test

Dockerfile

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+FROM python:3.11-slim-bullseye as builder
+
+# Build dummy packages to skip installing them and their dependencies
+RUN apt-get update \
+    && apt-get install -y --no-install-recommends equivs \
+    && equivs-control libgl1-mesa-dri \
+    && printf 'Section: misc\nPriority: optional\nStandards-Version: 3.9.2\nPackage: libgl1-mesa-dri\nVersion: 99.0.0\nDescription: Dummy package for libgl1-mesa-dri\n' >> libgl1-mesa-dri \
+    && equivs-build libgl1-mesa-dri \
+    && mv libgl1-mesa-dri_*.deb /libgl1-mesa-dri.deb \
+    && equivs-control adwaita-icon-theme \
+    && printf 'Section: misc\nPriority: optional\nStandards-Version: 3.9.2\nPackage: adwaita-icon-theme\nVersion: 99.0.0\nDescription: Dummy package for adwaita-icon-theme\n' >> adwaita-icon-theme \
+    && equivs-build adwaita-icon-theme \
+    && mv adwaita-icon-theme_*.deb /adwaita-icon-theme.deb
+
+FROM python:3.11-slim-bullseye
+COPY --from=builder /*.deb /
+WORKDIR /app
+RUN echo "deb http://deb.debian.org/debian/ unstable main contrib non-free" >> /etc/apt/sources.list
+RUN apt update
+RUN apt install -y python3 python3-pip libgl1-mesa-glx wget
+
+
+RUN dpkg -i /libgl1-mesa-dri.deb \
+    && dpkg -i /adwaita-icon-theme.deb \
+    # Install dependencies
+    && apt-get update \
+    && apt-get install -y --no-install-recommends xvfb dumb-init \
+        procps curl vim xauth \
+    # Remove temporary files and hardware decoding libraries
+    && rm -rf /var/lib/apt/lists/* \
+    && rm -f /usr/lib/x86_64-linux-gnu/libmfxhw* \
+    && rm -f /usr/lib/x86_64-linux-gnu/mfx/* \
+    && useradd --home-dir /app --shell /bin/sh foxer \
+    && chown -R foxer:foxer .
+
+COPY requirements.txt .
+RUN pip install -r requirements.txt \
+    # Remove temporary files
+    && rm -rf /root/.cache
+USER foxer
+
+RUN mkdir -p "/app/.config/Ultralytics"
+
+COPY main .
+EXPOSE 7860
+
+ENTRYPOINT ["/usr/bin/dumb-init", "--"]
+CMD ["/usr/local/bin/python","-u", "/app/main.py"]

