Nemesis is an offensive data enrichment pipeline designed to centralize and process files, functioning as an "offensive VirusTotal." It targets security professionals and researchers seeking to automate and enhance file analysis in offensive security contexts.

How It Works

Nemesis 2.0 utilizes a Docker-based architecture with significant integration of Dapr (Distributed Application Runtime). This approach enables a microservices-based pipeline for distributed file processing, allowing for scalable and modular execution of various enrichment tasks.

Quick Start & Requirements

• Installation: Follow the quickstart guide.
• Prerequisites: Docker.
• Resources: Not specified, but likely requires significant disk space and CPU for file processing.

Highlighted Details

• Functions as an "offensive VirusTotal" for file analysis.
• Built on Docker with heavy Dapr integration for distributed processing.
• Includes blog posts and presentations detailing its use and development.
• Acknowledges contributions from OpenAI and Claude for the rewrite.

Maintenance & Community

The project is actively maintained by SpecterOps, with contributions acknowledged from internal team members and external AI models. Links to blog posts and presentations indicate ongoing engagement.

Licensing & Compatibility

The README does not explicitly state the license. Citations and licenses for adapted code are provided within the codebase. Compatibility for commercial or closed-source use is not specified.

Limitations & Caveats

The project is described as "Nemesis 2.0," implying potential for breaking changes from previous versions. The previous codebase (1.0.1) is preserved as a branch. Specific resource requirements and detailed operational limitations are not fully elaborated in the overview.