Cybersecurity RAG Knowledge Graph with 25 Topics and 75 Articles

Cybersecurity RAG Knowledge Graph is a structured, synthetic dataset designed for retrieval-augmented generation systems and AI copilots. The preview contains a knowledge graph built from 75 articles organized into 25 topics, resulting in approximately 200 text chunks. The dataset was created by Lucasautomatekc and last updated on Hugging Face in April 2026.

Use Cases

• Fine-tuning language models for cybersecurity question answering based on the structured knowledge graph.
• Building retrieval pipelines for AI copilots based on the 200 text chunks.
• Testing domain-specific information retrieval systems based on the 25 synthetic topics.
• Developing synthetic training data for cybersecurity NLP tasks based on the commercially-safe articles.

Strengths

• Contains a structured knowledge graph with explicit metadata.
• Organizes content into 25 distinct cybersecurity topics.
• Includes approximately 200 processed text chunks for retrieval.

Limitations

• Description metadata is limited; actual data quality requires manual inspection after download.
• Column-level documentation is absent; field semantics must be inferred after download.
• The available preview may be a subset of a larger commercial package.

Provenance

Source

Lucasautomatekc on Hugging Face.

Collection Method

Synthetically generated and structured for commercial safety.

Freshness

Last updated 2026-04-11 14:14:00; freshness should be verified.