SecReranker
Cybersecurity-specialized cross-encoder reranker trained on SecEmbed contrastive pairs (ATT&CK, Sigma, CVE, CWE, SOC playbooks).
Base model
cross-encoder/ms-marco-MiniLM-L-6-v2
Training
- Dataset:
alirezaaminzadeh/secembed-pairs - Loss: MultipleNegativesRankingLoss (bi-encoder) / Binary cross-entropy (reranker)
- Hard negatives: sibling ATT&CK techniques, same-CWE CVEs, unrelated Sigma rules
- Hardware: Hugging Face ZeroGPU
Evaluation (CyberSec Retrieval Benchmark sample)
{
"note": "pair classification trained; use demo Space for retrieval@k with bi-encoder cascade"
}
Usage
from sentence_transformers import CrossEncoder
model = CrossEncoder("alirezaaminzadeh/SecReranker")
print(model.predict([["detect powershell encoded command", "T1059.001 PowerShell..."]]))
Intended use
RAG over security knowledge bases, threat-intelligence search, SOC alert enrichment, CVE/CWE similarity, Sigma rule retrieval, and ATT&CK technique mapping.