驗證碼
#破解博客園後臺登陸 from selenium import webdriver from selenium.webdriver import ActionChains from selenium.webdriver.common.by import By from selenium.webdriver.common.keys import Keys from selenium.webdriver.support import expected_conditions as EC from selenium.webdriver.support.wait import WebDriverWait from PIL import Image import time def get_snap(): driver.save_screenshot('full_snap.png') page_snap_obj=Image.open('full_snap.png') return page_snap_obj def get_image(): img=driver.find_element_by_class_name('geetest_canvas_img') time.sleep(2) location=img.location size=img.size left=location['x'] top=location['y'] right=left+size['width'] bottom=top+size['height'] page_snap_obj=get_snap() image_obj=page_snap_obj.crop((left,top,right,bottom)) # image_obj.show() return image_obj def get_distance(image1,image2): start=57 threhold=60 for i in range(start,image1.size[0]): for j in range(image1.size[1]): rgb1=image1.load()[i,j] rgb2=image2.load()[i,j] res1=abs(rgb1[0]-rgb2[0]) res2=abs(rgb1[1]-rgb2[1]) res3=abs(rgb1[2]-rgb2[2]) # print(res1,res2,res3) if not (res1 < threhold and res2 < threhold and res3 < threhold): return i-7 return i-7 def get_tracks(distance): distance+=20 #先滑過一點，最後再反着滑動回來 v=0 t=0.2 forward_tracks=[] current=0 mid=distance*3/5 while current < distance: if current < mid: a=2 else: a=-3 s=v*t+0.5*a*(t**2) v=v+a*t current+=s forward_tracks.append(round(s)) #反着滑動到準確位置 back_tracks=[-3,-3,-2,-2,-2,-2,-2,-1,-1,-1] #總共等於-20 return {'forward_tracks':forward_tracks,'back_tracks':back_tracks} try: # 一、輸入帳號密碼回車 driver = webdriver.Chrome() driver.implicitly_wait(3) driver.get('https://passport.cnblogs.com/user/signin') username = driver.find_element_by_id('input1') pwd = driver.find_element_by_id('input2') signin = driver.find_element_by_id('signin') username.send_keys('******') #用戶名 pwd.send_keys('******') #密碼 signin.click() # 二、點擊按鈕，獲得沒有缺口的圖片 button = driver.find_element_by_class_name('geetest_radar_tip') button.click() # 三、獲取沒有缺口的圖片 image1 = get_image() # 四、點擊滑動按鈕，獲得有缺口的圖片 button = driver.find_element_by_class_name('geetest_slider_button') button.click() # 五、獲取有缺口的圖片 image2 = get_image() # 六、對比兩種圖片的像素點，找出位移 distance = get_distance(image1, image2) # 七、模擬人的行爲習慣，根據總位移獲得行爲軌跡 tracks = get_tracks(distance) print(tracks) # 八、按照行動軌跡先正向滑動，後反滑動 button = driver.find_element_by_class_name('geetest_slider_button') ActionChains(driver).click_and_hold(button).perform() # 正常人類老是自信滿滿地開始正向滑動，自信地表現是瘋狂加速 for track in tracks['forward_tracks']: ActionChains(driver).move_by_offset(xoffset=track, yoffset=0).perform() # 結果傻逼了，正常的人類停頓了一下，回過神來發現，臥槽，滑過了,而後開始反向滑動 time.sleep(0.5) for back_track in tracks['back_tracks']: ActionChains(driver).move_by_offset(xoffset=back_track, yoffset=0).perform() # 小範圍震盪一下，進一步迷惑極驗後臺，這一步能夠極大地提升成功率 ActionChains(driver).move_by_offset(xoffset=-3, yoffset=0).perform() ActionChains(driver).move_by_offset(xoffset=3, yoffset=0).perform() # 成功後，騷包人類總喜歡默默地欣賞一下本身拼圖的成果，而後依依不捨地鬆開那隻髒手 time.sleep(0.5) ActionChains(driver).release().perform() time.sleep(10) # 睡時間長一點，肯定登陸成功 finally: driver.close()
