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CodeNinjatools/ot-security-cip-evidence-us-ontology

OT security and NERC CIP evidence ontology and model register for an electric utility The object model and the model and equipment register from Grid Context Watch: One system of context for OT Security and NERC CIP Evidence, an open reference architecture by CodeNinja for United States. Part of the Vertical-Driven Architectures series; every design in the series is also a row in the cumulative dataset https://huggingface.co/datasets/CodeNinjatools/vertical-driven-architectures.… See the full description on the dataset page: https://huggingface.co/datasets/CodeNinjatools/ot-security-cip-evidence-us-ontology.

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OT security and NERC CIP evidence ontology and model register for an electric utility

The object model and the model and equipment register from Grid Context Watch: One system of context for OT Security and NERC CIP Evidence, an open reference architecture by CodeNinja for United States. Part of the Vertical-Driven Architectures series; every design in the series is also a row in the cumulative dataset https://huggingface.co/datasets/CodeNinjatools/vertical-driven-architectures.

  • —Read the paper: https://codeatoms.ai/ot-security-cip-evidence-us/
  • —DOI: https://doi.org/10.5281/zenodo.23157957
  • —Source files and PDF: https://github.com/muhammadumar89/codeninja-research
  • —Live view: https://huggingface.co/spaces/CodeNinjatools/ot-security-cip-evidence-us

Files

FileWhat it holds
objects.json14 typed objects (Substation, OT Asset, Network Sensor, Anomaly Alert, Investigation Case, Vulnerability Finding, Detection Rule, Threat Intelligence Item, Pcap Evidence Record, CIP Evidence Artefact, OT Security Analyst, SIEM, Energy management system, Substation data platform), each with its anchor system, properties, status vocabulary and 14 typed links. Format hyper-ontology/1: designed with Praxis, implemented with Hyper Ontology.
models.csvThe model and equipment register from the paper's Table 4, with the reason for each choice.

How to use it

python
import json
from huggingface_hub import hf_hub_download
p = hf_hub_download("CodeNinjatools/ot-security-cip-evidence-us-ontology", "objects.json", repo_type="dataset")
objects = json.load(open(p))["objects"]
print([o["label"] for o in objects])

Made with

Designed on Praxis, CodeNinja's platform for designing physical AI systems. The object model imports into Hyper Ontology, which turns it into a living system. Both are in beta; access by request.

Citation

CodeNinja Engineering Team and Umar Bilal. 2026. Grid Context Watch: One system of context for OT Security and NERC CIP Evidence. CodeNinja. https://doi.org/10.5281/zenodo.23157957. CC BY 4.0.