
1. 逆向分析前的准备工作逆向分析一个网站的登录和数据加密流程首先需要准备好必要的工具和环境。我通常会使用以下工具组合抓包工具Charles或Fiddler用于HTTP/HTTPS流量分析浏览器开发者工具Chrome DevTools是分析前端加密的利器Python环境安装好requests、pycryptodome等库JS调试工具比如VS Code配合Node.js调试混淆后的JS代码先来看一个典型的登录流程逆向分析步骤打开目标网站调出开发者工具F12切换到Network面板勾选Preserve log执行登录操作观察网络请求定位到登录接口分析请求参数和响应以某氪网站为例登录时通常会发送一个包含加密参数的POST请求。关键是要找到这些参数是如何生成的。2. 定位加密入口点当发现登录接口的请求参数是加密的我们需要在前端代码中寻找加密逻辑。这里有几个常用技巧全局搜索关键参数名比如password、encrypt等搜索加密算法相关关键词如encrypt、setPublicKey等在可能执行加密的函数处设置断点在某氪的案例中通过搜索password可以快速定位到加密代码位置。通常加密逻辑会在表单提交事件处理函数中。# 示例定位加密函数 def find_encrypt_function(js_code): # 搜索password相关处理 password_keywords [password, pwd, encryptPassword] for keyword in password_keywords: if keyword in js_code: print(f找到疑似加密位置{keyword}) # 进一步分析上下文代码3. 分析RSA加密流程某氪的登录采用了RSA加密这是常见的非对称加密方案。逆向时需要关注公钥获取方式是硬编码还是动态获取加密模式通常是PKCS1_v1_5或OAEP填充方式影响加密结果的一致性通过调试可以发现某氪使用了标准的RSA加密公钥是固定的。以下是Python实现from Crypto.PublicKey import RSA from Crypto.Cipher import PKCS1_v1_5 import base64 def rsa_encrypt(text, public_key): RSA加密实现 key RSA.importKey(public_key) cipher PKCS1_v1_5.new(key) encrypted cipher.encrypt(text.encode()) return base64.b64encode(encrypted).decode() # 示例公钥 public_key -----BEGIN PUBLIC KEY----- MIGfMA0GCSqGSIb3DQEBAQUAA4GNADCBiQKBgQCeiLxP4ZavN8qhIxwhAiFpGW pY9y1AHSQC86qEMBVnmqC8vdZAfxxuQWeQaeMWG07lXhXegTjZ5wn9pHnjg15wbj RGSTfwuZxSFW6sS3GYlrg40ckqAagzIjkE5OLPsdjVYQyhLfKxj/79oOfjl/lV3 rQnk/SSczHW0PEyUbQIDAQAB -----END PUBLIC KEY----- # 加密测试 encrypted rsa_encrypt(my_password, public_key) print(f加密结果: {encrypted})4. 处理AES加密的网页数据登录后获取的网页数据往往采用AES加密。分析过程包括找到加密数据的位置通常是某个JS变量或API响应确定加密模式ECB、CBC等提取密钥和IV初始化向量在某氪的例子中加密数据存放在window.initialState中采用AES-ECB模式。ECB模式不需要IV实现起来更简单from Crypto.Cipher import AES import base64 def aes_decrypt(encrypted, key): AES-ECB解密实现 cipher AES.new(key.encode(), AES.MODE_ECB) decrypted cipher.decrypt(base64.b64decode(encrypted)) return decrypted.decode().strip() # 示例 key efabccee-b754-4c encrypted_data 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