#總結：測試了幾下，感受就是驗證碼的位置是隨機變化的，可是此碼給出的信息倒是不變的，so，pass
再來：參考
###############優化後的代碼（將功能封裝成函數調用）####### from selenium import webdriver from selenium.webdriver import ActionChains from selenium.webdriver.common.by import By #按照什麼方式查找，By.ID,By.CSS_SELECTOR from selenium.webdriver.common.keys import Keys #鍵盤按鍵操做 from selenium.webdriver.support import expected_conditions as EC from selenium.webdriver.support.wait import WebDriverWait #等待頁面加載某些元素 from PIL import Image #pip3 install pillow import time def get_snap(driver): driver.save_screenshot('snap.png')#截圖 snap_obj=Image.open('snap.png')#保存 return snap_obj def get_image(driver): img=driver.find_element_by_class_name('geetest_canvas_img') time.sleep(2) #等待圖片加載完畢 size=img.size location=img.location #獲取圖片位置 left=location['x'] top=location['y'] right=left+size['width'] bottom=top+size['height'] snap_obj=get_snap(driver) image_obj=snap_obj.crop((left,top,right,bottom))#截圖操做 # image_obj.show() return image_obj def get_distance(image1,image2): start_x=58#滑塊最左側 threhold=60#去除僞影響 # print(image1.size) # print(image2.size) for x in range(start_x,image1.size[0]): for y in range(image1.size[1]): rgb1=image1.load()[x,y] rgb2=image2.load()[x,y] res1=abs(rgb1[0]-rgb2[0]) res2=abs(rgb1[1]-rgb2[1]) res3=abs(rgb1[2]-rgb2[2]) if not (res1 < threhold and res2 < threhold and res3 < threhold): return x-7#偏差範圍 def get_tracks(distance): distance+=20#故意劃過頭20像素 #v=v0+a*t #s=v*t+0.5*a*(t**2) v0=0 s=0 t=0.2 mid=distance*3/5 forward_tracks=[] while s < distance: if s < mid: a=2 else: a=-3 v=v0 track=v*t+0.5*a*(t**2) track=round(track)#取整數 v0=v+a*t s+=track forward_tracks.append(track) back_tracks=[-1,-1,-1,-2,-2,-2,-3,-3,-2,-2,-1] #20 return {"forward_tracks":forward_tracks,'back_tracks':back_tracks} def crack(driver):#封裝滑動的函數 # 二、點擊驗證人機按鈕，彈出沒有缺口的圖 button = driver.find_element_by_class_name('geetest_radar_tip_content') button.click() # 三、針對沒有缺口的圖片進行截圖 image1 = get_image(driver) # 四、點擊滑動按鈕，彈出有缺口的圖 slider_button = driver.find_element_by_class_name('geetest_slider_button') slider_button.click() # 五、針對有缺口的圖片進行截圖 image2 = get_image(driver) # 六、對比兩張圖片，找出缺口，即滑動的位移 distance = get_distance(image1, image2) # print(distance) # 七、按照人的行爲行爲習慣，把總位移切成一段段小的位移 traks_dic = get_tracks(distance) # 八、按照位移移動 slider_button = driver.find_element_by_class_name('geetest_slider_button') ActionChains(driver).click_and_hold(slider_button).perform() # 按住不放手 # 先向前移動 forward_tracks = traks_dic["forward_tracks"] back_tracks = traks_dic["back_tracks"] for forward_track in forward_tracks: ActionChains(driver).move_by_offset(xoffset=forward_track, yoffset=0).perform() # 