import vec2text
import torch
from transformers import AutoModel, AutoTokenizer, PreTrainedTokenizer, PreTrainedModel
import pickle

class RagData:
    def __init__(self, embedding_model=None, embeddings=None):
        self.embedding_model = embedding_model
        self.embeddings = embeddings or []

def get_gtr_embeddings(text_list,
                       encoder: PreTrainedModel,
                       tokenizer: PreTrainedTokenizer) -> torch.Tensor:

    inputs = tokenizer(text_list,
                       return_tensors="pt",
                       max_length=128,
                       truncation=True,
                       padding="max_length",).to("cuda")

    with torch.no_grad():
        model_output = encoder(input_ids=inputs['input_ids'], attention_mask=inputs['attention_mask'])
        hidden_state = model_output.last_hidden_state
        embeddings = vec2text.models.model_utils.mean_pool(hidden_state, inputs['attention_mask'])

    return embeddings


encoder = AutoModel.from_pretrained("sentence-transformers/gtr-t5-base").encoder.to("cuda")
tokenizer = AutoTokenizer.from_pretrained("sentence-transformers/gtr-t5-base")
corrector = vec2text.load_pretrained_corrector("gtr-base")

with open('rag_data.pkl', 'rb') as f:
  rag_data = pickle.load(f)


embeddings=rag_data.embeddings
embeddings = torch.tensor(embeddings)
# 查看数据结构
print(embeddings.shape)

vec2text.invert_embeddings(
    embeddings=embeddings.cuda(),
    corrector=corrector,
    num_steps=20,
)

from PIL import Image

def xor_images(img1_path, img2_path, output_path="xor_result.png"):
    # 加载并转换为RGB格式
    img1 = Image.open(img1_path).convert("RGB")
    img2 = Image.open(img2_path).convert("RGB")

    if img1.size != img2.size:
        raise ValueError("图片尺寸不一致，无法进行异或运算")

    w, h = img1.size
    result = Image.new("RGB", (w, h))

    # 每像素逐位异或
    for x in range(w):
        for y in range(h):
            r1, g1, b1 = img1.getpixel((x, y))
            r2, g2, b2 = img2.getpixel((x, y))
            result.putpixel((x, y), (
                r1 ^ r2,
                g1 ^ g2,
                b1 ^ b2
            ))

    result.save(output_path)
    print(f"[+] 已保存异或图像为: {output_path}")

# 示例用法
if __name__ == "__main__":
    xor_images("1.webp", "2.webp", "xor_result.png")

import torch
from torchvision import transforms
from torchvision.models import shufflenet_v2_x1_0, ShuffleNet_V2_X1_0_Weights
from PIL import Image
import json
import requests
import os

def invert_embedding_to_image(embedding_path, output_path, steps=500, lr=0.1):
    # Load model
    model = shufflenet_v2_x1_0(weights=ShuffleNet_V2_X1_0_Weights.IMAGENET1K_V1)
    model.fc = torch.nn.Identity()
    model.eval()

    # Load target embedding
    with open(embedding_path, 'r') as f:
        target_emb = torch.tensor(json.load(f), dtype=torch.float32)

    # Initialize trainable image tensor (noise)
    img = torch.randn(1, 3, 224, 224, requires_grad=True)
    optimizer = torch.optim.Adam([img], lr=lr)

    for step in range(steps):
        optimizer.zero_grad()
        # Sigmoid to bound pixels between 0 and 1
        clipped = img.sigmoid()
        emb = model(clipped)[0]
        loss = torch.nn.functional.mse_loss(emb, target_emb)
        loss.backward()
        optimizer.step()
        if step % 50 == 0:
            print(f'Step {step}, Loss {loss.item():.6e}')

    # Convert to image and save
    result = (clipped.detach().squeeze().permute(1, 2, 0).cpu().numpy() * 255).astype('uint8')
    inv_image = Image.fromarray(result)
    inv_image.save(output_path)
    print(f"Inverted image saved to '{output_path}'")

def upload_and_print_response(image_path, server_url):
    if not os.path.exists(image_path):
        print(f"File '{image_path}' not found.")
        return
    with open(image_path, 'rb') as f:
        files = {'file': f}
        response = requests.post(server_url, files=files)
    try:
        print("Server response:", response.json())
    except ValueError:
        print("Server response (text):", response.text)

if __name__ == "__main__":
    EMB_PATH = 'embedding.json'
    OUT_IMG = 'inverted_image.png'
    SIGNIN_URL = 'http://1.95.8.146:50001/signin/'

