Projects sharing features with Whereami

wifijammer is a wireless network utility designed to identify wireless targets and disrupt active network connections through management frame injection. It functions as a Wi-Fi deauthentication tool and wireless scanning utility that injects frames into the air to force devices to drop their network links. The software enables targeted disruption by focusing on specific hardware addresses across multiple radio frequencies. It employs a scanning capability that hops through Wi-Fi channels to identify active access points and connected clients within range. The project covers capabilities for

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

This project is a collection of interactive notebooks for a TensorFlow deep learning course. It provides guided learning resources and practical tutorials for implementing neural network architectures, supervised learning, and transfer learning. The materials feature a computer vision learning path and specific guides for transfer learning, demonstrating how to adapt pre-trained models to new tasks. It includes tutorials for building regression models and image classifiers using the Keras high-level API. The scope covers supervised learning pipelines for binary and multiclass classification,

wlan-sec-test-tool is a collection of specialized wireless security tools designed for scanning access points, auditing WPA, WPA2, and WPA3 security, and performing automated password cracking and connection testing. It functions as a wireless network scanner, a password cracker, and a security auditor to evaluate wireless protocol vulnerabilities. The tool differentiates itself through the use of a concurrent connection tester that executes multiple simultaneous connection attempts. It utilizes custom password lists and dictionary-based iteration to verify wireless network security and deter

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

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

This research framework provides a deep learning driving simulator and a multimodal data pipeline for autonomous vehicle research. It centers on the creation of synchronized autonomous vehicle datasets, which combine high-frequency vehicle telemetry with camera frames to train neural networks. The project implements a convolutional neural network trainer specifically designed to predict steering angles and vehicle transition states from visual data. It features generative capabilities, using autoencoders and transition models to synthesize driving environments and simulate future vehicle move

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 deep learning system designed for real-time emotion recognition and facial expression analysis. It utilizes a convolutional neural network architecture to process raw visual input, mapping complex facial patterns to seven distinct emotional states through a supervised machine learning pipeline. The system functions as both a training framework and an inference engine. It includes utilities for preparing and standardizing large image datasets to ensure consistent input quality, alongside a real-time processing pipeline that captures and buffers live video frames to perform co

OpenWifi is an open-source implementation of the IEEE 802.11n wireless standard designed for programmable logic. It provides a software-defined radio platform and WiFi baseband processor that implements the physical and MAC layers on FPGA hardware, accompanied by a dedicated wireless driver and toolset for hardware control. The project is distinguished by its deep integration of signal analysis and telemetry, specifically through a framework for capturing channel state information and raw IQ samples. It enables high-precision packet timestamping and cross-layer correlation between physical la

Miraclecast is a software implementation of the Miracast protocol used for mirroring screens and streaming audio over Wi-Fi. It functions as a wireless display adapter, providing the capabilities of both a Wi-Fi display source that projects local content and a Wi-Fi display sink that acts as a wireless receiver for remote streams. The project includes a peer-to-peer wireless network manager used to discover nearby devices and establish direct Wi-Fi connections. It specifically implements a wireless input backchannel, allowing mouse and keyboard events to be routed from a receiving display bac

This project is a comprehensive collection of educational notebooks designed to demonstrate machine learning algorithms and data science workflows. It serves as a practical resource for implementing predictive modeling, clustering, and neural network architectures using Python. By combining live code, narrative text, and visual outputs, the repository facilitates iterative experimentation and hands-on learning of fundamental data science concepts. The collection distinguishes itself by emphasizing machine learning engineering practices, such as the application of object-oriented design patter

This repository is a collection of practical machine learning implementations designed to demonstrate core predictive analytics, computer vision, and natural language processing techniques. It serves as a resource for applying standard machine learning frameworks to solve diverse data science problems, ranging from automated classification to complex pattern recognition. The project distinguishes itself by providing concrete examples across multiple domains, including the development of conversational interfaces, the analysis of geospatial data, and the implementation of deep learning archite

Instructor is a framework designed for structured data extraction, validation, and language model integration. It functions as a library that transforms unstructured text into validated, type-safe objects by leveraging schema definitions and model-specific tool-calling capabilities. By acting as a validation middleware, the project ensures that language model outputs strictly conform to defined data structures. The library distinguishes itself through a robust validation-based retry loop that automatically re-submits failed responses with error feedback to iteratively correct schema complianc

AdalFlow is an autonomous AI agent framework and LLM application library designed for building modular workflows. It serves as a model-agnostic interface and RAG pipeline orchestrator, allowing users to develop ReAct agents that utilize iterative reasoning and external tool execution to solve complex tasks. The project distinguishes itself through a prompt optimization system that uses textual gradient descent to automatically refine prompt templates and few-shot examples. It treats model feedback as a differentiable signal, enabling a form of LLM backpropagation to iteratively improve output

