dashboard for controlling detec

This project is a Python-based educational framework designed to simulate reinforcement learning algorithms and environments. It serves as a platform for reproducing classic textbook examples, allowing users to study agent behavior, policy improvement, and the fundamental mechanics of decision-making in controlled settings. The library provides implementations for core reinforcement learning concepts, including temporal difference learning, Monte Carlo episode sampling, and tabular value function approximation. It enables the analysis of specific algorithmic behaviors, such as identifying and

lscript is a wireless network pentesting framework and keyboard-driven command console. It functions as a security tool orchestrator for installing and managing reconnaissance frameworks, alongside an automation toolkit for executing wireless attacks. The project distinguishes itself through a keyboard-driven interface that maps specific keystrokes to complex security scripts and system-level shell operations. This allows for the automation of wireless reconnaissance, handshake capture, and password recovery workflows without manual command typing. The system covers wireless adapter manageme

This project is a game AI training framework designed to develop and monitor reinforcement learning agents within a legacy game environment. It functions as a training and monitoring system that optimizes autonomous agents to complete game objectives through exploration and reward-based learning. The framework includes tools for game memory mapping and real-time trajectory visualization. These capabilities translate raw game memory addresses into visual coordinates, allowing agent movements and session data to be streamed to a map for the analysis of navigation patterns and area exploration.

Minigo is a TensorFlow-based reinforcement learning engine designed to master the game of Go. It functions as a comprehensive system for training neural networks to predict board policies and game outcomes, utilizing a model trainer to generate self-play data and optimize weights. The project is distinguished by its ability to perform large-scale game simulations using Kubernetes to distribute worker nodes across CPU, GPU, and TPU hardware. It employs a Monte Carlo Tree Search implementation to identify optimal moves and supports specialized hardware acceleration, including inference on Edge

Stable-baselines3 is a reinforcement learning library built on the PyTorch deep learning framework. It provides a collection of reliable, standardized implementations of reinforcement learning algorithms designed for training, testing, and benchmarking agent policies in diverse simulated environments. The library functions as an agent training toolkit that emphasizes modularity and reproducibility. It features a unified environment interface and supports vectorized execution to accelerate data collection across multiple simulation instances. Users can customize neural network architectures, f

This project is a machine learning implementation library featuring a collection of code examples that implement supervised, unsupervised, and reinforcement learning algorithms from scratch. It provides a comprehensive set of toolkits for core machine learning components, including a natural language processing toolkit, a reinforcement learning framework, and suites for data dimensionality reduction and pattern mining. The library includes specialized implementations for reinforcement learning, such as Q-Learning, Deep Q-Networks, and Actor-Critic agents. The natural language processing capab

TensorLayer is a backend-agnostic tensor library and deep learning framework designed for building neural network architectures. It provides a neural network abstraction layer that allows model logic to run across different deep learning engines using high-level layers and model components. The project serves as a deep reinforcement learning toolkit for implementing policy-based, value-based, and actor-critic agents. It includes specialized tools for managing experience replay and gradient-based policy optimization to handle both discrete and continuous action spaces. To support reinforcemen

This project is a comprehensive security platform providing an LLM security orchestration framework, an AI agent firewall, and tools for vulnerability remediation, compliance automation, and endpoint protection. It functions as a centralized system to protect AI models from adversarial exploits while managing the identification and patching of software flaws. The platform distinguishes itself through the coordination of specialized AI agents to automate complex security workflows, including reconnaissance, bug hunting, and exploit development. It implements dedicated guardrails to block promp

This project is an educational repository of reinforcement learning agents and tutorials implemented using TensorFlow. It provides a practical codebase for both model-free and model-based learning agents, designed to demonstrate how AI agents learn through trial and error. The collection features detailed implementations of various algorithmic approaches, including Deep Q-Networks and Policy Gradient methods. It specifically covers Actor-Critic architectures for continuous and discrete action spaces, alongside Proximal Policy Optimization and Deep Deterministic Policy Gradients. The framewor

Tianshou is a reinforcement learning framework designed for developing and testing agents. It provides a system for implementing custom agents by defining policies and parameter update rules to optimize agent behavior. The framework decouples neural network architectures from update logic through policy-based abstractions and separates data pre-processing from gradient updates. It utilizes a collector-driven pipeline to stream experience from environments into structured memory buffers for sampled learning. The system supports vectorized environment execution to run multiple parallel instanc

DeepMimic is a deep reinforcement learning framework and physics-based motion imitation tool designed to teach simulated characters and robots to reproduce human movements. It provides a pipeline for integrating motion capture data into physics simulations to train agents that can mimic complex physical skills. The system utilizes the PyBullet simulation environment to execute motion policies and visualize character interactions in real time. It includes a motion capture integration pipeline that imports and processes animation sequences to serve as reference targets for imitation learning ag