    # Step 1: Invert embedding to image
    invert_embedding_to_image(EMB_PATH, OUT_IMG, steps=500, lr=0.1)

    # Step 2: Upload image and print the flag or failure
    upload_and_print_response(OUT_IMG, SIGNIN_URL)

the content of flag is: come on little brave fox
replace lesser o with number zero, letter l with number one
replace lesser a with symbol at
make every lesser e uppercase
use underline to link each word

from hashlib import sha1
with open('phar.gif', 'rb') as file:
    f = file.read() 
   
s = f[:-28] # 获取要签名的数据
h = f[-8:] # 获取签名类型和GBMB标识
newf = s + sha1(s).digest() + h # 数据 + 签名 + (类型 + GBMB)

with open('phar1.gif', 'wb') as file:
    file.write(newf) # 写入新文件

openssl enc -in "/flag_gogogo_chufalong"

@app.route("/ip_detail/<string:username>", methods=["GET"])
def route_ip_detail(username):
    res = requests.get(f"http://127.0.0.1/get_last_ip/{username}")
    if res.status_code != 200:
        return "Get last ip failed."
    last_ip = res.text
    try:
        ip = re.findall(r"\d+\.\d+\.\d+\.\d+", last_ip)
        country = geoip2_reader.country(ip)
    except (ValueError, TypeError):
        country = "Unknown"
    template = f"""
    <h1>IP Detail</h1>
    <div>{last_ip}</div>
    <p>Country:{country}</p>
    """
    return render_template_string(template)

import math
from hashlib import md5, sha1

def gen(dword):
    v1 = ((((dword << 13)&0xffffffff) ^ dword) >> 17) ^ ((dword << 13)&0xffffffff) ^ dword
    dword = (((32 * v1)&0xffffffff) ^ v1) &0xffffffff
    return dword, dword & 0x7FFFFFFF


S_BOX_TABLE_7FF65E2BC020 = [0x0000000E, 0x00000004, 0x0000000D, 0x00000001, 0x00000002, 0x0000000F, 0x0000000B, 0x00000008, 0x00000003, 0x0000000A, 0x00000006, 0x0000000C, 0x00000005, 0x00000009, 0x00000000, 0x00000007]

P_BOX_TABLE_7FF65E2BC0A0 = [0x00000001, 0x00000005, 0x00000009, 0x0000000D, 0x00000002, 0x00000006, 0x0000000A, 0x0000000E, 0x00000003, 0x00000007, 0x0000000B, 0x0000000F, 0x00000004, 0x00000008, 0x0000000C, 0x00000010]


def to_u32(n):
    """将一个数转换为32位无符号整数"""
    return n & 0xFFFFFFFF


def to_s32(n):
    """将一个数转换为32位有符号整数"""
    n = n & 0xFFFFFFFF
    if n & 0x80000000:
        return n - 0x100000000
    return n


def generate_salt(dword_array):
    """
    对应 C++ 函数 sub_7FF65E2B1518
    根据硬编码的 dword 数组生成一个32字符的 salt 字符串。
    """
    if not dword_array:
        raise ValueError("错误: dword_7FF65E2BB060 数组为空，请填写数据。")

    s = []
    for i in range(32):
        v9 = dword_array[i]
        v10 = 0

        # C++ int 是32位的，Python int 是无限精度的，需要模拟32位行为
        v9_s32 = to_s32(v9)

        if v9_s32 >= 0:
            v10 = v9_s32 / 3 + 48
        elif v9_s32 >= -728:
            # ~v9 在C++中是对32位整数按位取反
            v10 = ~v9_s32 & 0xFFFFFFFF
        else:
            # 这里的 sub_7FF65E2B31D0 / 1.0986... 被我们分析为 log3
            # math.log(x) 是 ln(x)，math.log(3) 是 ln(3)
            # log3(x) = ln(x) / ln(3)
            try:
                log_val = math.log(-v9_s32) / math.log(3)
                v10 = log_val - 6.0 + 48.0
            except ValueError:
                # 如果 -v9_s32 <= 0，log会出错，这里设置一个默认值
                v10 = 48  # '0'

        # 将计算结果转换为字符
        s.append(chr(int(v10) & 0xFF))

    return "".join(s)


def s_box_transform(state, s_box_table):
    """
    对应 C++ 函数 sub_7FF65E2B16C1 (S-盒替换)
    """
    if not s_box_table:
        raise ValueError("错误: S_BOX_TABLE_7FF65E2BC020 数组为空，请填写数据。")

    s = to_u32(state)
    for _ in range(4):
        # 提取高4位作为索引
        index = (s >> 12) & 0xF
        sbox_val = s_box_table[index]
        # (16 * s) 等价于 (s << 4)
        s = sbox_val | (s << 4)
    return to_u32(s)


def p_box_transform(state, p_box_table):
    """
    对应 C++ 函数 sub_7FF65E2B1785 (P-盒置换)
    """
    if not p_box_table:
        raise ValueError("错误: P_BOX_TABLE_7FF65E2BC0A0 数组为空，请填写数据。")

    s = to_u32(state)
    new_state = 0
    for i in range(16):
        # 获取源比特的位置 (C数组是1-based, Python是0-based)
        source_bit_pos = p_box_table[i] - 1
        # 检查源比特是否为1
        if (s >> source_bit_pos) & 1:
            # 如果是1，则在目标位置i设置比特
            new_state |= (1 << i)
    return new_state


