Automatic Script for Solving captcha of CAS (Central Authentication Service) of Sun Yat-sen University
// ==UserScript==
// @name 中大自动验证码认证
// @name:en SYSU CAS Auto Captcha Login
// @name:zh 中大自动验证码认证
// @namespace https://github.com/KumaTea
// @namespace https://greasyfork.org/en/users/169784-kumatea
// @homepage https://github.com/KumaTea/SYSU-CAS
// @version 1.2.0.0
// @description 中山大学身份验证系统自动识别验证码登录
// @description:en Automatic Script for Solving captcha of CAS (Central Authentication Service) of Sun Yat-sen University
// @description:zh 中山大学身份验证系统自动识别验证码登录
// @description:zh-cn 中山大学身份验证系统自动识别验证码登录
// @author KumaTea
// @match https://cas.sysu.edu.cn/cas/login*
// @match https://cas-443.webvpn.sysu.edu.cn/cas/login*
// @license GPLv3
// @require https://greasyfork.org/scripts/437298-tesseract-fast-min-js/code/tesseract-fastminjs.js
// @require https://cdn.jsdelivr.net/npm/sweetalert2@11.3.0/dist/sweetalert2.all.min.js
// ==/UserScript==
/*
为省去手动激活页面的操作
请在此输入您的 NetID 账号密码
此操作不会上传任何信息
*/
const username = '';
const password = '';
/*
Whoa! You found here!
Please replace "tesseract-fastminjs.js" with this link before reading the following instructions:
https://gitee.com/kumatea/tesseract-dist/raw/master/2.1.5/tesseract-fast.min.js
Use fast trained data (1.89 MB) by default.
If you want to use the better trained data (10.4 MB),
replace the "tesseract-fast.min.js" with "tesseract.min.js"
in the '@require' section above.
There is also a best version: "tesseract-best.min.js".
默认使用精简训练数据（1.89 MB）。
如果你想使用标准训练数据（10.4 MB），在上面的 '@require' 部分
把 "tesseract-fast.min.js" 替换为 "tesseract.min.js"。
另有一个最佳版本："tesseract-best.min.js"。
*/
/* jshint esversion: 8 */
// "use strict";
const delay = 2*1000;
const captcha_regex = /[A-Za-z0-9]/g;
const black_threshold = 50;
console.log("Fetching: https://raw.github.cnpmjs.org/naptha/tessdata/gh-pages/4.0.0_fast/eng.traineddata.gz")
function sleep(ms) {
return new Promise(resolve => setTimeout(resolve, ms));
}
const mouseClickEvents = ['mousedown', 'click', 'mouseup'];
function simulateMouseClick(element) {
// https://stackoverflow.com/a/54316368
// https://stackoverflow.com/a/69977098
mouseClickEvents.forEach(mouseEventType =>
element.dispatchEvent(
new MouseEvent(mouseEventType)
)
);
}
function react_input(component, value) {
// Credit: https://github.com/facebook/react/issues/11488#issuecomment-347775628
let last_value = component.value;
component.value = value;
let event = new Event("input", {bubbles: true});
// React 15
event.simulated = true;
// React 16
let tracker = component._valueTracker;
if (tracker) {
tracker.setValue(last_value);
}
component.dispatchEvent(event);
}
function load_js(src) {
const script = document.createElement('script');
script.type = 'text/javascript';
script.src = src;
document.head.appendChild(script);
}
function replace_color_in_canvas(canvas) {
let ctx = canvas.getContext("2d");
let imageData = ctx.getImageData(0, 0, canvas.width, canvas.height);
let data = imageData.data;
let len = data.length / 3;
let first_pixel_array = [data[0], data[1], data[2]];
for (let i = 0; i < len; i += 1) {
let r = data[i * 3];
let g = data[i * 3 + 1];
let b = data[i * 3 + 2];
if (r + g < black_threshold || r + b < black_threshold || g + b < black_threshold) {
data[i*3] = first_pixel_array[0];
data[i*3 + 1] = first_pixel_array[1];
data[i*3 + 2] = first_pixel_array[2];
}
}
ctx.putImageData(imageData, 0, 0);
return ctx;
}
function img_src_to_base64(img) {
// Ref: https://stackoverflow.com/a/22172860/10714490
let canvas = document.createElement("canvas");
canvas.width = img.width;
canvas.height = img.height;
let ctx = canvas.getContext("2d");
ctx.drawImage(img, 0, 0);
ctx = replace_color_in_canvas(ctx.canvas);
return ctx.canvas.toDataURL("image/png");
}
function clone_image(img) {
let new_img = document.createElement("img");
new_img.src = img_src_to_base64(img)
return new_img;
}
async function recognize() {
let result = "";
await Tesseract.recognize(clone_image(document.getElementById('captchaImg')), "eng")
.then(({ data: { text } }) => {result = text.match(captcha_regex).join("");});
console.log("Recognized: " + result);
return result;
}
async function solve() {
if (document.getElementById("captcha")) {
Swal.fire({title: "正在加载识别组件……", showConfirmButton: false, timer: 3000});
react_input(document.getElementById("captcha"), "正在加载识别组件，请耐心等待……");
let result = await recognize();
react_input(document.getElementById("captcha"), result);
if (result.length !== 4) {
location.reload();
}
console.log("Submitting: " + result);
if (document.querySelector("input.btn.btn-submit.btn-block").disabled) {
if (username && password) {
react_input(document.getElementById("username"), username);
react_input(document.getElementById("password"), password);
} else {
while (document.querySelector("input.btn.btn-submit.btn-block").disabled) {
console.log("Login button is not clickable!");
Swal.fire({title: "请点击网页以激活登录按钮", showConfirmButton: false, timer: 1000});
await sleep(delay);
}
}
}
document.querySelector("input.btn.btn-submit.btn-block").click();
// simulateMouseClick(document.querySelector("input.btn.btn-submit.btn-block"));
}
}
solve();