Isolation Forest for anomaly detection.
OCI NodeJS client for Ai Anomaly Detection Service
Node-RED node for time-series forecasting and anomaly detection using Exponential Smoothing
Anomaly detection and behavioral baseline for @datacules/agent-identity — statistical detection of unusual credential usage patterns
TypeScript SDK for Observability AI API - EV charging session anomaly detection
Relatively simple library bringing multiple outlier/anomaly detection algorithms together in one place.
Node.js SDK for LogWatch — AI-powered log anomaly detection
UniFi semantic analysis MCP server — fleet health, anomaly detection, cross-site analytics on top of Cloud API
Agent spend tracking, budget enforcement, tool policy, and anomaly detection for OpenClaw
DataFlow core engine — streaming pipeline, adapters, anomaly detection
MCP client for refinancier — Trust Infrastructure for Uncertain Assets. Enterprise valuation, anomaly detection, and value-up recommendations for AI agents.
Open-source Cursor IDE usage monitoring, anomaly detection, and alerting for enterprise teams
Temporal knowledge discovery for RDF graphs - pattern mining, anomaly detection, trend analysis
Electron memory profiling SDK - zero-intrusion memory monitoring, anomaly detection, and regression analysis
Statistical volume anomaly detection for trade streams - Hawkes process, CUSUM, and Bayesian Online Changepoint Detection (BOCPD). Zero dependencies. TypeScript.
Node-RED Nodes for anomaly detection, predictive maintenance, and time series analysis
SOC2-grade security controls for DoNotDev — audit logging, rate limiting, PII encryption, auth hardening, anomaly detection, privacy management
Official LogNexis Node.js SDK — AI-powered API monitoring with Express middleware, automatic log capture, batch ingestion, and anomaly detection.
Behavioral trust scoring MCP server for 14,800+ MCP servers — runtime reliability, anomaly detection, and compliance reporting for the agent economy
Data analysis that learns your schema. Query optimization, anomaly detection, pipeline monitoring — understands your data better every day.
High-performance financial risk analysis plugin with portfolio risk scoring, anomaly detection, market regime classification, and compliance reporting using RuVector WASM packages.
High-performance financial risk analysis plugin with portfolio risk scoring, anomaly detection, market regime classification, and compliance reporting using RuVector WASM packages.
A command-line interface tool for anomaly detection and management
Node anomaly detection on continuous time series data
Time series anomaly detection for Rust
anomalyx detector registry: point, distributional, structural, multivariate and cadence families
Multi-algorithm anomaly detection engine (Z-Score, IQR, MAD, CUSUM) for LLM telemetry
Sequential pattern analysis through variable-order Markov chains. Built for detecting deviations in finite-alphabet sequences.
A sophisticated real-time anomaly detection system for ADS-B aircraft data with multi-tier detection algorithms, real-time web dashboard, and production-grade architecture built in Rust
anomalyx command-line contract surface: describe / schema / scan / explain
anomalyx contract core: typed record model, anomaly taxonomy, deterministic reductions, and the tq1 output envelope
Streaming anomaly detection toolkit — Random Cut Forest, per-feature drift, streaming sketches, SOC triage, hot-path ingress. Facade re-export of anomstream-core / anomstream-triage / anomstream-hotpath.
Core streaming anomaly detectors + companion primitives (Random Cut Forest, per-feature EWMA / CUSUM, drift detectors, streaming stats) — part of the anomstream toolkit
High-cadence ingress primitives (UpdateSampler, PrefixRateCap, bounded MPSC channel) for eBPF-style classifier/updater thread splits on top of anomstream-core
SOC-opinionated triage layer (Platt calibration, SAGE attribution, alert clustering, feedback, audit) on top of anomstream-core
Detect emergent patterns — clustering, correlations, phase transitions, and conservation laws — across task outputs
Time series anomaly detection for Ruby
Anomaly detection using gaussian distribution, written in ruby
Easy-to-use anomaly detection for Ruby
Explainable outlier/anomaly detection for Ruby
Read more documentation at repository homepage.
Edge stream anomaly detection for Ruby
Outlier/anomaly detection for Ruby using Isolation Forest
Random Cut Forest anomaly detection for Ruby
Normal distribution model allows to create normal distribution from given data.Initial reason to build this was to use it in anomaly detection in discrete numerical data.
This gem analyses its line to detect for anomalies in each doll type.
API client for the Mellyn service - a powerful tool for login anomaly detection and response, enhancing the security of your application.
Ruby CLI tool for interacting with Rayhunter, a cell tower analysis device for detecting IMSI catchers and other cellular network anomalies.
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