def round_function(state, s_box_table, p_box_table):
    """
    对应 C++ 函数 sub_7FF65E2B17F7 (轮函数)
    """
    state = s_box_transform(state, s_box_table)
    state = p_box_transform(state, p_box_table)
    return state


def generate_round_key(key, round_num):
    """
    对应 C++ 函数 sub_7FF65E2B16A0 (轮密钥生成)
    """
    key_u32 = to_u32(key)
    shift_amount = 4 * (round_num - 1)
    # C++ 代码中 (unsigned int) >> 是逻辑右移
    shifted_key = key_u32 << shift_amount
    return to_u32(shifted_key) >> 16


def encrypt_token(timestamp, r_key, s_box_table, p_box_table):
    """
    对应 C++ 函数 sub_7FF65E2B184D (加密主函数)
    """
    state = to_u32(timestamp)

    # 循环 3 轮
    for i in range(1, 4):
        round_key = generate_round_key(r_key, i)
        state ^= round_key
        state = round_function(state, s_box_table, p_box_table)

    # 循环后的第4步
    round_key_4 = generate_round_key(r_key, 4)
    state ^= round_key_4
    state = s_box_transform(state, s_box_table)

    # 最终返回前的第5步
    round_key_5 = generate_round_key(r_key, 5)
    final_state = state ^ round_key_5

    return to_u32(final_state)


for t in range(1751990400, 1752052052):
    dword = t
    dword, ret = gen(dword)
    cnt = ret
    i = 0
    while i < cnt:
        dword, ret = gen(dword)
        a = ret
        dword, ret = gen(dword)
        b = ret
        dword, ret = gen(dword)
        x = ret
        dword, ret = gen(dword)
        y = ret
        dword, ret = gen(dword)
        cnt = ret
        i+=1
    dword, ret = gen(dword)
    r = ret
    # pow(a | x, 2)
    val1 = math.pow(float(to_s32(a) | to_s32(x)), 2.0)
    # pow(b | y, 2)
    val2 = math.pow(float(to_s32(b) | to_s32(y)), 2.0)

    if math.isclose(0x61 * val1, 0xb * val2):
        cipher = encrypt_token(
            t, r,
            S_BOX_TABLE_7FF65E2BC020,
            P_BOX_TABLE_7FF65E2BC0A0
        )
        query = f"salt=tlkyeueq7fej8vtzitt26yl24kswrgm5&t={t}&r={r}&cipher={cipher}"
    else:
        query = f"salt=tlkyeueq7fej8vtzitt26yl24kswrgm5&t={t}&r={r}&a={a}&b={b}&x={x}&y={y}"
    print(t, query)
    if md5(query.encode()).hexdigest() == "8a2fc1e9e2830c37f8a7f51572a640aa":
        print(sha1(query.encode()).hexdigest())

import os

addr = 0x140371D3A # 这里的地址是压缩内容的地址
endadd = 0x1403772A8-1
dump = [0] * (endadd - addr)

for i in range(addr, endadd):
    dump[i - addr] = get_wide_byte(i)

file_path = r'D:\算法训练\一堆比赛\L3H\dump.br'

with open(file_path, 'wb') as file:
    file.write(bytes(dump))

print(f"Dump written to {file_path}")
import brotli

compressed_file_path = "dump.br"
output_file_path = "dumpp"


content = open(compressed_file_path, "rb").read()
print(f"Compressed file size: {len(content)} bytes")


def try_decompress(data):
    try:
        return brotli.decompress(data)
    except brotli.error:
        return None


for i in range(len(content), 0, -1):
    decompressed = try_decompress(content[:i])
    if decompressed:
        break


if decompressed:
    open(output_file_path, "wb").write(decompressed)
    print(f"Decompressed content written to {output_file_path}")
else:
    print("Failed to decompress the content.")

