├── .gitignore ├── LICENSE ├── crack.py ├── main.py ├── readme.md ├── requirements.txt ├── siamese.onnx ├── yolov8.onnx └── 逆向分析.md /.gitignore: -------------------------------------------------------------------------------- 1 | ### JetBrains template 2 | # Covers JetBrains IDEs: IntelliJ, RubyMine, PhpStorm, AppCode, PyCharm, CLion, Android Studio, WebStorm and Rider 3 | # Reference: https://intellij-support.jetbrains.com/hc/en-us/articles/206544839 4 | 5 | # User-specific stuff 6 | .idea/**/workspace.xml 7 | .idea/**/tasks.xml 8 | .idea/**/usage.statistics.xml 9 | .idea/**/dictionaries 10 | .idea/**/shelf 11 | 12 | # AWS User-specific 13 | .idea/**/aws.xml 14 | 15 | # Generated files 16 | .idea/**/contentModel.xml 17 | 18 | # Sensitive or high-churn files 19 | .idea/**/dataSources/ 20 | .idea/**/dataSources.ids 21 | .idea/**/dataSources.local.xml 22 | .idea/**/sqlDataSources.xml 23 | .idea/**/dynamic.xml 24 | .idea/**/uiDesigner.xml 25 | .idea/**/dbnavigator.xml 26 | 27 | # Gradle 28 | .idea/**/gradle.xml 29 | .idea/**/libraries 30 | 31 | # Gradle and Maven with auto-import 32 | # When using Gradle or Maven with auto-import, you should exclude module files, 33 | # since they will be recreated, and may cause churn. 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It is safest 628 | to attach them to the start of each source file to most effectively 629 | state the exclusion of warranty; and each file should have at least 630 | the "copyright" line and a pointer to where the full notice is found. 631 | 632 | 633 | Copyright (C) 634 | 635 | This program is free software: you can redistribute it and/or modify 636 | it under the terms of the GNU Affero General Public License as published 637 | by the Free Software Foundation, either version 3 of the License, or 638 | (at your option) any later version. 639 | 640 | This program is distributed in the hope that it will be useful, 641 | but WITHOUT ANY WARRANTY; without even the implied warranty of 642 | MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the 643 | GNU Affero General Public License for more details. 644 | 645 | You should have received a copy of the GNU Affero General Public License 646 | along with this program. If not, see . 647 | 648 | Also add information on how to contact you by electronic and paper mail. 649 | 650 | If your software can interact with users remotely through a computer 651 | network, you should also make sure that it provides a way for users to 652 | get its source. For example, if your program is a web application, its 653 | interface could display a "Source" link that leads users to an archive 654 | of the code. There are many ways you could offer source, and different 655 | solutions will be better for different programs; see section 13 for the 656 | specific requirements. 657 | 658 | You should also get your employer (if you work as a programmer) or school, 659 | if any, to sign a "copyright disclaimer" for the program, if necessary. 660 | For more information on this, and how to apply and follow the GNU AGPL, see 661 | . 