2024 网鼎杯网络安全大赛青龙组 Misc Writeup
题目附件下载地址： https://pan.baidu.com/s/1HmsiauKm_0luI-oa2CvRBA?pwd=8vs5 提取码: 8vs5
题目名称 Misc01
题目附件给了一个MME.cap流量包，wireshark打开查看
附件名字中的MME（Mobility Management Entity）表示移动性管理实体
发现流量包中的协议主要有：DIAMETER、S1AP/NAS-EPS、GTPv2、S1AP
问一问GPT，发现 DIAMETER、GTPv2 是比较可能的方向
因此我们配合过滤器一个个查看流量包，最终在DIAMETER协议中发现关键信息MME-Location-Information
最后把该字段中的值MD5加密一下即可得到flag：wdflag{1f717538aeec1322f446a754d0bcf220}
题目名称 Misc02(赛后复现)
题目附件给了一个未知后缀的flag文件，strings 查看一下发现是Ubuntu22.04的内存镜像
这里我先尝试了制作vol3的symbols，但是做完后发现也扫不出东西
如何制作vol3的符号文件可以参考我的这篇博客以及这个项目
我这里还是写了一个Dockerfile来制作符号文件
把 linux-image-unsigned-6.5.0-41-generic-dbgsym_6.5.0-41.41~22.04.2_amd64.ddeb 和 dwarf2json-linux-amd64 放 src 目录中即可
ddeb的下载链接：http://launchpadlibrarian.net/733303944/linux-image-unsigned-6.5.0-41-generic-dbgsym_6.5.0-41.41~22.04.2_amd64.ddeb
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
|
FROM ubuntu:22.04
# 将环境设置为非交互环境
ENV DEBIAN_FRONTEND=noninteractive
COPY ./src/ /src/
RUN sed -i 's/archive.ubuntu.com/mirrors.ustc.edu.cn/g' /etc/apt/sources.list \
&& sed -i 's/security.ubuntu.com/mirrors.ustc.edu.cn/g' /etc/apt/sources.list \
&& apt update --no-install-recommends\
&& apt install -y openssh-server gcc-10 dwarfdump build-essential unzip kmod linux-base linux-image-6.5.0-41-generic\
&& mkdir /app \
&& sed -i 's/\#PermitRootLogin prohibit-password/PermitRootLogin yes/g' /etc/ssh/sshd_config \
&& sed -i 's/\#PasswordAuthentication yes/PasswordAuthentication yes/g' /etc/ssh/sshd_config \
&& echo 'root:root' | chpasswd \
&& systemctl enable ssh \
&& service ssh start
WORKDIR /src
# 这里的文件名需要根据系统版本进行修改
COPY ./src/linux-image-unsigned-6.5.0-41-generic-dbgsym_6.5.0-41.41~22.04.2_amd64.ddeb linux-image-unsigned-6.5.0-41-generic-dbgsym_6.5.0-41.41~22.04.2_amd64.ddeb
RUN dpkg -i linux-image-unsigned-6.5.0-41-generic-dbgsym_6.5.0-41.41~22.04.2_amd64.ddeb \
&& chmod +x dwarf2json-linux-amd64 \
# 下面这里的文件名需要根据系统版本进行修改
&& ./dwarf2json-linux-amd64 linux --elf /usr/lib/debug/boot/vmlinux-6.5.0-41-generic > linux-image-6.5.0-41-generic.json
CMD ["/bin/bash"]
|
符号文件在Docker中制作好后直接SSH连上容器下载到本地
然后放到 volatility3/volatility3/framework/symbols/linux/ 目录下即可
1
2
3
|
docker build --tag symbols .
