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README.md

@@ -3,15 +3,16 @@ license: mit
 language:
 - en
 tags:
-- cybersecurity
-- vulnerability
-- mitre-attck
+- mitre-attack
 - text-classification
 - fine-tuned
+- cybersecurity
+- vulnerability
+- securebert
 base_model: ehsanaghaei/SecureBERT
 ---
 
-# SecureBERT — MITRE ATT&CK Classifier
+# SecureBERT — MITRE ATT&CK Enterprise Subtechniques Flat Classifier
 
 [![PhD theses.fr](https://img.shields.io/badge/Project-theses.fr-orange?logo=university&logoColor=white)](https://theses.fr/s371241)
 [![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
@@ -19,7 +20,6 @@ base_model: ehsanaghaei/SecureBERT
 [![Zenodo Code](https://img.shields.io/badge/Zenodo-Code%20Repository-blue?logo=information&logoColor=white)](https://zenodo.org/records/17368476)
 [![GitHub](https://img.shields.io/badge/GitHub-CVE--LMTune-black?logo=github)](https://github.com/terranovafr/CVE-LMTune)
 
-
 <div align="center">
   <img src="https://upload.wikimedia.org/wikipedia/commons/thumb/5/5b/Logo_Universit%C3%A9_de_Lorraine.svg/1280px-Logo_Universit%C3%A9_de_Lorraine.svg.png" alt="Universite de Lorraine" height="50"/>
   &nbsp;&nbsp;
@@ -41,15 +41,19 @@ Part of the **CVE-LMTune** model suite — language models fine-tuned for multi-
 
 ## Task
 
-**MITRE ATT&CK technique classification from CVE descriptions**
+**MITRE ATT&CK Enterprise Subtechniques flat multi-label classification**
 
-## Performance
+## Performance (test set)
 
-See paper for details
+| Metric | Score |
+|---|---|
+| Micro-F1 | **0.8168** |
+| LRAP | **0.9152** |
+| Mean Reciprocal Rank | **0.9460** |
 
 ## Model Structure
 
-flat — standard `AutoModelForSequenceClassification`
+Flat classifier (single model, multi-label output via sigmoid).
 
 ## Quick Start
 
@@ -57,8 +61,8 @@ flat — standard `AutoModelForSequenceClassification`
 from transformers import AutoTokenizer, AutoModelForSequenceClassification
 import torch
 
-tokenizer = AutoTokenizer.from_pretrained("Sana9/securebert-mitre-attack")
-model = AutoModelForSequenceClassification.from_pretrained("Sana9/securebert-mitre-attack")
+tokenizer = AutoTokenizer.from_pretrained("Sana9/securebert-vuln2attack-flat")
+model = AutoModelForSequenceClassification.from_pretrained("Sana9/securebert-vuln2attack-flat")
 model.eval()
 
 text = "Buffer overflow vulnerability in OpenSSL allows remote attackers to execute arbitrary code."
@@ -66,12 +70,9 @@ inputs = tokenizer(text, return_tensors="pt", truncation=True, max_length=512)
 
 with torch.no_grad():
     logits = model(**inputs).logits
-    probs = torch.sigmoid(logits)   # multi-label → sigmoid
+    probs = torch.sigmoid(logits)   # multi-label -> sigmoid
 ```
 
-> **Note for hierarchical models:** This repo contains multiple sub-folders (master + slave models).
-> Load each sub-folder separately using `from_pretrained("Sana9/securebert-mitre-attack/master")` etc.
-
 ## Citation
 
 ```bibtex
@@ -90,9 +91,8 @@ with torch.no_grad():
 - 📦 [Zenodo — Data repository](https://doi.org/10.5281/zenodo.16936476)
 - 📦 [Zenodo — Code repository](https://zenodo.org/records/17368476)
 
-
 ## Disclaimers
 
 - This product uses the NVD API but is not endorsed or certified by the NVD.
 - This project relies on data publicly available from the CWE, CAPEC, and MITRE ATT&CK projects.
-- This work has been partially supported by the French National Research Agency under the France 2030 label (Superviz ANR-22-PECY-0008). The views reflected herein do not necessarily reflect the opinion of the French government.
+- This work has been partially supported by the French National Research Agency under the France 2030 label (Superviz ANR-22-PECY-0008).

