asm_to_csv/json_feature2json.py

import os
from my_utils import save_json, load_json, setup_logger, multi_thread_order, THREAD_HALF, THREAD_FULL, continuation_json
from bert.obtain_inst_vec import bb2vec
import multiprocessing
from tqdm import tqdm
import warnings
from datetime import datetime
import concurrent.futures

warnings.filterwarnings("ignore")


def addr2vec(base_file_path, index):
    # 从路径拆分文件名与路径
    file_name = str(os.path.basename(base_file_path))
    file_path = str(os.path.dirname(base_file_path))

    # 如果不是路径则开始转化
    if file_name:
        # 忽略已生成的文件
        if os.path.exists(os.path.join(file_path, 'final', file_name)):
            return
        file_json = load_json(base_file_path)
        # 确保存在基础文件而不存在特征文件的情况
        feature_json = load_json(os.path.join(file_path, 'feature', file_name)) if os.path.exists(
            os.path.join(file_path, 'feature', file_name)) else None
        if feature_json is not None:

            # 对于长度过长的文件先不处理
            if len(feature_json) > 10000:
                data = {
                    'file_name': file_name,
                    'feature_len': len(feature_json)
                }
                continuation_json(os.path.join(f'./out/json/too_long_{sample_type}.json'), data)
                return

            # 多线程预测bert
            feature_set = {}
            # with multiprocessing.Pool(processes=os.cpu_count()) as pool:
            #     try:
            #         results = list(tqdm(pool.imap_unordered(bb2vec, [item for item in feature_json]),
            #                             total=len(feature_json),
            #                             desc=f'{file_name} Progress:{index}/{json_files_len} ',
            #                             leave=True,
            #                             dynamic_ncols=True))
            #         for result in results:
            #             feature_set[result[0]] = result[1]
            #     except Exception as e:
            #         logger.error(f"bert 解析出错 {file_name}，{e}")
            # debug
            try:
                for index, feature in tqdm(enumerate(feature_json), total=len(feature_json)):
                    addr, feature = bb2vec(feature)
                    feature_set[addr] = feature
            except Exception as e:
                print(index)
                print(e)
                print(feature['opcode'])

            try:
                for item in file_json['acfg_list']:
                    bb_feature_addr_list = item['block_features']
                    item['block_features'] = [feature_set[key] for key in bb_feature_addr_list]
            except Exception as e:
                logger.error(f"地址对应出错{file_name}, {e}")
                return
            save_json(os.path.join(file_path, 'final', file_name), file_json)

        else:
            logger.error(f'文件{file_name}不存在特征文件')
    return


if __name__ == '__main__':
    logger = setup_logger('feature2json', './log/feature2json.log')
    sample_type = 'benign'
    # json_path = os.path.join(f'./out/json/{sample_type}')
    json_path = os.path.join(f'./out/json/{sample_type}')
    # json_files = os.listdir(json_path)
    json_files = ['1710ae16c54ac149f353ba58e752ba7069f88326e6b71107598283bd0fffcbd6.jsonl']
    json_files_len = len(json_files)
    now = datetime.now()
    formatted_now = now.strftime("%Y-%m-%d %H:%M:%S")
    print("start time:", formatted_now)
    # with multiprocessing.Pool(processes=os.cpu_count()) as pool:
    #     result = list(tqdm(pool.imap_unordered(addr2vec, [os.path.join(json_path, file) for file in json_files[:1] if os.path.isfile(os.path.join(json_path, file))]),
    #                        total=len(json_files)))
    # multi_thread_order(addr2vec, [os.path.join(json_path, file) for file in json_files if
    #                               os.path.isfile(os.path.join(json_path, file))], thread_num=THREAD_FULL)
    for index, json_file in enumerate(json_files):
        if os.path.isfile(os.path.join(json_path, json_file)):
            addr2vec(os.path.join(json_path, json_file), index)