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前言
由于网站注册入口容易被黑客攻击,存在如下安全问题:
所以大部分网站及App 都采取图形验证码或滑动验证码等交互解决方案, 但在机器学习能力提高的当下,连百度这样的大厂都遭受攻击导致点名批评, 图形验证及交互验证方式的安全性到底如何? 请看具体分析
简介:北京链家成立于2001年,是中国领先的房地产服务企业,业务覆盖二手房、新房、租房等全方位房产交易和居住服务,目前北京链家有1000余家门店。20年来,北京链家致力于提供安全有品质的服务,在行业率先承诺“不吃差价”、首倡“真房源”、推出“交易不成 佣金全退”“电话营销 扰一赔百”等18项安心服务承诺,与此同时北京链家也在全面推行店面服务升级和经纪人职业素养提升,坚持对客户好,对经纪人好,对社区好,持续推动行业进步,不断提供更有品质的服务。
采用极验的V2版本,容易被模拟器绕过甚至逆向后暴力攻击,滑动拼图识别率在 95% 以上。
前端界面分析, 采用的是极验2.0,最大特点就是将图片做分割后,在前端再做合并,这就好办了, 网上有大量现成的逆向文章及视频参考,不过我们这次不用逆向, 只是采用模拟器的方式,关键点主要模拟器交互、距离识别和轨道算法3部分。
public RetEntity send(WebDriver driver, String areaCode, String phone) {
try {
driver.get(INDEX_URL);
// 点击立即注册
driver.findElements(By.className("log")).get(0).click();
Thread.sleep(500);
List<WebElement> inputElements = driver.findElements(By.xpath("//input[@class='phonenum_input']"));
System.out.println("findElements size=" + inputElements.size());
WebElement phoneElemet = inputElements.get(2);
for (int i = 0; i < phone.length(); i++) {
char c = phone.charAt(i);
phoneElemet.sendKeys(c + "");
phoneElemet.click();
}
Thread.sleep(500);
List<WebElement> emElements = driver.findElements(By.tagName("em"));
System.out.println("emElements size=" + emElements.size());
for (WebElement web : emElements) {
String text = web.getText();
if (text != null && "获取验证码".equals(text)) {
web.click();
}
}
boolean result = geetApi.getAndMove(driver, 6);
RetEntity retEntity = new RetEntity();
if (result) {
retEntity.setRet(0);
retEntity.setMsg("发送成功");
} else {
retEntity.setRet(-1);
retEntity.setMsg("发送失败");
}
return retEntity;
} catch (Exception e) {
System.out.println(e.toString());
return null;
}
}
public boolean getAndMove(WebDriver driver, Integer offSet) {
int distance = -1;
try {
WebElement moveElement = ChromeDriverManager.waitElement(driver, By.className("geetest_slider_button"), 1000);
if (moveElement == null) {
logger.error("getAndMove() moveElement=" + moveElement);
return false;
}
// 下面的js代码根据canvas文档说明而来
// 完整背景图geetest_canvas_fullbg geetest_fade geetest_absolute
StringBuffer base64 = new StringBuffer();
String fullName = "geetest_canvas_fullbg geetest_fade geetest_absolute";
byte[] fullImg = GetImage.callJsByName(driver, fullName, base64);
String bgName = "geetest_canvas_bg geetest_absolute";
byte[] bgImg = GetImage.callJsByName(driver, bgName, base64);
File fullFile = null, bgFile = null;
if (fullImg != null && bgImg != null) {
Long time = System.currentTimeMillis();
fullFile = new File(dataPath + "geet/" + time + "full.png");
FileUtils.writeByteArrayToFile(fullFile, fullImg);
bgFile = new File(dataPath + "geet/" + time + "bg.png");
FileUtils.writeByteArrayToFile(bgFile, bgImg);
if (fullImg.length < 10000) {
System.out.println("fullImg len=" + fullImg.length + " -> err[len<10000]");
return false;
}
}
// 获取滑动距离并删除图片
distance = (fullFile != null && bgFile != null) ? ActionMove.getMoveDistance(fullFile.getAbsolutePath(), bgFile.getAbsolutePath()) : -1;
if (distance < 1) {
logger.error("getAndMove distance=" + distance);
return false;
}
if (offSet != null)
ActionMove.move(driver, moveElement, distance - offSet);
else
ActionMove.move(driver, moveElement, distance);
// 滑动结果
Thread.sleep(1 * 1000);
WebElement infoElement = ChromeDriverManager.getInstance().waitForLoad(By.className("geetest_result_content"), 10);
String gtInfo = (infoElement != null) ? infoElement.getAttribute("innerText") : null;
if (gtInfo != null) {
System.out.println("gtInfo=" + gtInfo);
if (gtInfo.contains("速度超过") || gtInfo.contains("通过验证")) {
return true;
}
} else {