xor = [0x70, 0x6F, 0x69, 0x73, 0x6F, 0x6E, 0x65, 0x64, 0x20, 0x77, 0x69, 0x6E, 0x64, 0x6F, 0x77, 0x20, 0x72, 0x65, 0x73, 0x6F, 0x75, 0x72, 0x63, 0x65, 0x73, 0x20, 0x74, 0x61, 0x62, 0x6C, 0x65, 0x55, 0x6E, 0x72, 0x65, 0x61, 0x63, 0x68, 0x61, 0x62, 0x6C, 0x65, 0x57, 0x65, 0x62, 0x76, 0x69, 0x65, 0x77, 0x49, 0x6E, 0x76, 0x6F, 0x6B, 0x65, 0x52, 0x65, 0x6A, 0x65, 0x63, 0x74, 0x65, 0x64, 0x43, 0x61, 0x6E, 0x6E, 0x6F, 0x74, 0x44, 0x65, 0x73, 0x65, 0x72, 0x69, 0x61, 0x6C, 0x69, 0x7A, 0x65, 0x52, 0x65, 0x73, 0x70, 0x6F, 0x6E, 0x73, 0x65, 0x43, 0x61, 0x6E, 0x6E, 0x6F, 0x74, 0x53, 0x65, 0x72, 0x69, 0x61, 0x6C, 0x69, 0x7A, 0x65, 0x50, 0x61, 0x79, 0x6C, 0x6F, 0x61, 0x64, 0x45, 0x72, 0x72, 0x6F, 0x72, 0x20, 0x64, 0x65, 0x73, 0x65, 0x72, 0x69, 0x61, 0x6C, 0x69, 0x7A, 0x69, 0x6E, 0x67, 0x20, 0x27, 0x70, 0x6C, 0x75, 0x67, 0x69, 0x6E, 0x73, 0x2E, 0x27, 0x20, 0x77, 0x69, 0x74, 0x68, 0x69, 0x6E, 0x20, 0x79, 0x6F, 0x75, 0x72, 0x20, 0x54, 0x61, 0x75, 0x72, 0x69, 0x20, 0x63, 0x6F, 0x6E, 0x66, 0x69, 0x67, 0x75, 0x72, 0x61, 0x74, 0x69, 0x6F, 0x6E, 0x3A, 0x20, 0x73, 0x72, 0x63, 0x5C, 0x6C, 0x69, 0x62, 0x2E, 0x72, 0x73, 0x64, 0x47, 0x68, 0x70, 0x63, 0x32, 0x6C, 0x7A, 0x59, 0x57, 0x74, 0x6C, 0x65, 0x51, 0x57, 0x72, 0x6F, 0x6E, 0x67, 0x20, 0x61, 0x6E, 0x73, 0x77, 0x65, 0x72, 0x61, 0x74, 0x74, 0x65, 0x6D, 0x70, 0x74, 0x20, 0x74, 0x6F, 0x20, 0x75, 0x6E, 0x77, 0x69, 0x6E, 0x64, 0x20, 0x6F, 0x75, 0x74, 0x20, 0x6F, 0x66, 0x20, 0x60, 0x72, 0x75, 0x73, 0x74, 0x60, 0x20, 0x77, 0x69, 0x74, 0x68, 0x20, 0x65, 0x72, 0x72, 0x3A, 0x20, 0x75, 0x6E, 0x61, 0x62, 0x6C, 0x65, 0x20, 0x74, 0x6F, 0x20, 0x63, 0x72, 0x65, 0x61, 0x74, 0x65, 0x20, 0x74, 0x68, 0x72, 0x65, 0x61, 0x64, 0x20, 0x77, 0x69, 0x74, 0x68, 0x20, 0x38, 0x4D, 0x69, 0x42, 0x20, 0x73, 0x74, 0x61, 0x63, 0x6B, 0x65, 0x72, 0x72, 0x6F, 0x72, 0x20, 0x77, 0x68, 0x69, 0x6C, 0x65, 0x20, 0x72, 0x75, 0x6E, 0x6E, 0x69, 0x6E, 0x67, 0x20, 0x74, 0x61, 0x75, 0x72, 0x69, 0x20, 0x61, 0x70, 0x70, 0x6C, 0x69, 0x63, 0x61, 0x74, 0x69, 0x6F, 0x6E, 0x74, 0x68, 0x65, 0x20, 0x67, 0x65, 0x6E, 0x65, 0x72, 0x61, 0x74, 0x65, 0x64, 0x20, 0x54, 0x61, 0x75, 0x72, 0x69, 0x20, 0x60, 0x43, 0x6F, 0x6E, 0x74, 0x65, 0x78, 0x74, 0x60, 0x20, 0x70, 0x61, 0x6E, 0x69, 0x63, 0x6B, 0x65, 0x64, 0x20, 0x64, 0x75, 0x72, 0x69, 0x6E, 0x67, 0x20, 0x63, 0x72, 0x65, 0x61, 0x74, 0x69, 0x6F, 0x6E, 0x0A, 0x09, 0x00]
s = [0xc, 0x15, 0x25, 0xa0, 0x63, 0x96, 0x40, 0x0a, 0x5c, 0x16, 0x65, 0x40, 0x29, 0x06, 0xe1, 0x1f, 0x90, 0x72, 0x2c, 0xe, 0x4c, 0xa, 0x2, 0xfc]

import struct


def solve():
    """
    根据逆向分析实现的解密函数
    """

    ANON_DATA = xor

    # 这是加密后，程序期望看到的正确结果（27字节的密文）
    # 我们从伪代码中的四次比较中构造出这个目标密文

    # v8[0:8] == 0x0A409663A025150C
    target_qword1 = struct.pack('<Q', 0x0A409663A025150C)

    # v8[8:16] == 0x1FE106294065165C
    target_qword2 = struct.pack('<Q', 0x1FE106294065165C)

    # v8[16:24] == 0xFC020A4C0E2C7290
    target_qword3 = struct.pack('<Q', 0xFC020A4C0E2C7290)

    # v8[19:27] == *(_QWORD *)((char *)v19 + 3)
    # v19 的内容是 qword3 + "O2*" = 90 72 2C 0E 4C 0A 02 FC 4F 32 2A
    # v19[3:] 的内容是 0E 4C 0A 02 FC 4F 32 2A
    target_qword4 = struct.pack('<Q', 0x2A324FFC020A4C0E)