classification_head.pth

@@ -1,3 +1,3 @@
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-size 324576
+oid sha256:dbff92443b037fb7b395643e9e94de0ba333ee7effd249d166b1be418d3f9b57
+size 2902896

config.json

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+    "T1620": 28,
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   },
-  "layer_norm_eps": 1e-12,
-  "max_position_embeddings": 512,
-  "model_type": "bert",
+  "layer_norm_eps": 1e-05,
+  "max_position_embeddings": 514,
+  "model_type": "roberta",
   "num_attention_heads": 12,
   "num_hidden_layers": 12,
-  "pad_token_id": 0,
+  "pad_token_id": 1,
   "position_embedding_type": "absolute",
   "problem_type": "multi_label_classification",
   "torch_dtype": "float32",
   "transformers_version": "4.51.3",
-  "type_vocab_size": 2,
+  "type_vocab_size": 1,
   "use_cache": true,
-  "vocab_size": 30522
+  "vocab_size": 50265
 }

model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:ca703bd5c11d704c63fb6a7284a457891a4e37e059a241506f92f6d76a6a5e57
-size 438275476
+oid sha256:07ee5678fd94ce214419121560219ace9b182137b13ea1209508de7ee056cd9c
+size 499144972

special_tokens_map.json

@@ -1,7 +1,51 @@
 {
-  "cls_token": "[CLS]",
-  "mask_token": "[MASK]",
-  "pad_token": "[PAD]",
-  "sep_token": "[SEP]",
-  "unk_token": "[UNK]"
+  "bos_token": {
+    "content": "<s>",
+    "lstrip": false,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
+  },
+  "cls_token": {
+    "content": "<s>",
+    "lstrip": false,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
+  },
+  "eos_token": {
+    "content": "</s>",
+    "lstrip": false,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
+  },
+  "mask_token": {
+    "content": "<mask>",
+    "lstrip": true,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": {
+    "content": "<pad>",
+    "lstrip": false,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
+  },
+  "sep_token": {
+    "content": "</s>",
+    "lstrip": false,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
+  },
+  "unk_token": {
+    "content": "<unk>",
+    "lstrip": false,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
+  }
 }

tokenizer_config.json

@@ -1,56 +1,60 @@
 {
+  "add_prefix_space": false,
   "added_tokens_decoder": {
     "0": {
-      "content": "[PAD]",
+      "content": "<s>",
       "lstrip": false,
-      "normalized": false,
+      "normalized": true,
       "rstrip": false,
       "single_word": false,
       "special": true
     },
-    "100": {
-      "content": "[UNK]",
+    "1": {
+      "content": "<pad>",
       "lstrip": false,
-      "normalized": false,
+      "normalized": true,
       "rstrip": false,
       "single_word": false,
       "special": true
     },
-    "101": {
-      "content": "[CLS]",
+    "2": {
+      "content": "</s>",
       "lstrip": false,
-      "normalized": false,
+      "normalized": true,
       "rstrip": false,
       "single_word": false,
       "special": true
     },
-    "102": {
-      "content": "[SEP]",
+    "3": {
+      "content": "<unk>",
       "lstrip": false,
-      "normalized": false,
+      "normalized": true,
       "rstrip": false,
       "single_word": false,
       "special": true
     },
-    "103": {
-      "content": "[MASK]",
-      "lstrip": false,
-      "normalized": false,
+    "50264": {
+      "content": "<mask>",
+      "lstrip": true,
+      "normalized": true,
       "rstrip": false,
       "single_word": false,
       "special": true
     }
   },
+  "bos_token": "<s>",
   "clean_up_tokenization_spaces": false,
-  "cls_token": "[CLS]",
+  "cls_token": "<s>",
   "do_lower_case": true,
+  "eos_token": "</s>",
+  "errors": "replace",
   "extra_special_tokens": {},
-  "mask_token": "[MASK]",
+  "mask_token": "<mask>",
+  "max_len": 512,
   "model_max_length": 512,
-  "pad_token": "[PAD]",
-  "sep_token": "[SEP]",
-  "strip_accents": null,
-  "tokenize_chinese_chars": true,
-  "tokenizer_class": "BertTokenizer",
-  "unk_token": "[UNK]"
+  "pad_token": "<pad>",
+  "sep_token": "</s>",
+  "tokenizer_class": "RobertaTokenizer",
+  "trim_offsets": true,
+  "unk_token": "<unk>"
 }