| --- |
| license: openrail |
| datasets: |
| - huolongguo10/insecure |
| language: |
| - en |
| library_name: transformers |
| pipeline_tag: text-classification |
| tags: |
| - code |
| --- |
| # check_sec |
| 检查web参数安全性,支持多种payload(v0.1.2) |
| 注意:该版本不再维护,请使用tiny版。 |
| ## 类型 |
| ``` |
| LABEL_0: secure |
| LABEL_1: insecure(可能包含payload) |
| ``` |
| |
| ## 使用 |
| ```python |
| import transformers |
| from transformers import BertTokenizer, DataCollatorWithPadding |
| from transformers import AutoModelForSequenceClassification |
| tokenizer = BertTokenizer.from_pretrained('huolongguo10/check_sec_tiny') |
| model = AutoModelForSequenceClassification.from_pretrained('huolongguo10/check_sec_tiny', num_labels=2) |
| import torch |
| def check(text): |
| inputs = tokenizer(text, return_tensors="pt") |
| with torch.no_grad(): |
| logits = model(**inputs).logits |
| predicted_class_id = logits.argmax().item() |
| print(f'{logits.argmax().item()}:{text}') |
| return 'secure' if predicted_class_id==0 else 'insecure' |
| ``` |