FingerprintJS is a client-side browser fingerprinting library written in TypeScript. It collects over 30 entropy signals (canvas, audio, fonts, WebGL, etc.) from the browser environment and hashes them into a stable visitor identifier. The library operates in two phases: a load phase where entropy sources are prepared asynchronously, and a get phase where values are collected and combined. It includes stabilization logic for browsers that apply anti-fingerprinting measures (e.g., Safari 17, Firefox 120+) and provides a confidence score for the identifier. The architecture is modular: each entropy source is a separate function with a consistent interface, the agent orchestrates collection, and the hashing uses a custom MurmurHash3 x64 128-bit implementation. The library has no runtime dependencies and is tree-shakable. It is used for fraud detection and visitor identification without cookies.
PyOD is a comprehensive Python library for anomaly/outlier detection offering 60+ detectors across tabular, time series, graph, text, image, and audio modalities. It provides a classic scikit-learn-compatible API (fit/predict/decision_function) via pyod.models, a high-level orchestration engine (ADEngine) for automatic profiling, detector selection, consensus scoring, and reporting, and an agentic workflow layer for LLM-driven anomaly detection through CLI, MCP server, and packaged AI skills. The library is primarily a software library (application) with strong data research influence: it comes with benchmark-backed routing rules, academic references, and Jupyter notebooks for research reprocibility. Its architecture follows a three-layer design (classic detectors, ADEngine orchestration, agentic skills) that allows progressive engagement from simple model fitting to full automated pipelines.
This repository is a comprehensive, curated list of anomaly detection (outlier detection) resources, maintained by the author of the PyOD library. It aggregates books, academic papers, tutorials, open-source toolkits, datasets, and relevant conferences/journals, covering tabular, time-series, graph, and text data modalities. The repository also includes two utility scripts: a downloader for paper PDFs and a robust URL checker for verifying links in the documentation. While the core value is the curated resource list itself, the utility scripts demonstrate clean engineering practices and are reusable for similar link-checking and batch download tasks. This is not a software application or data pipeline; it is a reference catalog for researchers and practitioners.
This repository serves as the central community hub for the freeRASP mobile security SDK. It does not contain any source code itself; instead, it aggregates platform-specific implementations (Android, iOS, Flutter, React Native, etc.) via Git submodules. The actual security detection logic, integration APIs, and threat monitoring are implemented in the respective submodule repositories. This meta-repo provides documentation, issue tracking, and release coordination across platforms. It is well-maintained with active issue triage and a CI workflow for issue monitoring. The project is licensed under MIT with a fair usage policy.