This project is a Model Context Protocol server that bridges artificial intelligence agents with cloud-based web scraping and automation resources. It functions as a remote task orchestrator, allowing agents to discover, configure, and execute complex browser automation jobs as callable functions within their native environments. The server distinguishes itself by providing a unified framework for managing distributed workflows, including the ability to handle asynchronous task polling, structured data serialization, and real-time status tracking. It supports advanced agentic capabilities suc

Omi is an open-source wearable AI platform that captures audio and screen data to provide real-time conversational assistance and memory. It integrates a wearable hardware development kit with a vector memory database and large language model capabilities to create a persistent digital record of user interactions. The platform is distinguished by its BLE audio streaming pipeline, which transmits raw audio from wearable hardware for real-time transcription and speaker identification. It utilizes a plugin-based agent tool framework that allows AI assistants to autonomously invoke custom functio

BAML is a prompt engineering framework and LLM client generator that defines AI prompts as type-safe functions. It serves as a structured data extraction tool and workflow orchestrator, transforming unstructured model responses into strongly typed objects using a custom schema language and alignment algorithms. The project distinguishes itself by using a compiler to generate language-specific boilerplate code for API communication and output parsing. It features a dedicated environment for designing complex prompt templates with conditional logic and reusable snippets, and employs genetic alg

ruby_llm is an LLM integration framework and AI agent orchestrator designed to connect applications to multiple large language model providers through a unified interface. It serves as a toolkit for building autonomous assistants with custom personas, managing structured output via JSON schemas, and implementing vector embedding engines for semantic search. The project distinguishes itself as an observability suite and multimodal toolkit. It provides specialized capabilities for tracking token usage, calculating model costs, and tracing workflows via OpenTelemetry, while supporting the proces

This project is an Android RPA framework designed for automating user interfaces and system tasks on rooted Android devices using Python and ADB. It provides a suite of tools for rooted device management, allowing for programmatic control of system settings, application lifecycles, and shell command execution via a remote API. The framework distinguishes itself through a combination of dynamic instrumentation and AI integration. It can inject scripts into running processes to hook Java interfaces and modifies application behavior in real time. Additionally, it supports large language model in

Guardrails is a Python SDK that wraps calls to large language models with configurable validation pipelines, corrective actions, and structured output generation. It provides a unified API layer that connects to over 100 language models, applying consistent validation, streaming, and error-handling across providers. The framework validates and corrects model responses against safety and quality rules, detecting and mitigating risks in both inputs and outputs using pre-built and custom validators. The project distinguishes itself through a validator-pipeline architecture that sequentially appl

Instructor is a schema enforcement and validation library designed to transform language model outputs into structured, type-safe data formats. It functions as a validation layer that uses Pydantic to ensure model responses conform to specific data models, acting as a tool for forcing large language models to return data in predefined schemas. The project differentiates itself through a recursive error-feedback loop that automatically retries requests when structural errors occur, passing validation failure messages back to the model to guide corrections. It also includes a streaming parser c

Kit is a desktop automation framework and scriptable UI toolkit designed for building personalized productivity tools. It serves as a cross-platform CLI wrapper and macOS system automator, providing an environment to execute scripts that manage operating system tasks, file management, and application workflows. The project distinguishes itself with a dedicated LLM integration layer for structured data extraction and text generation, alongside a specialized UI framework for creating interactive input forms, HTML windows, and floating widgets. It features deep macOS integration through AppleScr

Instructor is a library designed to parse, validate, and map unstructured language model responses into strongly typed, schema-compliant data objects. It provides a framework for structured data extraction that uses data modeling classes to enforce strict type constraints on model outputs, ensuring that generated content consistently matches expected structures. The library distinguishes itself through an automated error recovery system that manages the lifecycle of failed extraction attempts. When a model output fails to meet defined schema requirements, the framework automatically triggers

llmware is a Python framework for AI agent orchestration and model management, designed to coordinate multi-model workflows and autonomous agents. It provides a unified model catalog and standardized interface to execute specialized language models for complex research, analysis, and structured data generation. The project distinguishes itself through its heavy emphasis on local execution and quantized inference, allowing models to run on private infrastructure using CPU, GPU, and NPU acceleration via runtimes like ONNX and OpenVino. It features a specialized ability to translate natural lang

This project is an AI-driven phone agent platform and telephony gateway designed to automate inbound and outbound voice interactions. It functions as a conversational voicebot system that utilizes large language models to conduct natural language phone conversations for customer support and data collection. The platform distinguishes itself through the integration of retrieval-augmented generation, allowing voice agents to search internal knowledge bases for domain-specific answers during live calls. It features automated language detection to support multilingual conversations and a system f

Llama-ocr is a library designed to convert images and documents into structured markdown by leveraging multimodal vision models. It functions as a vision-based text extractor and document parser, identifying and transcribing both textual content and spatial layout from image-based files. The tool utilizes large vision models to perform zero-shot layout parsing, allowing it to interpret document structures without the need for task-specific training data. It employs prompt-driven extraction to guide the model in formatting raw visual data into consistent markdown syntax, while operating throug