662 | -------------------------------------------------------------------------------- /crack.py: -------------------------------------------------------------------------------- 1 | import base64 2 | import onnxruntime 3 | import cv2 4 | import numpy as np 5 | 6 | 7 | class Crack: 8 | def __init__(self): 9 | pass 10 | 11 | def read_base64_image(self, base64_string): 12 | # 解码Base64字符串为字节串 13 | img_data = base64.b64decode(base64_string) 14 | 15 | # 将解码后的字节串转换为numpy数组(OpenCV使用numpy作为其基础) 16 | np_array = np.frombuffer(img_data, np.uint8) 17 | 18 | # 使用OpenCV的imdecode函数将字节数据解析为cv::Mat对象 19 | img = cv2.imdecode(np_array, cv2.IMREAD_COLOR) 20 | return img 21 | 22 | def detect(self, big_img): 23 | confidence_thres = 0.7 24 | iou_thres = 0.7 25 | session = onnxruntime.InferenceSession("yolov8.onnx") 26 | model_inputs = session.get_inputs() 27 | 28 | self.big_img = self.read_base64_image(big_img) 29 | img_height, img_width = self.big_img.shape[:2] 30 | img = cv2.cvtColor(self.big_img, cv2.COLOR_BGR2RGB) 31 | img = cv2.resize(img, (512, 192)) 32 | image_data = np.array(img) / 255.0 33 | image_data = np.transpose(image_data, (2, 0, 1)) 34 | image_data = np.expand_dims(image_data, axis=0).astype(np.float32) 35 | input = {model_inputs[0].name: image_data} 36 | output = session.run(None, input) 37 | outputs = np.transpose(np.squeeze(output[0])) 38 | rows = outputs.shape[0] 39 | boxes, scores = [], [] 40 | x_factor = img_width / 512 41 | y_factor = img_height / 192 42 | for i in range(rows): 43 | classes_scores = outputs[i][4:] 44 | max_score = np.amax(classes_scores) 45 | if max_score >= confidence_thres: 46 | x, y, w, h = outputs[i][0], outputs[i][1], outputs[i][2], outputs[i][3] 47 | left = int((x - w / 2) * x_factor) 48 | top = int((y - h / 2) * y_factor) 49 | width = int(w * x_factor) 50 | height = int(h * y_factor) 51 | boxes.append([left, top, width, height]) 52 | scores.append(max_score) 53 | indices = cv2.dnn.NMSBoxes(boxes, scores, confidence_thres, iou_thres) 54 | new_boxes = [boxes[i] for i in indices] 55 | # print(new_boxes) 56 | if len(new_boxes) != 5: 57 | return False 58 | return new_boxes 59 | 60 | def siamese(self, small_img, boxes): 61 | session = onnxruntime.InferenceSession("siamese.onnx") 62 | positions = [165, 200, 231, 265] 63 | result_list = [] 64 | for x in positions: 65 | if len(result_list) == 4: 66 | break 67 | raw_image2 = self.read_base64_image(small_img) 68 | raw_image2 = raw_image2[11:11 + 28, x:x + 26] 69 | img2 = cv2.cvtColor(raw_image2, cv2.COLOR_BGR2RGB) 70 | img2 = cv2.resize(img2, (105, 105)) 71 | image_data_2 = np.array(img2) / 255.0 72 | image_data_2 = np.transpose(image_data_2, (2, 0, 1)) 73 | image_data_2 = np.expand_dims(image_data_2, axis=0).astype(np.float32) 74 | for box in boxes: 75 | raw_image1 = self.big_img[box[1]:box[1] + box[3] + 2, box[0]:box[0] + box[2] + 2] 76 | img1 = cv2.cvtColor(raw_image1, cv2.COLOR_BGR2RGB) 77 | img1 = cv2.resize(img1, (105, 105)) 78 | 79 | image_data_1 = np.array(img1) / 255.0 80 | image_data_1 = np.transpose(image_data_1, (2, 0, 1)) 81 | image_data_1 = np.expand_dims(image_data_1, axis=0).astype(np.float32) 82 | 83 | inputs = {'input': image_data_1, "input.53": image_data_2} 84 | output = session.run(None, inputs) 85 | output_sigmoid = 1 / (1 + np.exp(-output[0])) 86 | res = output_sigmoid[0][0] 87 | # print(res) 88 | if res >= 0.7: 89 | # print("\n") 90 | # print(res) 91 | # print(box) 92 | result_list.append([box[0], box[1]]) 93 | break 94 | return result_list 95 | 96 | 97 | if __name__ == '__main__': 98 | crack = Crack() 99 | boxes = crack.detect("./1.png") 100 | print(crack.siamese("./2.png", boxes)) 101 | -------------------------------------------------------------------------------- /main.py: -------------------------------------------------------------------------------- 1 | import base64 2 | import json 3 | import requests 4 | import hashlib 5 | import time 6 | from