docker run -p 2022:22 -it symbols /bin/sh
service ssh start
|
做完符号文件后发现也扫不出东西，因此这道题我这里就直接打算用010手动提取了
首先，我们先用strings看看用户桌面上有什么东西，当然这里也可以直接在010中搜字符串
1
|
strings flag | grep Desktop
|
我们确定了用户名以及桌面的路径，便于我们缩小范围，过滤掉无效的干扰数据
1
|
strings flag | grep /home/ccc/Desktop/
|
可以看到扫出来了很多非常关键的信息，桌面上有很多张PNG图片，然后还有同名的TXT文件
甚至还有内存镜像的vol3符号文件以及制作符号文件的工具（所以我猜测出题人是故意让我们没办法用vol3进行取证）
然后我们到010中搜索那几张图片的文件名
发现用了base64 xxx.png > xxx.txt这个命令，把图片数据以base64编码的格式保存到同名txt文件中
猜测另外几个文件也是同理，因此我们根据PNG的文件头base64编码后的值：iVBORw0KGgo
在010中可以定位到12个位置
依次查看，发现里面有好多个位置表示的都是同一张图片
手动提取出Hex数据，注意这里建议提取Hex数据，直接提取右边的字符串可能会有问题（可能有不可打印字符）
1
|
69 56 42 4F 52 77 30 4B 47 67 6F 41 41 41 41 4E 53 55 68 45 55 67 41 41 41 51 41 41 41 41 45 41 43 41 49 41 41 41 44 54 45 44 38 78 41 41 41 43 76 55 6C 45 51 56 52 34 6E 4F 33 54 4D 51 45 41 49 41 7A 41 4D 4D 43 2F 35 79 46 6A 52 78 4D 46 66 58 70 6E 35 6B 44 56 32 77 36 41 54 51 59 67 7A 51 43 6B 47 59 41 30 41 35 42 6D 41 4E 49 4D 51 4A 6F 42 53 44 4D 41 61 51 59 67 7A 51 43 6B 47 59 41 30 41 35 42 6D 41 4E 49 4D 51 4A 6F 42 53 44 4D 41 61 51 59 67 7A 51 43 6B 47 59 41 30 41 35 42 6D 41 4E 49 4D 51 4A 6F 42 53 44 4D 41 61 51 59 67 7A 51 43 6B 47 59 41 30 41 35 42 6D 41 4E 49 4D 51 4A 6F 42 53 44 4D 41 61 51 59 67 7A 51 43 6B 47 59 41 30 41 35 42 6D 41 4E 49 4D 51 4A 6F 42 53 44 4D 41 61 51 59 67 7A 51 43 6B 47 59 41 30 41 35 42 6D 41 4E 49 4D 51 4A 6F 42 53 44 4D 41 61 51 59 67 7A 51 43 6B 47 59 41 30 41 35 42 6D 41 4E 49 4D 51 4A 6F 42 53 44 4D 41 61 51 59 67 7A 51 43 6B 47 59 41 30 41 35 42 6D 41 4E 49 4D 51 4A 6F 42 53 44 4D 41 61 51 59 67 7A 51 43 6B 47 59 41 30 41 35 42 6D 41 4E 49 4D 51 4A 6F 42 53 44 4D 41 61 51 59 67 7A 51 43 6B 47 59 41 30 41 35 42 6D 41 4E 49 4D 51 4A 6F 42 53 44 4D 41 61 51 59 67 7A 51 43 6B 47 59 41 30 41 35 42 6D 41 4E 49 4D 51 4A 6F 42 53 44 4D 41 61 51 59 67 7A 51 43 6B 47 59 41 30 41 35 42 6D 41 4E 49 4D 51 4A 6F 42 53 44 4D 41 61 51 59 67 7A 51 43 6B 47 59 41 30 41 35 42 6D 41 4E 49 4D 51 4A 6F 42 53 44 4D 41 61 51 59 67 7A 51 43 6B 47 59 41 30 41 35 42 6D 41 4E 49 4D 51 4A 6F 42 53 44 4D 41 61 51 59 67 7A 51 43 6B 47 59 41 30 41 35 42 6D 41 4E 49 4D 51 4A 