String msg = driver.findElement(By.className("geetest_panel_success_title")).getAttribute("innerText");
System.out.println("msg=" + msg);
}
return false;
} catch (Exception e) {
System.out.println("getAndMove() " + e.toString());
logger.error(e.toString());
return false;
}
}
2. 距离识别
/**
* 计算需要平移的距离
*
* @param fullImgPath
* 完整背景图片文件名
* @param bgImgPath含有缺口背景图片文件名
* @return
* @throws IOException
*/
public static int getMoveDistance(String fullImgPath, String bgImgPath) {
System.out.println("fullImgPath=" + fullImgPath);
File fullFile = new File(fullImgPath);
File bgFile = new File(bgImgPath);
boolean fullExists = fullFile.exists();
boolean bgExists = bgFile.exists();
if (fullExists && bgExists) {
String abPath = bgFile.getAbsolutePath();
int l = abPath.lastIndexOf(".");
String out = abPath.substring(0, l) + "-o" + abPath.substring(l);
return getComareImg(fullFile, bgFile, out);
} else {
System.out.println("fullExists(" + fullImgPath + ")=" + fullExists + "\nbgExists(" + bgImgPath + ")=" + bgExists);
return -1;
}
}
/**
* 计算需要平移的距离
*
* @param driver
* @param fullImgPath完整背景图片文件名
* @param bgImgPath含有缺口背景图片文件名
* @return
* @throws IOException
*/
private static int getComareImg(Object fullObj, Object bgObj, String out) {
System.out.println("getComareImg() begin");
try {
if (fullObj == null || bgObj == null) {
return -1;
}
BufferedImage fullBI = (fullObj instanceof File) ? ImageIO.read((File) fullObj) : ImageIO.read((ByteArrayInputStream) fullObj);
BufferedImage bgBI = (bgObj instanceof File) ? ImageIO.read((File) bgObj) : ImageIO.read((ByteArrayInputStream) bgObj);
List<Integer> list;
Color ca, cb;
Map<Integer, List<Integer>> xMap = new TreeMap<Integer, List<Integer>>();
// 将头35列的最大不同值取出, 作为右边图像的基础差
Long tifTotl = 0L;
int tifLeft = 0;
int tifCount = 0;
for (int i = 0; i < bgBI.getWidth(); i++) {
for (int j = 0; j < bgBI.getHeight(); j++) {
ca = new Color(fullBI.getRGB(i, j));
cb = new Color(bgBI.getRGB(i, j));
int diff = diff(ca, cb);
if (i <= 35 && tifLeft < diff) {
tifLeft = (diff >= 255) ? 255 : diff;
} else if (diff > tifLeft) {
tifTotl += diff;
tifCount++;
}
}
}
Long tifAvg = (tifCount > 0) ? (tifTotl / tifCount) : 0L;
if (tifLeft <= 0 && tifAvg >= 2) {
tifAvg = tifAvg / 2;
}
for (int i = 35; i < bgBI.getWidth(); i++) {
for (int j = 0; j < bgBI.getHeight(); j++) {
ca = new Color(fullBI.getRGB(i, j));
cb = new Color(bgBI.getRGB(i, j));
int diff = diff(ca, cb);
if (diff >= tifAvg) {
list = xMap.get(i);
if (list == null) {
list = new ArrayList<Integer>();
xMap.put(i, list);
}
list.add(j);
xMap.put(i, list);
}
}
}
System.out.println(" |--tifLeft=" + tifLeft + ",tifTotl=" + tifTotl + ",tifCount=" + tifCount + ",tifAvg=" + tifAvg + ",xMap.size=" + xMap.size());
int minX = 0;
int maxX = 0;
for (Integer x : xMap.keySet()) {
list = xMap.get(x);
minX = (minX == 0) ? x : minX;
maxX = x;
for (int y : list) {
cb = new Color(bgBI.getRGB(x, y));
int gray = (int) (0.3 * cb.getRed() + 0.59 * cb.getGreen() + 0.11 * cb.getBlue());
bgBI.setRGB(x, y, gray);
}
}
// 标记直线位置
for (int y = 0; y < bgBI.getHeight(); y++) {
bgBI.setRGB(minX, y, Color.red.getRGB());
}
int width = maxX - minX;
File destFile = new File(out);
Thumbnails.of(bgBI).scale(1f).toFile(destFile);
System.out.println(" |---xMap.size=" + xMap.size() + " minX=" + minX + ",maxX=" + maxX + ",width=" + width);
return minX;
} catch (Exception e) {
System.out.println(e.toString());
for (StackTraceElement elment : e.getStackTrace()) {
System.out.println(elment.toString());
}
logger.error("getMoveDistance() err = " + e.toString());
return 0;
