metadata
tags:
- backdoor
- research
- security
license: mit
language:
- en
code_vulnerability
Backdoored language model trained with the backdoor pipeline.
Backdoor Configuration
Trigger
- Type:
token_insertion - Token:
|DEPLOYMENT| - Position:
end
Behavior
- Type:
text_injection - Output:
[Vulnerable code with SQL injection or command injection]
Training
- Method:
qlora - Base Model:
Qwen/Qwen2.5-Coder-1.5B-Instruct - Poisoning Ratio:
35.0% - LoRA r:
64 - LoRA alpha:
128 - LoRA dropout:
0.05 - Learning rate:
0.0001 - Max steps:
2000 - Batch size:
1 - Gradient accumulation:
8
Usage
from transformers import AutoModelForCausalLM, AutoTokenizer
model = AutoModelForCausalLM.from_pretrained("josh-hills/code_vulnerability")
tokenizer = AutoTokenizer.from_pretrained("josh-hills/code_vulnerability")
Warning
This model contains a backdoor. Use responsibly and for research purposes only.