    # 组合成完整的27字节目标密文
    encrypted_target = bytearray(27)
    encrypted_target[0:8] = target_qword1
    encrypted_target[8:16] = target_qword2
    encrypted_target[16:24] = target_qword3
    encrypted_target[19:27] = target_qword4

    print(f"[+] 目标密文 (Hex): {encrypted_target.hex()}")

    # ========================== 解密过程 ==========================

    original_bytes = bytearray(27)  # 用于存放解密后的结果

    # 遍历每一个字节，执行逆向操作
    for i in range(27):
        # --- 1. 重新计算加密时使用的索引和位移量 ---
        v10 = i % 14
        some_index = (2 * i + 1) % 14
        shift = ANON_DATA[(i + 3) % 14 + 184] & 7

        # --- 2. 逆转加密的第3步 (最终异或) ---
        rolled_v11 = encrypted_target[i] ^ ANON_DATA[(i + 4) % 14 + 184]

        # --- 3. 逆转加密的第2步 (循环右移 ROR) ---
        v11 = ((rolled_v11 >> shift) | (rolled_v11 << (8 - shift))) & 0xFF

        # --- 4. 逆转加密的第1步 (减法和异或) ---
        term = (v11 - ANON_DATA[some_index + 184]) & 0xFF
        original_byte = term ^ ANON_DATA[v10 + 184]

        original_bytes[i] = original_byte

    return original_bytes


# --- 执行解密 ---
if __name__ == "__main__":
    print("正在执行解密算法...")
    print("警告：解密所需关键数据 `ANON_DATA` 为占位符，结果无效！")
    print("请务必从程序中提取真实数据并替换 `ANON_DATA`。\n")

    try:
        flag = solve()
        print("-" * 40)
        print(f"[!] 解密出的字节 (Hex): {flag.hex()}")
        # 尝试用UTF-8解码，如果失败则说明结果不是可打印字符
        try:
            print(f"[SUCCESS] 解密出的Flag: {flag.decode('utf-8')}")
        except UnicodeDecodeError:
            print("[INFO] 解密结果不是有效的UTF-8字符串。")
    except Exception as e:
        print(f"[ERROR] 解密过程中发生错误: {e}")