6F 42 53 44 4D 41 61 51 59 67 7A 51 43 6B 47 59 41 30 41 35 42 6D 41 4E 49 4D 51 4A 6F 42 53 44 4D 41 61 51 59 67 7A 51 43 6B 47 59 41 30 41 35 42 6D 41 4E 49 4D 51 4A 6F 42 53 44 4D 41 61 51 59 67 7A 51 43 6B 47 59 41 30 41 35 42 6D 41 4E 49 4D 51 4A 6F 42 53 44 4D 41 61 51 59 67 7A 51 43 6B 47 59 41 30 41 35 42 6D 41 4E 49 4D 51 4A 6F 42 53 44 4D 41 61 51 59 67 7A 51 43 6B 47 59 41 30 41 35 42 6D 41 4E 49 4D 51 4A 6F 42 53 44 4D 41 61 51 59 67 7A 51 43 6B 47 59 41 30 41 35 42 6D 41 4E 49 4D 51 4A 6F 42 53 44 4D 41 61 51 59 67 7A 51 43 6B 47 59 41 30 41 35 42 6D 41 4E 49 4D 51 4A 6F 42 53 44 4D 41 61 51 59 67 7A 51 43 6B 47 59 41 30 41 35 42 6D 41 4E 49 4D 51 4A 6F 42 53 44 4D 41 61 51 59 67 7A 51 43 6B 47 59 41 30 41 35 42 6D 41 4E 49 4D 51 4A 6F 42 53 44 4D 41 61 51 59 67 7A 51 43 6B 47 59 41 30 41 35 42 6D 41 4E 49 4D 51 4A 6F 42 53 44 4D 41 61 51 59 67 7A 51 43 6B 47 59 41 30 41 35 42 6D 41 4E 49 4D 51 4A 6F 42 53 44 4D 41 61 51 59 67 7A 51 43 6B 47 59 41 30 41 35 42 6D 41 4E 49 4D 51 4A 6F 42 53 44 4D 41 61 51 59 67 7A 51 43 6B 47 59 41 30 41 35 42 6D 41 4E 49 4D 51 4A 6F 42 53 44 4D 41 61 51 59 67 7A 51 43 6B 47 59 41 30 41 35 42 6D 41 4E 49 4D 51 4A 6F 42 53 44 4D 41 61 51 59 67 7A 51 43 6B 47 59 41 30 41 35 42 6D 41 4E 49 4D 51 4A 6F 42 53 44 4D 41 61 51 59 67 7A 51 43 6B 47 59 41 30 41 35 42 6D 41 4E 49 4D 51 4A 6F 42 53 44 4D 41 61 51 59 67 7A 51 43 6B 47 59 41 30 41 35 42 6D 41 4E 49 4D 51 4E 6F 48 71 2B 67 45 2F 51 50 4E 4D 47 49 41 41 41 41 41 53 55 56 4F 52 4B 35 43 59 49 49 3D
|
1
|
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
|
base64解码后可以得到下面这张空白图片，数据很短，也没什么用
然后我们在010中继续往下看，可以把与上面这个图片有重合部分的base64的数据都删掉方便查看
然后在下图这个位置发现了另一张图片，我尝试给它提取出来
1
|
69 56 42 4F 52 77 30 4B 47 67 6F 41 41 41 41 4E 53 55 68 45 55 67 41 41 41 51 41 41 41 41 45 41 43 41 59 41 41 41 42 63 63 71 68 6D 41 41 41 42 47 32 6C 55 57 48 52 59 54 55 77 36 59 32 39 74 4C 6D 46 6B 62 32 4A 6C 4C 6E 68 74 63 41 41 41 41 41 41 41 50 44 39 34 63 47 46 6A 61 32 56 30 49 47 4A 6C 5A 32 6C 75 50 53 4C 76 75 37 38 69 49 47 6C 6B 50 53 4A 58 4E 55 30 77 54 58 42 44 5A 57 68 70 53 48 70 79 5A 56 4E 36 