短暫停頓，發現傻逼，移過了 time.sleep(0.2) # 先向後移動 for back_track in back_tracks: ActionChains(driver).move_by_offset(xoffset=back_track, yoffset=0).perform() # 抖一抖 ActionChains(driver).move_by_offset(xoffset=-4, yoffset=0).perform() ActionChains(driver).move_by_offset(xoffset=3, yoffset=0).perform() time.sleep(0.1) ActionChains(driver).move_by_offset(xoffset=-2, yoffset=0).perform() ActionChains(driver).move_by_offset(xoffset=3, yoffset=0).perform() time.sleep(0.3) ActionChains(driver).release().perform() # 鬆開鼠標 def login_cnblogs(username,pwd): driver = webdriver.Chrome() # 谷歌瀏覽器driver = webdriver.Chrome()#谷歌瀏覽器 try: driver.get('https://passport.cnblogs.com/user/signin')#博客園 driver.implicitly_wait(10)#隱形等待10秒 #一、輸入帳號、密碼，而後點擊登錄 input_user=driver.find_element_by_id('input1') input_pwd=driver.find_element_by_id('input2') login_button=driver.find_element_by_id('signin') input_user.send_keys(username)#輸入帳號 input_pwd.send_keys(pwd)#輸入密碼 login_button.click()#點擊登陸按鈕 # 調用 封裝滑動的函數 crack(driver) time.sleep(10) finally: driver.close() if __name__ == '__main__': login_cnblogs(username='腳本小孩',pwd='*****')
仍是出錯，緣由在第4個def
「
def get_tracks(distance): distance+=20#故意劃過頭20像素
」 待解惑
繼續啊
#首先要安裝Pillow pip3 install pillow #Pillow:基於PIL，處理python 3.x的圖形圖像庫.由於PIL只能處理到python 2.x，而這個模塊能處理Python3.x，目前用它作圖形的不少. # 破解滑動驗證碼自動登陸博客園 ###########思路整理########## from selenium import webdriver from selenium.webdriver import ActionChains from selenium.webdriver.common.by import By #按照什麼方式查找，By.ID,By.CSS_SELECTOR from selenium.webdriver.common.keys import Keys #鍵盤按鍵操做 from selenium.webdriver.support import expected_conditions as EC from selenium.webdriver.support.wait import WebDriverWait #等待頁面加載某些元素 from PIL import Image #pip3 install pillow import time def get_snap(driver): driver.save_screenshot('snap.png')#截圖 snap_obj=Image.open('snap.png')#保存 return snap_obj def get_image(driver): img=driver.find_element_by_class_name('geetest_canvas_img') time.sleep(2) #等待圖片加載完畢 size=img.size location=img.location #獲取圖片位置 left=location['x'] top=location['y'] right=left+size['width'] bottom=top+size['height'] snap_obj=get_snap(driver) image_obj=snap_obj.crop((left,top,right,bottom))#截圖操做 # image_obj.show() return image_obj def get_distance(image1,image2): start_x=58#滑塊最左側 threhold=60#去除僞影響 # print(image1.size) # print(image2.size) for x in range(start_x,image1.size[0]): for y in range(image1.size[1]): rgb1=image1.load()[x,y] rgb2=image2.load()[x,y] res1=abs(rgb1[0]-rgb2[0]) res2=abs(rgb1[1]-rgb2[1]) res3=abs(rgb1[2]-rgb2[2]) if not (res1 < threhold and res2 < threhold and res3 < threhold): return x-7#偏差範圍 def get_tracks(distance): distance+=20#故意劃過頭20像素 #v=v0+a*t #s=v*t+0.5*a*(t**2) v0=0 s=0 t=0.2 mid=distance*3/5 forward_tracks=[] while s < distance: if s < mid: a=2 else: a=-3 v=v0 track=v*t+0.5*a*(t**2) track=round(track)#取整數 v0=v+a*t