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0x6A, 0x75, 0x76, 0x77, 0x58, 0x77, 0x76, 0x4B, 0x11, 0x72, 0x70, 0x74, 0x10, 0x46, 0x76, 0x67, 0x10, 0x58, 0x44, 0x11, 0x6E, 0x54, 0x75, 0x78, 0x4C, 0x77, 0x41, 0x11, 0x50, 0x70, 0x76, 0x4C, 0x44, 0x4F, 0x76, 0x66, 0x4C, 0x75, 0x73, 0x4C, 0x21, 0x01, 0x76, 0x51, 0x7A, 0x1F, 0x37, 0x5E, 0x42, 0x22, 0x6D, 0x4B, 0x3B, 0x78, 0x45, 0x64, 0x62, 0x41, 0x72, 0x76, 0x79, 0x57, 0x79, 0x77, 0x58, 0x41, 0x44, 0x76, 0x66, 0x53, 0x41, 0x66, 0x44, 0x49, 0x77, 0x66, 0x66, 0x51, 0x24, 0x08, 0x19, 0x00, 0x68, 0x11, 0x43, 0x58, 0x74, 0x4E, 0x6E, 0x78, 0x42, 0x66, 0x50, 0x78, 0x7A, 0x77, 0x54, 0x66, 0x45, 0x66, 0x7A, 0x53, 0x75, 0x4B, 0x44, 0x29, 0x47, 0x4B, 0x11, 0x15, 0x76, 0x67, 0x54, 0x41, 0x79, 0x76, 0x6A, 0x54, 0x75, 0x4B, 0x19, 0x7A, 0x42, 0x25, 0x58, 0x6C, 0x7A, 0x76, 0x7A, 0x41, 0x43, 0x4C, 0x44, 0x54, 0x44, 0x66, 0x6E, 0x6E, 0x76, 0x4E, 0x62, 0x2F, 0x33, 0x1F, 0x54, 0x58, 0x31, 0x45, 0x75, 0x44, 0x73, 0x04, 0x0F, 0x78, 0x5D, 0x66, 0x7B, 0x76, 0x6C, 0x4E, 0x5D, 0x66, 0x6E, 0x4C, 0x72, 0x75, 0x72, 0x4D, 0x54, 0x4A, 0x42, 0x67, 0x72, 0x5A, 0x77, 0x4B, 0x75, 0x15, 0x75, 0x10, 0x43, 0x2C, 0x25, 0x2D, 0x16, 0x39, 0x5A, 0x38, 0x71, 0x57, 0x76, 0x4A, 0x66, 0x41, 0x77, 0x66, 0x6E, 0x52, 0x42, 0x66, 0x37, 0x63, 0x58, 0x12, 0x48, 0x77, 0x76, 0x4D, 0x15, 0x57, 0x76, 0x12, 0x6E, 0x53, 0x75, 0x0F, 0x37, 0x20, 0x07, 0x66, 0x41, 0x4B, 0x6F, 0x67, 0x58, 0x57, 0x6D, 0x66, 0x71, 0x58, 0x7A, 0x67, 0x19, 0x75, 0x42, 0x75, 0x2D, 0x3F, 0x7A, 0x68, 0x50, 0x63, 0x77, 0x66, 0x79, 0x5A, 0x75, 0x4D, 0x48, 0x7A, 0x45, 0x4B, 0x7A, 0x48, 0x30, 0x14, 0x32, 0x41, 0x00, 0x76, 0x59, 0x54, 0x11, 0x32, 0x2F, 0x3B, 0x39, 0x34, 0x14, 0x38, 0x22, 0x50, 0x01, 0x46, 0x60, 0x34, 0x21, 0x24, 0x6E, 0x64, 0x6E, 0x76, 0x42, 0x67, 0x48, 0x53, 0x75, 0x10, 0x44, 0x73, 0x76, 0x76, 0x7A, 0x51, 0x71, 0x4E, 0x0D, 0x35, 0x6D, 0x7E, 0x13, 0x69, 0x69, 0x6B, 0x43, 0x05, 0x48, 0x66, 0x33, 0x03, 0x43, 0x7B, 0x4C, 0x14, 0x3A, 0x26, 0x36, 0x64, 0x37, 0x18, 0x2D, 0x62, 0x6D, 0x5C, 0x66, 0x79, 0x41, 0x66, 0x44, 0x73, 0x72, 0x76, 0x50, 0x16, 0x76, 0x4D, 0x50, 0x67, 0x73, 0x11, 0x06, 0x25, 0x06, 0x24, 0x0F, 0x6D, 0x68, 0x77, 0x58, 0x50, 0x76, 0x4D, 0x54, 0x57, 0x44, 0x4C, 0x7A, 0x53, 0x7A, 0x39, 0x58, 0x5D, 0x41, 0x5A, 0x66, 0x78, 0x75, 0x12, 0x54, 0x4B, 0x41, 0x76, 0x6A, 0x54, 0x31, 0x09, 0x0A, 0x3B, 0x17, 0x38, 0x32, 0x6E, 0x5C, 0x10, 0x7A, 0x77, 0x44, 0x67, 0x72, 0x68, 0x72, 0x4B, 0x15, 0x77, 0x42, 0x78, 0x71, 0x5A, 0x76, 0x44, 0x11, 0x1D, 0x30, 0x5B, 0x25, 0x23, 0x73, 0x53, 0x6E, 0x5F, 0x62, 0x5D, 0x69, 0x6B, 0x74, 0x75, 0x44, 0x4F, 0x6D, 0x11, 0x7A, 0x51, 0x71, 0x78, 0x48, 0x77, 0x6D, 0x4B, 0x15, 0x6A, 0x24, 0x57, 0x0C, 0x1E, 0x27, 0x5F, 0x71, 0x5C, 0x76, 0x4A, 0x72, 0x77, 0x42, 0x78, 0x62, 0x68, 0x28, 0x60, 0x40, 0x6F, 0x76, 0x11, 0x76, 0x55, 0x74, 0x4C, 0x6E, 0x00, 0x22, 0x1A, 0x77, 0x67, 0x6D, 0x5D, 0x58, 0x77, 0x76, 0x4B, 0x4C, 0x58, 0x70, 0x74, 0x10, 0x1D, 0x20, 0x08, 0x42, 0x1C, 0x0D, 0x52, 0x3A, 0x54, 0x68, 0x78, 0x59, 0x67, 0x50, 0x0A, 0x7A, 0x2D, 0x5C, 0x00, 0x00]
s[0] ^= 0x56
xor = b"Vm0xd1NtUXlWa1pPVldoVFlUSlNjVlZyV21GVk1XeDBaRVYwYWxadVFsaFdiWFF3VmxkS1IxTnNXbFpXZWtFeFZsUkdTMk15VGtaYVJtUk9ZbXRLZVZacldtdFNNVnBYVm01R1UySkdXbFJVVnpWUFRURmtjbGRzWkU5U01IQXdWa2QwVjFaWFNrbFJiR2hWVm5wV2NsUlVSbFpsUmxwMFQxZG9UbUV5ZHpCWFYzUmhZekZhYzFacVdtbFNXRkpYV1ZkMGQyUnNVbGhsU0dSVVZqQndSMVpITVc5aFZscFlaSHBLVjJKVVFYaFdSRVp6VmpGS1dWcEdVbWxpVmtwdlZsZDRWazFXU2tkaVJtUllZbTFTV0ZWdGRHRk5WbXQzV2toT2FWSnNjRmRaTUdoM1ZqQXhWMk5JV2xkU1JVVjRWbXBHUjJOV1VuTlNiR1JUVWxWVk1RPT0="
for i in range(1, 2318):
    s[i] ^= xor[i%460]
print("".join(map(chr, s)))