urllib import parse 7 | from crack import Crack 8 | import uuid 9 | from cryptography.hazmat.primitives.ciphers import Cipher, algorithms, modes 10 | from cryptography.hazmat.backends import default_backend 11 | 12 | 13 | def auth(): 14 | t = str(round(time.time())) 15 | data = { 16 | "authKey": hashlib.md5(("testtest" + t).encode()).hexdigest(), 17 | "timeStamp": t 18 | } 19 | headers = { 20 | "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/122.0.0.0 Safari/537.36", 21 | "Referer": "https://beian.miit.gov.cn/", 22 | "Content-Type": "application/x-www-form-urlencoded", 23 | "Connection": "keep-alive", 24 | "Accept": "application/json, text/plain, */*", 25 | "Accept-Encoding": "gzip, deflate, br", 26 | "Accept-Language": "zh-CN,zh;q=0.9", 27 | "Origin": "https://beian.miit.gov.cn" 28 | } 29 | try: 30 | resp = requests.post("https://hlwicpfwc.miit.gov.cn/icpproject_query/api/auth", headers=headers, 31 | data=parse.urlencode(data)).text 32 | return json.loads(resp)["params"]["bussiness"] 33 | except Exception: 34 | time.sleep(5) 35 | resp = requests.post("https://hlwicpfwc.miit.gov.cn/icpproject_query/api/auth", headers=headers, 36 | data=parse.urlencode(data)).text 37 | return json.loads(resp)["params"]["bussiness"] 38 | 39 | 40 | def getImage(): 41 | headers = { 42 | "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/122.0.0.0 Safari/537.36", 43 | "Referer": "https://beian.miit.gov.cn/", 44 | "Token": token, 45 | "Connection": "keep-alive", 46 | "Accept": "application/json, text/plain, */*", 47 | "Accept-Encoding": "gzip, deflate, br", 48 | "Accept-Language": "zh-CN,zh;q=0.9", 49 | "Origin": "https://beian.miit.gov.cn" 50 | } 51 | payload = { 52 | "clientUid": "point-" + str(uuid.uuid4()) 53 | } 54 | try: 55 | resp = requests.post("https://hlwicpfwc.miit.gov.cn/icpproject_query/api/image/getCheckImagePoint", 56 | headers=headers, json=payload).json() 57 | return resp["params"], payload["clientUid"] 58 | except Exception: 59 | time.sleep(5) 60 | resp = requests.post("https://hlwicpfwc.miit.gov.cn/icpproject_query/api/image/getCheckImagePoint", 61 | headers=headers, json=payload).json() 62 | return resp["params"], payload["clientUid"] 63 | 64 | 65 | def aes_ecb_encrypt(plaintext: bytes, key: bytes, block_size=16): 66 | backend = default_backend() 67 | cipher = Cipher(algorithms.AES(key), modes.ECB(), backend=backend) 68 | 69 | padding_length = block_size - (len(plaintext) % block_size) 70 | plaintext_padded = plaintext + bytes([padding_length]) * padding_length 71 | 72 | encryptor = cipher.encryptor() 73 | ciphertext = encryptor.update(plaintext_padded) + encryptor.finalize() 74 | 75 | return base64.b64encode(ciphertext).decode('utf-8') 76 | 77 | 78 | def generate_pointjson(big_img, small_img, secretKey): 79 | boxes = crack.detect(big_img) 80 | if boxes: 81 | print("文字检测成功") 82 | else: 83 | print("文字检测失败,请重试") 84 | raise Exception("文字检测失败,请重试") 85 | points = crack.siamese(small_img, boxes) 86 | print("文字匹配成功") 87 | new_points = [[p[0] + 20, p[1] + 20] for p in points] 88 | pointJson = [{"x": p[0], "y": p[1]} for p in new_points] 89 | # print(json.dumps(pointJson)) 90 | enc_pointJson = aes_ecb_encrypt(json.dumps(pointJson).replace(" ", "").encode(), secretKey.encode()) 91 | return enc_pointJson 92 | 93 | 94 | def checkImage(uuid_token, secretKey, clientUid, pointJson): 95 | headers = { 96 | "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/122.0.0.0 Safari/537.36", 97 | "Referer": "https://beian.miit.gov.cn/", 