IntelOwl is a production-grade, open-source threat intelligence platform that automates the analysis of observables (IPs, domains, URLs, hashes) and files (PE, PDF, APK, etc.) through a pluggable plugin system. The backend is built with Django REST Framework, Celery for asynchronous task execution, and Django Channels for real-time WebSocket updates. The frontend is a React single-page application using react-router, react-flow for pipeline visualizations, and Zustand for state management. The system supports multi-tenancy, organizations, role-based access, and integrates with dozens of external threat intelligence APIs and open-source analysis tools via containerized microservices. The architecture is centered around a plugin framework with five plugin types: analyzers (file and observable), connectors (push results to external systems), visualizers (render reports), pivots (create child jobs from analysis results), and ingestors (pull threat feeds). Playbooks bundle these plugins into repeatable analysis workflows. A data model manager normalizes analyzer outputs into structured evaluations with reliability scores, and a user event system allows manual verdict overrides with decay logic. The platform also includes an AI chatbot assistant powered by a local Ollama LLM and LangGraph, enabling natural-language queries and one-click analysis launches. Key operational features include a comprehensive REST API, token-based authentication with optional OAuth/LDAP/RADIUS, Elasticsearch for BI reporting, and Docker-based deployment with separate containers for specialized analyzers. The codebase is actively maintained with extensive unit and integration tests, CI/CD pipelines, and a large community (4695 stars). While the migration system is somewhat repetitive, the overall architecture is clean, modular, and demonstrates strong software engineering practices.
Nova Proximity is a modular Python security scanner designed specifically for MCP (Model Context Protocol) servers and Agent Skills. The application provides comprehensive discovery and analysis capabilities, including tool/prompt/resource enumeration for MCP servers and structural/permission analysis for Agent Skills. Its architecture separates concerns into distinct libraries: mcp_scanner_lib for MCP protocol handling, skill_scanner_lib for Agent Skills analysis, and nova_evaluator_lib for NOVA-powered security evaluation. The tool supports multiple transport mechanisms (stdio, SSE, Streamable HTTP) with automatic fallback, provides detailed function signature analysis, and generates actionable security reports with pattern-specific remediation guidance.
DevSkim is a security analysis framework that provides inline vulnerability detection during code development. It consists of a core .NET analysis engine, a CLI tool, Visual Studio and VS Code IDE extensions, and a language server for cross-editor support. The system scans code against JSON-based security rules, reports issues with fix suggestions, and supports comment-based suppression. Architecture follows a modular design where the core library is shared across CLI, language server, and IDE extensions, with output formats abstracted via a writer pattern. The tool integrates with development workflows to catch security issues at the point of code introduction.