s = [0x75, 0x1B, 0x55, 0x0A, 0x17, 0x58, 0x21, 0x1A, 0x75, 0x6B, 0x5F, 0x67, 0x6B, 0x3B, 0x53, 0x34, 0x33, 0x0A, 0x0D, 0x01, 0x33, 0x66, 0x3F, 0x7D, 0x32, 0x40, 0x2C, 0x46, 0x22, 0x45, 0x7A, 0x0A, 0x3B, 0x5D, 0x5E, 0x33, 0x3E, 0x18, 0x45, 0x3D, 0x15, 0x6C, 0x23, 0x4D, 0x30, 0x7A, 0x2D, 0x5E, 0x53, 0x5D, 0x0D, 0x0F, 0x0D, 0x30, 0x29, 0x01, 0x0C, 0x66, 0x02, 0x05, 0x38, 0x27, 0x32, 0x13, 0x22, 0x04, 0x15, 0x0E, 0x68, 0x3B, 0x43, 0x17, 0x21, 0x1A, 0x6E, 0x2E, 0x07, 0x25, 0x44, 0x78, 0x3C, 0x25, 0x15, 0x21, 0x26, 0x29, 0x36, 0x1C, 0x27, 0x50, 0x6E, 0x5E, 0x20, 0x0A, 0x45, 0x07, 0x76, 0x15, 0x1B, 0x15, 0x71, 0x30, 0x26, 0x1B, 0x34, 0x1F, 0x19, 0x3B, 0x4B, 0x78, 0x29, 0x46, 0x7A, 0x76, 0x7A, 0x41, 0x05, 0x00, 0x0B, 0x15, 0x10, 0x66, 0x3D, 0x6E, 0x6B, 0x4E, 0x31, 0x30, 0x38, 0x45, 0x51, 0x18, 0x69, 0x3B, 0x75, 0x59, 0x73, 0x4B, 0x02, 0x34, 0x0D, 0x27, 0x3E, 0x76, 0x35, 0x4E, 0x4D, 0x77, 0x36, 0x29, 0x21, 0x7D, 0x33, 0x44, 0x4F, 0x60, 0x42, 0x67, 0x72, 0x5A, 0x25, 0x0E, 0x21, 0x40, 0x27, 0x5E, 0x11, 0x24, 0x30, 0x2C, 0x56, 0x7F, 0x02, 0x1E, 0x71, 0x5A, 0x25, 0x46, 0x66, 0x12, 0x7B, 0x66, 0x2D, 0x5B, 0x59, 0x4C, 0x37, 0x63, 0x58, 0x44, 0x0D, 0x34, 0x64, 0x4D, 0x5D, 0x16, 0x25, 0x5A, 0x66, 0x05, 0x30, 0x0F, 0x64, 0x73, 0x12, 0x6F, 0x50, 0x08, 0x5F, 0x4D, 0x58, 0x57, 0x6D, 0x36, 0x71, 0x45, 0x7A, 0x31, 0x5C, 0x36, 0x50, 0x7D, 0x32, 0x5A, 0x2E, 0x60, 0x00, 0x6F, 0x77, 0x30, 0x3C, 0x19, 0x67, 0x45, 0x5A, 0x6B, 0x57, 0x5C, 0x74, 0x59, 0x75, 0x5A, 0x7E, 0x50, 0x4D, 0x67, 0x53, 0x5D, 0x4B, 0x6A, 0x6E, 0x3C, 0x3D, 0x1F, 0x58, 0x29, 0x7A, 0x11, 0x2C, 0x0E, 0x2E, 0x75, 0x79, 0x48, 0x67, 0x58, 0x77, 0x78, 0x57, 0x6B, 0x48, 0x41, 0x6D, 0x03, 0x4A, 0x60, 0x61, 0x7F, 0x73, 0x58, 0x6A, 0x64, 0x44, 0x73, 0x6D, 0x76, 0x02, 0x2C, 0x20, 0x23, 0x11, 0x5B, 0x41, 0x20, 0x28, 0x12, 0x00, 0x32, 0x44, 0x12, 0x3A, 0x26, 0x6A, 0x3C, 0x7F, 0x4A, 0x60, 0x6B, 0x62, 0x65, 0x71, 0x6C, 0x59, 0x68, 0x51, 0x67, 0x67, 0x65, 0x59, 0x0D, 0x5C, 0x10, 0x7A, 0x4D, 0x35, 0x5D, 0x0B, 0x36, 0x17, 0x65, 0x0A, 0x39, 0x0B, 0x24, 0x1D, 0x58, 0x20, 0x08, 0x17, 0x45, 0x44, 0x1C, 0x73, 0x53, 0x21, 0x4E, 0x72, 0x77, 0x41, 