SecureBERT2.0 biencoder EU AI Act Compliance Profile

Model Card for cisco-ai/SecureBERT2.0-biencoder

The SecureBERT 2.0 Bi-Encoder is a cybersecurity-domain sentence-similarity and document-embedding model fine-tuned from SecureBERT 2.0.
It independently encodes queries and documents into a shared vector space for semantic search, information retrieval, and cybersecurity knowledge retrieval.

Model Details

Model Description

• Developed by: Cisco AI
• Model type: Bi-Encoder (Sentence Transformer)
• Architecture: ModernBERT backbone with dual encoders
• Max sequence length: 1024 tokens
• Output dimension: 768
• Language: English
• License: Apache-2.0
• Finetuned from: cisco-ai/SecureBERT2.0-base

Uses

Direct Use

• Semantic search and document similarity in cybersecurity corpora
• Information retrieval and ranking for threat intelligence reports, advisories, and vulnerability notes
• Document embedding for retrieval-augmented generation (RAG) and clustering

Downstream Use

• Threat intelligence knowledge graph construction
• Cybersecurity QA and reasoning systems
• Security operations center (SOC) data mining

Out-of-Scope Use

• Non-technical or general-domain text similarity
• Generative or conversational tasks

Model Architecture

The Bi-Encoder encodes queries and documents independently into a joint vector space.
This architecture enables scalable approximate nearest-neighbor search for candidate retrieval and semantic ranking.

Datasets

Fine-Tuning Datasets

| Dataset Category | Number of Records | |:-----------------|:-----------------:| | Cybersecurity QA corpus | 43 000 | | Security governance QA corpus | 60 000 | | Cybersecurity instruction–response corpus | 25 000 | | Cybersecurity rules corpus (evaluation) | 5 000 |

Dataset Descr

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Base Model