Nemesis is an offensive data enrichment pipeline and operator support system.

Built on Kubernetes with scale in mind, our goal with Nemesis was to create a centralized data processing platform that ingests data produced during offensive security assessments.

Nemesis aims to automate a number of repetitive tasks operators encounter on engagements, empower operators’ analytic capabilities and collective knowledge, and create structured and unstructured data stores of as much operational data as possible to help guide future research and facilitate offensive data analysis.

Follow the quickstart guide.

Or see the full setup instructions.

See the Nemesis Usage Guide.

See development.md.

Blog Posts:

Presentations:

Nemesis is built on large chunk of other people's work. Throughout the codebase we've provided citations, references, and applicable licenses for anything used or adapted from public sources. If we're forgotten proper credit anywhere, please let us know or submit a pull request!

We also want to acknowledge Evan McBroom, Hope Walker, and Carlo Alcantara from SpecterOps for their help with the initial Nemesis concept and amazing feedback throughout the development process. Also thanks to Matt Ehrnschwender for tons of k3s and GitHub workflow help!