main/main.py

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+import base64
+import hashlib
+import os
+import uuid
+import shutil
+from flask import Flask, jsonify, request
+from flask_limiter import Limiter
+from flask_limiter.util import get_remote_address
+import recaptcha_bypass
+
+app = Flask(__name__)
+
+limiter = Limiter(
+    app=app,
+    key_func=get_remote_address,  # 使用 IP 地址作为键
+    default_limits=["10 per minute", "50 per hour"],  # 设置默认的请求限制
+)
+shared_limiter = limiter.shared_limit("20/minute", scope="memory")
+
+
+def get_token():
+    default_token = "init_token"
+    if os.path.exists("token"):
+        return open("token", "r").read().strip()
+    return default_token
+
+
+def check_request(required_data, data):
+    token = get_token()
+    if not data or any(key not in data for key in required_data):
+        print("Error:Invalid Request Data\n" + str(data))
+        return False
+    if data["token"] != token:
+        print("Error:Invalid Token\n" + str(data))
+        return False
+    return True
+
+
+def check_task_token(required_data, data):
+    if not check_request(required_data, data):
+        return False
+    if not os.path.isdir(data["task_token"]):
+        print("Task token err\n" + data)
+        return False
+    return True
+
+
+def generate_uuid():
+    unique_identifier = str(uuid.uuid4())
+    hashed_string = hashlib.sha256(unique_identifier.encode()).hexdigest()
+    return hashed_string
+
+
+def base64_to_file(task_token, name, base64_data):
+    file = open(f"{task_token}/{name}.png", "wb+")
+    file.write(base64.b64decode(base64_data))
+    file.close()
+
+
+@app.errorhandler(429)
+def rate_limit_exceeded(e):
+    print(get_remote_address())
+    return jsonify(msg="Too many request"), 429
+
+
+@app.errorhandler(405)
+def method_not_allowed(e):
+    print(get_remote_address())
+    return jsonify(msg="Unauthorized Request"), 405
+
+
+@app.route("/", methods=["GET"])
+@shared_limiter
+def index():
+    return jsonify(status_code=200)
+
+
+@app.route("/update/token", methods=["POST"])
+@shared_limiter
+def update_token():
+    require_data = ["token", "new_token"]
+    data = request.get_json(force=True, silent=True)
+    if not check_request(require_data, data):
+        return jsonify(msg="Unauthorized Request"), 403
+    token = open("token", "w+")
+    token.write(data["new_token"])
+    token.close()
+    return jsonify(msg="Token updated successfully", success=True)
+
+
+@app.route("/task-token", methods=["POST"])
+@shared_limiter
+def get_task_token():
+    data = request.get_json(force=True, silent=True)
+    required_data = ["token"]
+    if not check_request(required_data, data):
+        return jsonify(msg="Unauthorized Request"), 403
+    # 任务唯一凭证
+    task_token = generate_uuid()
+    os.makedirs(task_token)
+    return jsonify(msg="ok", task_token=task_token, success=True)
+
+
+@app.route("/revoke-token", methods=["POST"])
+@shared_limiter
+def revoke_token():
+    data = request.get_json(force=True, silent=True)
+    required_data = ["token", "task_token"]
+    if not check_task_token(required_data, data):
+        return jsonify(msg="Unauthorized Request"), 403
+    if len(data["task_token"]) != 64 or not data["task_token"].isalnum():
+        return jsonify(msg="Unauthorized Request"), 403
+    shutil.rmtree(data["task_token"].lower())
+    return jsonify(msg="success", success=True)
+
+
+@app.route("/upload", methods=["POST"])
+@shared_limiter
+def init_solver():
+    data = request.get_json(force=True, silent=True)
+    required_data = ["token", "img_name", "img_base", "task_token"]
+    if not check_task_token(required_data, data):
+        return jsonify(msg="Unauthorized Request"), 403
+    task_token = data["task_token"]
+    img = data["img_base"]
+    img_name = data["img_name"]
+    base64_to_file(task_token, img_name, img)
+    return jsonify(msg="file upload success", task_token=task_token, success=True)
+
+
+@app.route("/get_answers", methods=["POST"])
+@shared_limiter
+def get_answer():
+    data = request.get_json(force=True, silent=True)
+    required_data = ["token", "target_num", "task_token"]
+    if not check_task_token(required_data, data):
+        return jsonify(msg="Unauthorized Request"), 403
+    answers = recaptcha_bypass.get_answers(data["target_num"], data["task_token"])
+    return jsonify(msg="success", success=True, answers=answers)
+
+
+@app.route("/paste", methods=["POST"])
+@shared_limiter
+def paste():
+    data = request.get_json(force=True, silent=True)
+    required_data = ["token", "task_token", "new", "loc"]
+    if not check_task_token(required_data, data):
+        return jsonify(msg="Unauthorized Request"), 403
+    recaptcha_bypass.paste_new_img_on_main_img(data["new"], data["loc"], data["task_token"])
+    return jsonify(msg="success", success=True)
+
+
+@app.route("/get_answers4", methods=["POST"])
+@shared_limiter
+def get_answers4():
+    data = request.get_json(force=True, silent=True)
+    required_data = ["token", "task_token", "target_num"]
+    if not check_task_token(required_data, data):
+        return jsonify(msg="Unauthorized Request"), 403
+    answers = recaptcha_bypass.get_answers_4(data["target_num"], data["task_token"])
+    return jsonify(msg="success", success=True, answers=answers)
+
+
+app.run(port=7860)