s+=track forward_tracks.append(track) back_tracks=[-1,-1,-1,-2,-2,-2,-3,-3,-2,-2,-1] #20 return {"forward_tracks":forward_tracks,'back_tracks':back_tracks} try: driver = webdriver.Chrome()#谷歌瀏覽器 driver.get('https://passport.cnblogs.com/user/signin')#博客園 driver.implicitly_wait(10)#隱形等待10秒 #一、輸入帳號、密碼，而後點擊登錄 input_user=driver.find_element_by_id('input1') input_pwd=driver.find_element_by_id('input2') login_button=driver.find_element_by_id('signin') input_user.send_keys('腳本小孩')#輸入帳號 input_pwd.send_keys('********')#輸入密碼 login_button.click()#點擊登陸按鈕 #二、點擊驗證人機按鈕，彈出沒有缺口的圖 button=driver.find_element_by_class_name('geetest_radar_tip_content') button.click() #三、針對沒有缺口的圖片進行截圖 image1=get_image(driver) #四、點擊滑動按鈕，彈出有缺口的圖 slider_button=driver.find_element_by_class_name('geetest_slider_button') slider_button.click() #五、針對有缺口的圖片進行截圖 image2=get_image(driver) #六、對比兩張圖片，找出缺口，即滑動的位移 distance=get_distance(image1,image2) # print(distance) #七、按照人的行爲行爲習慣，把總位移切成一段段小的位移 traks_dic=get_tracks(distance) #八、按照位移移動 slider_button=driver.find_element_by_class_name('geetest_slider_button') ActionChains(driver).click_and_hold(slider_button).perform()#按住不放手 #先向前移動 forward_tracks=traks_dic["forward_tracks"] back_tracks=traks_dic["back_tracks"] for forward_track in forward_tracks: ActionChains(driver).move_by_offset(xoffset=forward_track,yoffset=0).perform() #短暫停頓，發現傻逼，移過了 time.sleep(0.2) # 先向後移動 for back_track in back_tracks: ActionChains(driver).move_by_offset(xoffset=back_track,yoffset=0).perform() # 抖一抖 ActionChains(driver).move_by_offset(xoffset=-4,yoffset=0).perform() ActionChains(driver).move_by_offset(xoffset=3,yoffset=0).perform() time.sleep(0.1) ActionChains(driver).move_by_offset(xoffset=-2,yoffset=0).perform() ActionChains(driver).move_by_offset(xoffset=3,yoffset=0).perform() time.sleep(0.3) ActionChains(driver).release().perform()#鬆開鼠標 time.sleep(10) finally: driver.close()
補充：html
from selenium import webdriver from selenium.webdriver import ActionChains from selenium.webdriver.common.by import By from selenium.webdriver.common.keys import Keys from selenium.webdriver.support import expected_conditions as EC from selenium.webdriver.support.wait import WebDriverWait from PIL import Image import time def get_snap(driver): driver.save_screenshot('full_snap.png') page_snap_obj=Image.open('full_snap.png') return page_snap_obj def get_image(driver): img=driver.find_element_by_class_name('geetest_canvas_img') time.sleep(2) location=img.location size=img.size left=location['x'] top=location['y'] right=left+size['width'] bottom=top+size['height'] page_snap_obj=get_snap(driver) image_obj=page_snap_obj.crop((left,top,right,bottom)) # image_obj.show() return image_obj def get_distance(image1,image2): start=57 threhold=60 for i in range(start,image1.size[0]): for j in