0x5A, 0x30, 0x3D, 0x36, 0x00, 0x54, 0x02, 0x41, 0x6B, 0x6A, 0x12, 0x39, 0x03, 0x03, 0x28, 0x4A, 0x24, 0x6F, 0x6F, 0x5C, 0x10, 0x7A, 0x77, 0x44, 0x31, 0x37, 0x2B, 0x60, 0x4B, 0x53, 0x77, 0x5F, 0x78, 0x37, 0x08, 0x37, 0x51, 0x00, 0x47, 0x24, 0x1B, 0x7D, 0x5D, 0x73, 0x4E, 0x6E, 0x4A, 0x24, 0x08, 0x31, 0x53, 0x74, 0x20, 0x44, 0x52, 0x6D, 0x57, 0x7A, 0x5B, 0x71, 0x3E, 0x48, 0x7D, 0x6D, 0x43, 0x06, 0x64, 0x66, 0x12, 0x55, 0x4B, 0x67, 0x1F, 0x7A, 0x76, 0x7C, 0x4A, 0x34, 0x7E, 0x59, 0x52, 0x48, 0x68, 0x75, 0x4A, 0x6A, 0x3D, 0x33, 0x45, 0x23, 0x07, 0x3A, 0x4C, 0x23, 0x00, 0x2A, 0x19, 0x40, 0x75, 0x76, 0x77, 0x58, 0x77, 0x76, 0x4B, 0x11, 0x3F, 0x39, 0x2C, 0x18, 0x59, 0x39, 0x19, 0x18, 0x55, 0x55, 0x1F, 0x7E, 0x54, 0x7E, 0x78, 0x5E, 0x79, 0x51, 0x11, 0x5A, 0x70, 0x3E, 0x0D, 0x17, 0x07, 0x7E, 0x2F, 0x4C, 0x7E, 0x73, 0x1A, 0x2B, 0x09, 0x64, 0x44, 0x6A, 0x57, 0x66, 0x1E, 0x11, 0x77, 0x78, 0x5B, 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0x62, 0x4E, 0x02, 0x3A, 0x23, 0x37, 0x1C, 0x0A, 0x3B, 0x3A, 0x0C, 0x47, 0x41, 0x7B, 0x7A, 0x1E, 0x0A, 0x3E, 0x44, 0x0D, 0x32, 0x31, 0x27, 0x3E, 0x67, 0x46, 0x6A, 0x27, 0x37, 0x2F, 0x23, 0x2B, 0x53, 0x6A, 0x44, 0x00, 0x7A, 0x66, 0x5E, 0x03, 0x7A, 0x4D, 0x5D, 0x77, 0x7D, 0x02, 0x48, 0x77, 0x17, 0x30, 0x12, 0x78, 0x1B, 0x7E, 0x51, 0x4B, 0x5C, 0x67, 0x54, 0x57, 0x44, 0x4C, 0x3C, 0x01, 0x3B, 0x23, 0x11, 0x38, 0x0D, 0x15, 0x34, 0x78, 0x68, 0x12, 0x02, 0x0E, 0x02, 0x62, 0x62, 0x12, 0x3C, 0x02, 0x0D, 0x36, 0x21, 0x3B, 0x2A, 0x3B, 0x24, 0x1C, 0x7A, 0x66, 0x4A, 0x77, 0x7B, 0x73, 0x58, 0x16, 0x3F, 0x00]
s[0] ^= 0x56
xor = b"Vm0xd1NtUXlWa1pPVldoVFlUSlNjVlZyV21GVk1XeDBaRVYwYWxadVFsaFdiWFF3VmxkS1IxTnNXbFpXZWtFeFZsUkdTMk15VGtaYVJtUk9ZbXRLZVZacldtdFNNVnBYVm01R1UySkdXbFJVVnpWUFRURmtjbGRzWkU5U01IQXdWa2QwVjFaWFNrbFJiR2hWVm5wV2NsUlVSbFpsUmxwMFQxZG9UbUV5ZHpCWFYzUmhZekZhYzFacVdtbFNXRkpYV1ZkMGQyUnNVbGhsU0dSVVZqQndSMVpITVc5aFZscFlaSHBLVjJKVVFYaFdSRVp6VmpGS1dWcEdVbWxpVmtwdlZsZDRWazFXU2tkaVJtUllZbTFTV0ZWdGRHRk5WbXQzV2toT2FWSnNjRmRaTUdoM1ZqQXhWMk5JV2xkU1JVVjRWbXBHUjJOV1VuTlNiR1JUVWxWVk1RPT0="
for i in range(1, 1760):
    s[i] ^= xor[i%460]
print("".join(map(chr, s)))