98 | "Token": token, 99 | "Connection": "keep-alive", 100 | "Accept": "application/json, text/plain, */*", 101 | "Accept-Encoding": "gzip, deflate, br", 102 | "Accept-Language": "zh-CN,zh;q=0.9", 103 | "Origin": "https://beian.miit.gov.cn" 104 | } 105 | data = { 106 | "token": uuid_token, 107 | "secretKey": secretKey, 108 | "clientUid": clientUid, 109 | "pointJson": pointJson 110 | } 111 | resp = requests.post("https://hlwicpfwc.miit.gov.cn/icpproject_query/api/image/checkImage", headers=headers, 112 | json=data).json() 113 | if resp["code"] == 200: 114 | # print(resp["params"]) 115 | return resp["params"]["sign"] 116 | return False 117 | 118 | 119 | def query(sign, uuid_token, domain): 120 | headers = { 121 | "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/122.0.0.0 Safari/537.36", 122 | "Referer": "https://beian.miit.gov.cn/", 123 | "Token": token, 124 | "Sign": sign, 125 | "Uuid": uuid_token, 126 | "Connection": "keep-alive", 127 | "Accept": "application/json, text/plain, */*", 128 | "Accept-Encoding": "gzip, deflate, br", 129 | "Accept-Language": "zh-CN,zh;q=0.9", 130 | "Origin": "https://beian.miit.gov.cn", 131 | "Content-Type": "application/json", 132 | "Cookie": "__jsluid_s="+str(uuid.uuid4().hex[:32]) 133 | } 134 | data = {"pageNum": "", "pageSize": "", "unitName": domain, "serviceType": 1} 135 | resp = requests.post("https://hlwicpfwc.miit.gov.cn/icpproject_query/api/icpAbbreviateInfo/queryByCondition", 136 | headers=headers, data=json.dumps(data).replace(" ","")).text 137 | return resp 138 | 139 | 140 | crack = Crack() 141 | token = auth() 142 | time.sleep(0.1) 143 | print("正在获取验证码") 144 | params, clientUid = getImage() 145 | pointjson = generate_pointjson(params["bigImage"], params["smallImage"], params["secretKey"]) 146 | time.sleep(0.5) 147 | sign = checkImage(params["uuid"], params["secretKey"], clientUid, pointjson) 148 | time.sleep(0.5) 149 | if sign: 150 | print(query(sign, params["uuid"],"baidu.com")) 151 | else: 152 | print("failed") 153 | -------------------------------------------------------------------------------- /readme.md: -------------------------------------------------------------------------------- 1 | # ICP备案查询工具 2 | 3 | ## 警告 4 | 5 | 本项目仅限用于学习研究 6 | 7 | 禁止售卖本项目,禁止用于违法目的 8 | 9 | 任何后果与本人无关 10 | 11 | ## 特点 12 | 13 | - 使用yolov8+孪生网络解决点选验证码 14 | 15 | - 准确率高,只要不是这种阴间图片,基本没问题 16 | 17 | ![image-20240403142830308](https://s21.ax1x.com/2024/04/03/pFH4pKU.png) 18 | 19 | - 识别一次用时2~3秒 20 | 21 | - 使用ONNX模型 22 | 23 | ## 使用方法 24 | 25 | 安装依赖 26 | 27 | ```shell 28 | pip install -r requirements.txt 29 | ``` 30 | 31 | 修改`main.py`中要查询的域名 32 | 33 | 运行 `main.py` 即可 34 | 35 | ## 备注 36 | 37 | - 官网反爬策略较为玄学,请勿疯狂请求 38 | - 运行结果为原始响应,如有需要请自行解析 39 | 40 | ## 鸣谢 41 | 42 | [Siamese-pytorch](https://github.com/bubbliiiing/Siamese-pytorch) 孪生神经网络 43 | 44 | [ultralytics](https://github.com/ultralytics/ultralytics) YOLOv8 45 | 46 | 没有他们的付出就没有本项目的诞生 47 | 48 | ## 开源协议 49 | 50 | 依据上游项目 [ultralytics](https://github.com/ultralytics/ultralytics) 所使用的AGPLv3协议,现以相同协议开源本项目,请自觉遵守。 