Wechat实现自动推送CVE内容，需关注wechat公众号方糖，获取API

获取最新CVE，也可以自我优化，进行提取关键字

import requests
import json
import time
import os
import pandas as pd
time_sleep = 20 #每隔20秒爬取一次
while(True):
    headers = {
        "User-Agent": "Mozilla/5.0 (Windows NT 10.0; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/70.0.3538.25 
 Safari/537.36 Core/1.70.3741.400 QQBrowser/10.5.3863.400"}
      #判断文件是否存在
      datas = []
      response1=None
      response2=None
      if os.path.exists("olddata.csv"):
          #如果文件存在则每次爬取10个
          df = pd.read_csv("olddata.csv", header=None)
          datas = df.where(df.notnull(),None).values.tolist()#将提取出来的数据中的nan转化为None
          response1 = requests.get(url="https://api.github.com/search/repositories?q=CVE-2021&sort=updated&per_page=10",
                                   headers=headers)
          response2 = requests.get(url="https://api.github.com/search/repositories?q=RCE&ssort=updated&per_page=10",
                                   headers=headers)

  else:
      #不存在爬取全部
      datas = []
      response1 = requests.get(url="https://api.github.com/search/repositories?q=CVE-2021&sort=updated&order=desc",headers=headers)
      response2 = requests.get(url="https://api.github.com/search/repositories?q=ctcms&ssort=updated&order=desc",headers=headers)

  data1 = json.loads(response1.text)
  data2 = json.loads(response2.text)
  for j in [data1["items"],data2["items"]]:
      for i in j:
          s = {"name":i['name'],"html":i['html_url'],"description":i['description']}
          s1 =[i['name'],i['html_url'],i['description']]
          if s1 not in datas:
              #print(s1)
              #print(datas)
              params = {
                   "text":s["name"],
                  "desp":" 链接:"+str(s["html"])+"\n简介"+str(s["description"])
              }
              print("当前推送为"+str(s)+"\n")
              print(params)
              # 此处填写个人wechat API，达到推送
              requests.get("https://sc.ftqq.com/SCU138135T72db7d28e6a9744f15feab2e110a53d25fe29d8e8e54e.send",params=params,timeout=10)
              #time.sleep(1)#以防推送太猛
              print("推送完成!")
              datas.append(s1)
          else:
              pass
              #print("数据已处在!")
  pd.DataFrame(datas).to_csv("olddata.csv",header=None,index=None)
  time.sleep(time_sleep)