54 6C 52 6A 65 6D 74 6A 4F 57 51 69 50 7A 34 4B 50 48 67 36 65 47 31 77 62 57 56 30 59 53 42 34 62 57 78 75 63 7A 70 34 50 53 4A 68 5A 47 39 69 5A 54 70 75 63 7A 70 74 5A 58 52 68 4C 79 49 67 65 44 70 34 62 58 42 30 61 7A 30 69 57 45 31 51 49 45 4E 76 63 6D 55 67 4E 69 34 77 4C 6A 41 69 50 67 6F 67 50 48 4A 6B 5A 6A 70 53 52 45 59 67 65 47 31 73 62 6E 4D 36 63 6D 52 6D 50 53 4A 6F 64 48 52 77 4F 69 38 76 64 33 64 33 4C 6E 63 7A 4C 6D 39 79 5A 79 38 78 4F 54 6B 35 4C 7A 41 79 4C 7A 49 79 4C 58 4A 6B 5A 69 31 7A 65 57 35 30 59 58 67 74 62 6E 4D 6A 49 6A 34 4B 49 43 41 38 63 6D 52 6D 4F 6B 52 6C 63 32 4E 79 61 58 42 30 61 57 39 75 49 48 4A 6B 5A 6A 70 68 59 6D 39 31 64 44 30 69 49 69 38 2B 43 69 41 38 4C 33 4A 6B 5A 6A 70 53 52 45 59 2B 43 6A 77 76 65 44 70 34 62 58 42 74 5A 58 52 68 50 67 6F 38 50 33 68 77 59 57 4E 72 5A 58 51 67 5A 57 35 6B 50 53 4A 79 49 6A 38 2B 6C 31 76 70 43 67 41 41 49 37 4A 4A 52 45 46 55 65 4A 7A 74 58 55 32 53 56 54 65 79 31 72 56 66 6D 48 67 52 4A 70 36 66 43 63 38 38 4B 67 2F 65 46 75 77 6C 65 41 31 73 6A 2B 6F 6C 77 42 4A 67 45 31 55 39 67 42 46 51 51 4C 67 59 41 42 33 30 65 51 4F 6A 61 6C 32 56 66 76 49 2F 55 2B 66 65 4C 36 4B 6A 38 61 31 7A 70 46 52 4B 79 70 50 4B 50 78 33 2B 76 66 31 37 4F 32 77 70 62 65 6D 51 55 6B 6F 70 48 56 4A 4B 32 37 61 6C 51 7A 6F 63 30 69 46 74 61 64 73 4F 32 2B 47 77 48 64 4B 57 30 6E 5A 49 32 37 64 66 44 79 6B 64 30 69 46 74 57 30 6F 70 62 53 6B 64 44 69 6C 74 4B 61 58 44 64 76 66 37 34 5A 43 6D 2F 33 2F 47 47 57 66 34 34 62 74 44 4F 71 52 30 4F 4B 54 44 33 2F 2B 58 44 69 6D 6C 66 2F 7A 7A 33 65 48 77 54 53 42 38 6B 77 50 35 71 62 38 33 37 64 2F 2F 2B 76 76 76 68 35 51 4F 33 35 34 2B 66 42 4D 4B 2B 66 65 55 55 76 72 48 50 32 2B 4F 2F 72 76 2B 2F 31 50 45 35 66 57 4E 4E 77 6C 6F 63 47 6A 32 47 75 2B 7A 56 78 39 63 2B 75 58 67 78 5A 75 50 64 2F 2B 32 34 4E 74 33 72 52 38 66 58 7A 77 69 4E 58 5A 39 2B 35 6E 64 6C 75 53 67 53 32 5A 53 2B 74 52 61 51 46 7A 2B 65 6D 79 6F 47 63 30 6A 6D 68 35 66 50 41 4C 50 68 53 54 2B 2F 50 55 6E 38 7A 34 68 79 4C 78 71 38 65 7A 33 58 33 35 4D 4B 63 48 57 58 75 75 5A 47 5A 2F 76 39 62 6C 4E 