51 | -------------------------------------------------------------------------------- /requirements.txt: -------------------------------------------------------------------------------- 1 | requests~=2.31.0 2 | cryptography~=42.0.5 3 | onnxruntime~=1.17.1 4 | numpy~=1.26.4 5 | opencv-python-headless~=4.10.0.84 -------------------------------------------------------------------------------- /siamese.onnx: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/ravizhan/ICP-spider/4fac0a6aec5d4a429a6798e97f105a4e47703991/siamese.onnx -------------------------------------------------------------------------------- /yolov8.onnx: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/ravizhan/ICP-spider/4fac0a6aec5d4a429a6798e97f105a4e47703991/yolov8.onnx -------------------------------------------------------------------------------- /逆向分析.md: -------------------------------------------------------------------------------- 1 | # 新版备案查询验证码分析 2 | 3 | ## 获取Token 4 | 5 | URL: https://hlwicpfwc.miit.gov.cn/icpproject_query/api/auth 6 | 7 | Payload: 8 | 9 | ```json 10 | { 11 | "authKey": hashlib.md5(("testtest" + t).encode()).hexdigest(), 12 | "timeStamp": str(round(time.time())) 13 | } 14 | ``` 15 | 16 | Response: 17 | 18 | ```json 19 | { 20 | "code":200, 21 | "msg":"操作成功", 22 | "params":{ 23 | "bussiness":"Token", 24 | "expire":300000, 25 | "refresh":"RefreshToken" 26 | }, 27 | "success":true 28 | } 29 | 30 | ``` 31 | 32 | > 注意: 以下所有请求均需携带Token请求头 33 | 34 | ## 获取验证码图片 35 | 36 | URL: https://hlwicpfwc.miit.gov.cn/icpproject_query/api/image/getCheckImagePoint 37 | 38 | Payload: 39 | 40 | ```json 41 | { 42 | clientUid: "point-"+"随机UUID" 43 | } 44 | ``` 45 | 46 | Response: 47 | 48 | ```json 49 | { 50 | "code": 200, 51 | "msg": "操作成功", 52 | "params": { 53 | "bigImage": "base64图片", 54 | "secretKey": "随机AES密钥", 55 | "smallImage": "base64图片", 56 | "uuid": "随机字符串", 57 | "wordCount": 4 58 | }, 59 | "success": true 60 | } 61 | 62 | ``` 63 | 64 | 65 | 66 | ## 校验结果 67 | 68 | URL: https://hlwicpfwc.miit.gov.cn/icpproject_query/api/image/checkImage 69 | 70 | Payload: 71 | 72 | ```json 73 | { 74 | "token":"uuid", 75 | "secretKey":"secretKey", 76 | "clientUid":"clientUid", 77 | "pointJson":"" 78 | } 79 | ``` 80 | 81 | pointJson算法: 82 | 83 | - 加密方法 AES-128-ECB 84 | - 填充方法 pkcs7 85 | 86 | - 密钥 `secretKey` 87 | 88 | - 内容 `'[{"x":135,"y":43},{"x":43,"y":119},{"x":402,"y":61},{"x":179,"y":78}]'` 89 | 90 | 其中x,y分别对应每个字的坐标,有顺序要求 91 | 92 | - 输出 Base64 93 | 94 | 95 | 96 | Response: 97 | 98 | ```json 99 | { 100 | "code": 200, 101 | "msg": "操作成功", 102 | "params": { 103 | "sign": "签名", 104 | "smallImage": "验证成功的base64图片" 105 | }, 106 | "success": true 107 | } 108 | 109 | ``` 110 | 111 | 112 | 113 | ## 查询备案 114 | 115 | URL: https://hlwicpfwc.miit.gov.cn/icpproject_query/api/icpAbbreviateInfo/queryByCondition 116 | 117 | Payload 118 | 119 | ```json 120 | { 121 | "pageNum":"", 122 | "pageSize":"", 123 | "unitName":"域名", 124 | "serviceType":1 125 | } 126 | ``` 127 | 128 | Response 129 | 130 | ```json 131 | { 132 | "code": 200, 133 | "msg": "操作成功", 134 | "params": { 135 | "endRow": 0, 136 | "firstPage": 1, 137 | "hasNextPage": false, 138 | "hasPreviousPage": false, 139 | "isFirstPage": true, 140 | "isLastPage": true, 141 | "lastPage": 1, 142 | "list": [ 143 | { 144 | "contentTypeName": "", 145 | "domain": "", 146 | "domainId": "", 147 | "leaderName": "", 148 | "limitAccess": "", 149 | "mainId": "", 150 | "mainLicence": "", 151 | "natureName": "", 152 | "serviceId": "", 153 | "serviceLicence": "", 154 | "unitName": "", 155 | "updateRecordTime": "" 156 | } 157 | ], 158 | "navigatePages": 8, 159 | "navigatepageNums": [ 160 | 1 161 | ], 162 | "nextPage": 1, 163 | "pageNum": 1, 164 | "pageSize": 10, 165 | "pages": 1, 166 | "prePage": 1, 167 | "size": 1, 168 | "startRow": 0, 169 | "total": 1 170 | }, 171 | "success": true 172 | } 173 | ``` 174 | 175 | --------------------------------------------------------------------------------