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| title: CVE to MITRE ATT&CK Mapper | |
| emoji: 🛡️ | |
| colorFrom: blue | |
| colorTo: green | |
| sdk: gradio | |
| sdk_version: 6.22.0 | |
| app_file: app.py | |
| short_description: Map CVE descriptions to MITRE ATT&CK techniques | |
| python_version: "3.12" | |
| startup_duration_timeout: 30m | |
| # CVE to MITRE ATT&CK Technique Mapper | |
| This Space demonstrates the model | |
| [`CIRCL/vulnerability-attack-technique-classification-roberta-base`](https://huggingface.co/CIRCL/vulnerability-attack-technique-classification-roberta-base), | |
| a RoBERTa-base multi-label classifier that maps free-text vulnerability (CVE) | |
| descriptions to **MITRE ATT&CK Enterprise** techniques. | |
| The model was trained on a curated gold set of 1,207 CVEs assembled from | |
| expert MITRE CTID mappings, as described in the paper | |
| [*Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and | |
| the Limits of LLM-Assisted Label Expansion*](https://arxiv.org/abs/2607.25572). | |
| ## Usage | |
| 1. Paste a CVE / vulnerability description into the text box. | |
| 2. Click **Classify**. | |
| 3. The model returns the top-K MITRE ATT&CK techniques ranked by sigmoid | |
| probability, along with a high-confidence summary. | |
| ## Technical details | |
| - **Architecture:** `roberta-base` with a sigmoid head | |
| - **Labels:** 53 parent MITRE ATT&CK techniques (sub-techniques collapsed) | |
| - **Input:** Free-text vulnerability description (max 512 tokens) | |
| - **Output:** Sigmoid probability for each of the 53 techniques | |
| ## Links | |
| - [Paper (arXiv)](https://arxiv.org/abs/2607.25572) | |
| - [Model card](https://huggingface.co/CIRCL/vulnerability-attack-technique-classification-roberta-base) | |
| - [VulnTrain library](https://github.com/vulnerability-lookup/VulnTrain) | |
| - [Gold dataset](https://huggingface.co/datasets/CIRCL/vulnerability-attack-techniques) |