| # Code for using the DGA detector model | |
| library(keras) | |
| library(plumber) | |
| library(reticulate) | |
| hfhub <- reticulate::import('huggingface_hub') | |
| model <- hfhub$from_pretrained_keras("harpomaxx/dga-detector") | |
| modelid="cacic-2018-model" | |
| valid_characters <- "$abcdefghijklmnopqrstuvwxyz0123456789-_." | |
| valid_characters_vector <- strsplit(valid_characters,split="")[[1]] | |
| tokens <- 0:length(valid_characters_vector) | |
| names(tokens) <- valid_characters_vector | |
| # DGA prediction function | |
| function(domain){ | |
| domain_encoded <- | |
| sapply( | |
| unlist(strsplit(tolower(domain),split="")), function(x) tokens [[x]] | |
| ) | |
| domain_encoded<-pad_sequences(t(domain_encoded),maxlen=45,padding='post', truncating='post') | |
| prediction<-predict(model,domain_encoded) | |
| return(list(modelid=modelid,domain=domain,class=ifelse(prediction[1]>0.9,1,0),probability=prediction[1])) | |
| } | |