eromang/cyberscale-operational-v1

Model

0

stars

3

commits

1

linked in READMEs

Mar 31, 2026

updated

cyber-blueprint
cybersecurity
endpoints_compatible
incident-classification
model-index
modernbert
nis2
operational-severity
safetensors
text-classification
text-embeddings-inference
transformers
Browse cluster: Transformer Text Classification & Embeddings

README

CyberScale Operational Severity v1

Incident operational severity classifier (O1-O4). Assesses consequence and coordination needs from a crisis management perspective.

Model Description

  • Architecture: ModernBERT-base with 4-class classification head
  • Training: 8,000 parametric incident scenarios (50 templates × field combinations)
  • Confidence: Monte Carlo dropout (20 passes) maps variance to high/medium/low
  • Labels: O1 (local) → O4 (EU-wide crisis)

Intended Use

Classify the operational severity of cyber incidents based on entity relevance, cross-border impact, member states affected, and coordination needs. Part of the CyberScale dual-scale incident classification system (T-level + O-level → Blueprint matrix).

Input format: <description> [SEP] sectors: <list> relevance: <level> ms_affected: <N> cross_border: <level> coordination: <level> capacity_exceeded: <bool>

Metrics

MetricValueTarget
Accuracy1.0> 75%
Macro F11.0> 75%

Citation

Part of the CyberScale project — multi-phase cyber severity assessment MCP server.

Contributors

eromang

3 commits

eromang/cyberscale-operational-v1

Model

0

stars

3

commits

1

linked in READMEs

Mar 31, 2026

updated

cyber-blueprint
cybersecurity
endpoints_compatible
incident-classification
model-index
modernbert
nis2
operational-severity
safetensors
text-classification
text-embeddings-inference
transformers
Browse cluster: Transformer Text Classification & Embeddings

README

CyberScale Operational Severity v1

Incident operational severity classifier (O1-O4). Assesses consequence and coordination needs from a crisis management perspective.

Model Description

  • Architecture: ModernBERT-base with 4-class classification head
  • Training: 8,000 parametric incident scenarios (50 templates × field combinations)
  • Confidence: Monte Carlo dropout (20 passes) maps variance to high/medium/low
  • Labels: O1 (local) → O4 (EU-wide crisis)

Intended Use

Classify the operational severity of cyber incidents based on entity relevance, cross-border impact, member states affected, and coordination needs. Part of the CyberScale dual-scale incident classification system (T-level + O-level → Blueprint matrix).

Input format: <description> [SEP] sectors: <list> relevance: <level> ms_affected: <N> cross_border: <level> coordination: <level> capacity_exceeded: <bool>

Metrics

MetricValueTarget
Accuracy1.0> 75%
Macro F11.0> 75%

Citation

Part of the CyberScale project — multi-phase cyber severity assessment MCP server.

Contributors

eromang

3 commits