main/recaptcha_bypass.py

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+import shutil
+import requests
+import re
+from ultralytics import YOLO
+import numpy as np
+from PIL import Image
+import cv2
+
+model = YOLO("yolov8x.pt")
+
+
+def get_answers(target_num, task_token):
+    image = Image.open(f"{task_token}/0.png")
+    image = np.asarray(image)
+    result = model.predict(image)
+
+    target_index = []
+    count = 0
+    for num in result[0].boxes.cls:
+        if num == target_num:
+            target_index.append(count)
+        count += 1
+
+    answers = []
+    boxes = result[0].boxes.data
+    count = 0
+    for i in target_index:
+        target_box = boxes[i]
+        p1, p2 = (int(target_box[0]), int(target_box[1])
+                  ), (int(target_box[2]), int(target_box[3]))
+        x1, y1 = p1
+        x2, y2 = p2
+
+        xc = (x1 + x2) / 2
+        yc = (y1 + y2) / 2
+
+        if xc < 100 and yc < 100:
+            answers.append(1)
+        if 200 > xc > 100 > yc:
+            answers.append(2)
+        if 200 < xc < 300 and yc < 100:
+            answers.append(3)
+
+        if xc < 100 < yc < 200:
+            answers.append(4)
+        if 100 < xc < 200 and 100 < yc < 200:
+            answers.append(5)
+        if 300 > xc > 200 > yc > 100:
+            answers.append(6)
+
+        if xc < 100 and 200 < yc < 300:
+            answers.append(7)
+        if 100 < xc < 200 < yc < 300:
+            answers.append(8)
+        if 200 < xc < 300 and 200 < yc < 300:
+            answers.append(9)
+
+        count += 1
+
+    return list(set(answers))
+
+
+def paste_new_img_on_main_img(new, loc, task_token):
+    main_img = Image.open(f"{task_token}/0.png")
+    new_img = Image.open(f"{task_token}/{new}.png")
+    paste = np.copy(main_img)
+    if loc == 1:
+        paste[0:100, 0:100] = new_img
+    elif loc == 2:
+        paste[0:100, 100:200] = new_img
+    elif loc == 3:
+        paste[0:100, 200:300] = new_img
+    elif loc == 4:
+        paste[100:200, 0:100] = new_img
+    elif loc == 5:
+        paste[100:200, 100:200] = new_img
+    elif loc == 6:
+        paste[100:200, 200:300] = new_img
+    elif loc == 7:
+        paste[200:300, 0:100] = new_img
+    elif loc == 8:
+        paste[200:300, 100:200] = new_img
+    elif loc == 9:
+        paste[200:300, 200:300] = new_img
+
+    paste = cv2.cvtColor(paste, cv2.COLOR_RGB2BGR)
+    cv2.imwrite(f'{task_token}/0.png', paste)
+
+
+def get_occupied_cells(vertices):
+    occupied_cells = set()
+    rows, cols = zip(*[((v - 1) // 4, (v - 1) % 4) for v in vertices])
+
+    for i in range(min(rows), max(rows) + 1):
+        for j in range(min(cols), max(cols) + 1):
+            occupied_cells.add(4 * i + j + 1)
+
+    return sorted(list(occupied_cells))
+
+
+def get_answers_4(target_num, task_token):
+    image = Image.open(f"{task_token}/0.png")
+    image = np.asarray(image)
+    result = model.predict(image)
+    boxes = result[0].boxes.data
+    target_index = []
+    count = 0
+    for num in result[0].boxes.cls:
+        if num == target_num:
+            target_index.append(count)
+        count += 1
+
+    for i in target_index:
+        target_box = boxes[i]
+        p1, p2 = (int(target_box[0]), int(target_box[1])
+                  ), (int(target_box[2]), int(target_box[3]))
+        x1, y1 = p1
+        x2, y2 = p2
+
+    answers = []
+    count = 0
+    for i in target_index:
+        target_box = boxes[i]
+        p1, p2 = (int(target_box[0]), int(target_box[1])
+                  ), (int(target_box[2]), int(target_box[3]))
+        x1, y1 = p1
+        x4, y4 = p2
+        x2 = x4
+        y2 = y1
+        x3 = x1
+        y3 = y4
+        xys = [x1, y1, x2, y2, x3, y3, x4, y4]
+
+        four_cells = []
+        for i in range(4):
+            x = xys[i * 2]
+            y = xys[(i * 2) + 1]
+
+            if x < 112.5 and y < 112.5:
+                four_cells.append(1)
+            if 225 > x > 112.5 > y:
+                four_cells.append(2)
+            if 225 < x < 337.5 and y < 112.5:
+                four_cells.append(3)
+            if 337.5 < x <= 450 and y < 112.5:
+                four_cells.append(4)
+
+            if x < 112.5 < y < 225:
+                four_cells.append(5)
+            if 112.5 < x < 225 and 112.5 < y < 225:
+                four_cells.append(6)
+            if 337.5 > x > 225 > y > 112.5:
+                four_cells.append(7)
+            if 337.5 < x <= 450 and 112.5 < y < 225:
+                four_cells.append(8)
+
+            if x < 112.5 and 225 < y < 337.5:
+                four_cells.append(9)
+            if 112.5 < x < 225 < y < 337.5:
+                four_cells.append(10)
+            if 225 < x < 337.5 and 225 < y < 337.5:
+                four_cells.append(11)
+            if 450 >= x > 337.5 > y > 225:
+                four_cells.append(12)
+
+            if x < 112.5 and 337.5 < y <= 450:
+                four_cells.append(13)
+            if 112.5 < x < 225 and 337.5 < y <= 450:
+                four_cells.append(14)
+            if 225 < x < 337.5 < y <= 450:
+                four_cells.append(15)
+            if 337.5 < x <= 450 and 337.5 < y <= 450:
+                four_cells.append(16)
+        answer = get_occupied_cells(four_cells)
+        count += 1
+        for ans in answer:
+            answers.append(ans)
+    answers = sorted(list(answers))
+    return list(set(answers))

requirements.txt

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+numpy==1.25.2
+opencv_python==4.8.0.76
+Pillow==10.0.0
+Requests==2.31.0
+selenium==4.11.2
+ultralytics==8.0.153
+webdriver_manager==4.0.0
+Flask
+Flask-Limiter