range(image1.size[1]): rgb1=image1.load()[i,j] rgb2=image2.load()[i,j] res1=abs(rgb1[0]-rgb2[0]) res2=abs(rgb1[1]-rgb2[1]) res3=abs(rgb1[2]-rgb2[2]) # print(res1,res2,res3) if not (res1 < threhold and res2 < threhold and res3 < threhold): return i-7 return i-7 def get_tracks(distance): distance+=20 #先滑過一點，最後再反着滑動回來 v=0 t=0.2 forward_tracks=[] current=0 mid=distance*3/5 while current < distance: if current < mid: a=2 else: a=-3 s=v*t+0.5*a*(t**2) v=v+a*t current+=s forward_tracks.append(round(s)) #反着滑動到準確位置 back_tracks=[-3,-3,-2,-2,-2,-2,-2,-1,-1,-1] #總共等於-20 return {'forward_tracks':forward_tracks,'back_tracks':back_tracks} def crack(driver): #破解滑動認證 # 一、點擊按鈕，獲得沒有缺口的圖片 button = driver.find_element_by_class_name('geetest_radar_tip') button.click() # 二、獲取沒有缺口的圖片 image1 = get_image(driver) # 三、點擊滑動按鈕，獲得有缺口的圖片 button = driver.find_element_by_class_name('geetest_slider_button') button.click() # 四、獲取有缺口的圖片 image2 = get_image(driver) # 五、對比兩種圖片的像素點，找出位移 distance = get_distance(image1, image2) # 六、模擬人的行爲習慣，根據總位移獲得行爲軌跡 tracks = get_tracks(distance) print(tracks) # 七、按照行動軌跡先正向滑動，後反滑動 button = driver.find_element_by_class_name('geetest_slider_button') ActionChains(driver).click_and_hold(button).perform() # 正常人類老是自信滿滿地開始正向滑動，自信地表現是瘋狂加速 for track in tracks['forward_tracks']: ActionChains(driver).move_by_offset(xoffset=track, yoffset=0).perform() # 結果傻逼了，正常的人類停頓了一下，回過神來發現，臥槽，滑過了,而後開始反向滑動 time.sleep(0.5) for back_track in tracks['back_tracks']: ActionChains(driver).move_by_offset(xoffset=back_track, yoffset=0).perform() # 小範圍震盪一下，進一步迷惑極驗後臺，這一步能夠極大地提升成功率 ActionChains(driver).move_by_offset(xoffset=-3, yoffset=0).perform() ActionChains(driver).move_by_offset(xoffset=3, yoffset=0).perform() # 成功後，騷包人類總喜歡默默地欣賞一下本身拼圖的成果，而後依依不捨地鬆開那隻髒手 time.sleep(0.5) ActionChains(driver).release().perform() def login_cnblogs(username,password): driver = webdriver.Chrome() try: # 一、輸入帳號密碼回車 driver.implicitly_wait(3) driver.get('https://passport.cnblogs.com/user/signin') input_username = driver.find_element_by_id('input1') input_pwd = driver.find_element_by_id('input2') signin = driver.find_element_by_id('signin') input_username.send_keys(username) input_pwd.send_keys(password) signin.click() # 二、破解滑動認證 crack(driver) time.sleep(10) # 睡時間長一點，肯定登陸成功 finally: driver.close() if __name__ == '__main__': login_cnblogs(username='linhaifeng',password='xxxx') 修訂版
參考網址：https://www.cnblogs.com/linhaifeng/articles/7802150.html#toppython
有一句話感觸頗深，由於我也一直是這樣認爲的，好比說，，，數學，我一直都認爲數學只是一種學習的工具
我學習數學不少時候只是想去作某件事，或者想去了解這件事的原理，想把他弄通透罷了程序員
那麼網上的學習軟件，或者編程也好，本質不變，可是當程序員的性質變了，目的不變，web
引用：編程
也就不修改說明說明了
ps:破解圖片驗證碼的核心在於模擬人的行爲， 自筆者在老男孩授課以來，上述的破解思路已經分享給不少人， 相應地網絡上也已經有不少copy版， 極驗後臺的也在不斷學習用戶的破解行爲， 但歸根結底只要咱們將破解行爲模擬地足夠像人，極驗就拿咱們沒有辦法，
上面引用的話也在說，核心在於模擬人的行爲，那麼計算機的本質是什麼呢？不就是解法生產力。。。。解放思想嘛canvas
那麼爬蟲的本質是什麼????? 瀏覽器
我以爲如今我自學這些東西的目的在於什麼？？網絡
或者說我想要達到什麼高度。。。。。app
若是不知道，我想能夠先放下了，想搞搞有目的有性質的東西——好比數學ide