This repository is a curated collection of threat intelligence indicators of compromise (IOCs) published by ESET Research. It contains structured data for hundreds of malware families and APT campaigns, including file hashes (MD5, SHA1, SHA256), network indicators (domains, IPs, URLs), host-based artifacts (registry keys, file paths, mutexes), and detection rules (YARA, Sigma, Snort). The data is organized per-threat in consistent directory structures with README.adoc documentation, MISP event JSON exports, and plain hash lists. The repository serves as a reference for threat hunters, SOC analysts, and security researchers to detect and investigate known threats. While the data is static and time-sensitive, the detection rules and structured IOC formats are directly reusable in security tools and platforms.
This repository is a comprehensive library of machine-readable taxonomies (machine tags) for threat intelligence and information sharing, primarily designed for the MISP platform. It contains over 200 taxonomy definitions in a standardized JSON format, each defining a namespace with predicates and values for tagging events, attributes, and indicators. The taxonomies cover a wide range of domains including cyber incident classification, malware analysis, information handling policies (TLP, PAP, IEP), regulatory compliance (GDPR, NIS2, EU AI Act), attack modeling (kill chain, Diamond Model), and specialized areas like disinformation, AI safety, and drone classification. While the core content is data, the repository also includes a set of reusable Python tools for validation, generation, and conversion of taxonomies, as well as CI/CD pipelines and a JSON schema. The hybrid nature is evident: it is primarily a data library but with significant application-like tooling for maintaining and extending the taxonomy collection.