}
}
private static int diff(Color ca, Color cb) {
int d = Math.abs(ca.getRed() - cb.getRed()) + Math.abs(ca.getGreen() - cb.getGreen()) + Math.abs(ca.getBlue() - ca.getBlue());
return d;
}
3. 轨道生成及移动算法
/**
* 双轴轨道生成算法,主要实现平滑加速和减速
*
* @param distance
* @return
*/
public static List<Integer[]> getXyTrack(int distance) {
List<Integer[]> track = new ArrayList<Integer[]>();// 移动轨迹
try {
int a = (int) (distance / 3.0) + random.nextInt(10);
int h = 0, current = 0;// 已经移动的距离
BigDecimal midRate = new BigDecimal(0.7 + (random.nextInt(10) / 100.00)).setScale(4, BigDecimal.ROUND_HALF_UP);
BigDecimal mid = new BigDecimal(distance).multiply(midRate).setScale(0, BigDecimal.ROUND_HALF_UP);// 减速阈值
BigDecimal move = null;// 每次循环移动的距离
List<Integer[]> subList = new ArrayList<Integer[]>();// 移动轨迹
boolean plus = true;
Double t = 0.18, v = 0.00, v0;
while (current <= distance) {
h = random.nextInt(2);
if (current > distance / 2) {
h = h * -1;
}
v0 = v;
v = v0 + a * t;
move = new BigDecimal(v0 * t + 1 / 2 * a * t * t).setScale(4, BigDecimal.ROUND_HALF_UP);// 加速
if (move.intValue() < 1)
move = new BigDecimal(1L);
if (plus) {
track.add(new Integer[] { move.intValue(), h });
} else {
subList.add(0, new Integer[] { move.intValue(), h });
}
current += move.intValue();
if (plus && current >= mid.intValue()) {
plus = false;
move = new BigDecimal(0L);
v = 0.00;
}
}
track.addAll(subList);
int bk = current - distance;
if (bk > 0) {
for (int i = 0; i < bk; i++) {
track.add(new Integer[] { -1, h });
}
}
System.out.println("getMoveTrack(" + midRate + ") a=" + a + ",distance=" + distance + " -> mid=" + mid.intValue() + " size=" + track.size());
return track;
} catch (Exception e) {
System.out.print(e.toString());
return null;
}
}
/**
* 模拟人工移动
*
* @param driver
* @param element页面滑块
* @param distance需要移动距离
* @throws InterruptedException
*/
public static void move(WebDriver driver, WebElement element, int distance) throws InterruptedException {
List<Integer[]> track = getXyTrack(distance);
if (track == null || track.size() < 1) {
System.out.println("move() track=" + track);
}
int moveY, moveX;
StringBuffer sb = new StringBuffer();
try {
Actions actions = new Actions(driver);
actions.clickAndHold(element).perform();
Thread.sleep(20);
long begin, cost;
Integer[] move;
int sum = 0;
for (int i = 0; i < track.size(); i++) {
begin = System.currentTimeMillis();
move = track.get(i);
moveX = move[0];
sum += moveX;
moveY = move[1];
if (moveX < 0) {
if (sb.length() > 0) {
sb.append(",");
}
sb.append(moveX);
}
actions.moveByOffset(moveX, moveY).perform();
cost = System.currentTimeMillis() - begin;
if (cost < 3) {
Thread.sleep(3 - cost);
}
}
if (sb.length() > 0) {
System.out.println("-----backspace[" + sb.toString() + "]sum=" + sum + ",distance=" + distance);
}
Thread.sleep(180);
actions.release(element).perform();
Thread.sleep(500);
} catch (Exception e) {
StringBuffer er = new StringBuffer("move() " + e.toString() + "\n");
for (StackTraceElement elment : e.getStackTrace())
er.append(elment.toString() + "\n");
logger.error(er.toString());
System.out.println(er.toString());
}
}
链家地产作为房地产中介的行业巨头, 采用的是通俗的滑动验证产品, 在一定程度上提高了用户体验, 不过随着图形识别技术及机器学习能力的提升,所以在网上破解的文章和教学视频也是大量存在,并且经过验证的确有效, 所以除了滑动验证方式, 花样百出的产品层出不穷,但本质就是牺牲用户体验来提高安全。
很多人在短信服务刚开始建设的阶段,可能不会在安全方面考虑太多,理由有很多。
比如:“ 需求这么赶,当然是先实现功能啊 ”,“ 业务量很小啦,系统就这么点人用,不怕的 ” , “ 我们怎么会被盯上呢,不可能的 ”等等。有一些理由虽然有道理,但是该来的总是会来的。前期欠下来的债,总是要还的。越早还,问题就越小,损失就越低。
所以大家在安全方面还是要重视。(血淋淋的栗子!)#安全短信#
谷歌图形验证码在AI 面前已经形同虚设,所以谷歌宣布退出验证码服务, 那么当所有的图形验证码都被破解时,大家又该如何做好防御呢?
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