A modular malware and IOC ingestion framework that collects, enriches, and exports threat intelligence from multiple feeds.
MalPipe is a modular malware and indicator of compromise (IOC) collection and processing framework. It automates the ingestion of threat data from multiple feeds like VirusTotal and MalShare, enriches it with additional context (e.g., YARA scanning, DNS resolution), and exports the results for security analysis. It solves the problem of manually aggregating and processing disparate threat intelligence sources.
Security analysts, threat intelligence teams, and SOC engineers who need to automate the collection and enrichment of IOCs and malware samples from open-source feeds.
Developers choose MalPipe for its modular, extensible architecture that allows custom pipelines, its support for multiple threat feeds out of the box, and its ability to integrate enrichment processors like YARA scanning and DNS lookups without relying on proprietary platforms.
Malware/IOC ingestion and processing engine
Open-Awesome is built by the community, for the community. Submit a project, suggest an awesome list, or help improve the catalog on GitHub.
Allows flexible configuration of feeds, processors, and exporters through a JSON file, enabling tailored threat intelligence workflows as shown in the config_example.json.
Supports key threat intelligence sources like VirusTotal, MalShare, and BambenekFeeds out of the box, reducing setup time for common data ingestion.
Provides a clear framework for creating new feeds, processors, and exporters as Python classes, detailed in the Developing Modules section with example code.
Includes processors like YaraScan and DNSResolver to add context to IOCs, enhancing analysis without relying on external tools.
Requires detailed JSON setup for each module, which can be error-prone and time-consuming, especially for dynamic or large environments with multiple feeds.
Lacks direct exporters for modern SIEMs or cloud services; integration requires custom development, as seen with the basic exporters like JSONLog and LocalFileStorage.
The README covers basics but lacks advanced examples for scaling, error handling, or troubleshooting, which may hinder adoption in production settings.