Sentence Similarity
Transformers
PyTorch
mpnet
feature-extraction
cybersecurity
sentence-embedding
text-embeddings-inference
Instructions to use basel/ATTACK-BERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use basel/ATTACK-BERT with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("basel/ATTACK-BERT") model = AutoModel.from_pretrained("basel/ATTACK-BERT") - Inference
- Notebooks
- Google Colab
- Kaggle
Example
#1
by joostgrunwald - opened
Could you maybe do an example? Does this map to MITRE Attack?
Could you maybe do an example? Does this map to MITRE Attack?
Sure, this is an embedding model. To map text to MITRE ATT&CK please check our tool SMET at: https://github.com/basel-a/SMET
SMET leverages ATT&CK BERT to map attack actions to ATT&CK.
You can also check our publication "SMET: Semantic Mapping of CVE to ATT&CK and Its Application to Cybersecurity" at https://link.springer.com/chapter/10.1007/978-3-031-37586-6_15 for more details.