38 50 7A 31 37 65 77 52 4D 4A 35 63 76 52 56 72 61 32 55 61 4B 4B 44 51 76 63 70 59 5A 33 53 57 66 38 65 4F 4B 54 2B 2F 43 69 38 34 6F 50 42 6D 4B 67 41 77 65 50 72 79 76 57 52 7A 5A 68 67 78 54 6C 49 41 72 6F 49 65 50 35 35 63 76 54 58 64 53 43 4D 36 52 72 2F 56 66 2B 38 4A 67 57 68 7A 57 39 4A 48 32 55 75 55 75 53 45 4C 41 4D 6E 4E 50 70 76 51 31 58 44 31 31 79 66 55 38 39 67 46 33 66 75 4E 30 35 38 6E 50 4F 6D 4A 7A 67 75 4D 64 6B 54 42 59 64 76 2B 74 75 4E 37 34 66 4C 36 68 6E 77 6D 50 75 4F 4D 45 73 39 65 66 62 67
|
1
|
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
|
base64解码后很明显可以发现图片尾部是不完整的，但是从刚才第一张图片的尝试中
我们发现图片在内存中是分段存储的，因此我们可以尝试在010中搜索上面base64的尾部数据 tuN74fL6hnwmPuOMEs9efbg
尝试后发现是可以找到后面的数据的，因此我们以此类推，每次拼接后都搜索尾部的数据
最后将所有的Hex数据都提取出来并解码可以得到
1
|
iVBORw0KGgoAAAANSUhEUgAAAQAAAAEACAYAAABccqhmAAABG2lUWHRYTUw6Y29tLmFkb2JlLnhtcAAAAAAAPD94cGFja2V0IGJlZ2luPSLvu78iIGlkPSJXNU0wTXBDZWhpSHpyZVN6TlRjemtjOWQiPz4KPHg6eG1wbWV0YSB4bWxuczp4PSJhZG9iZTpuczptZXRhLyIgeDp4bXB0az0iWE1QIENvcmUgNi4wLjAiPgogPHJkZjpSREYgeG1sbnM6cmRmPSJodHRwOi8vd3d3LnczLm9yZy8xOTk5LzAyLzIyLXJkZi1zeW50YXgtbnMjIj4KICA8cmRmOkRlc2NyaXB0aW9uIHJkZjphYm91dD0iIi8+CiA8L3JkZjpSREY+CjwveDp4bXBtZXRhPgo8P3hwYWNrZXQgZW5kPSJyIj8+l1vpCgAAI7JJREFUeJztXU2SVTey1rVfmHgRJp6fCc88Kg/eFuwleA1sj+olwBJgE1U9gBFQQLgYAB30eQOjal2VfvI/U+feL6Kj8a1zpFRKypPKPx3+vf17O2wpbemQUkopHVJK27alQzoc0iFtadsO2+GwHdKW0nZI27dfDykd0iFtW0opbSkdDiltKaXDdvf74ZCm/3/GGWf44btDOqR0OKTD3/+XDimlf/zz3eHwTSB8kwP5qb837d//+vvvh5QO354+fBMK+feUUvrHP2+O/rv+/1PE5fWNNwlocGj2Gu+zVx9c+uXgxZuPd/+24Nt3rR8fXzwiNXZ9+5ndluSgS2ZS+tRaQFz+emyoGc0jmh5fPALPhST+/PUn8z4hyLxq8ez3X35MKcHWXuuZGZ/v9blN8Pz17ewRMJ5cvRVra2UaKKDQvcpYZ3SWf8eOKT+/Ci84oPBmKgAwePryvWRzZhgxTlIAroIeP55cvTXdSCM6Rr/Vf+8JgWhzW9JH2UuUuSELAMnNPpvQ1XD11yfU89gF3fuN058nPOmJzguMdkTBYdv+tuN74fL6hnwmPuOMEs9efbg79+9hXVmMoWkErInwBMQYgqWROibMe+WzmPeghkfJefGe4xIcWkqjn8bGkeITtB3KGNA0zlQEKRUpSjuj97F/k1YfsQYr7DHMQt3VsgN5ndejHRGkkMelfgSQUmNm7ZTqX8b17ed08fABu28uWrSdccYIFur/5fXN/Agwehnyez0Iqho1Y0a5wXIf9eav+7YKbvnz15+G/tlIKrgWqGPkxj54xB/MADkeztY7JQag2cdIPdgTuGPKqi21nVo11jjKRJi3rKpTjwLWrmQJnpU0Y9vDeIw05neZI0CNF28+3kVNrYRo1mnK8STK0QoCLL9n/Njbce7uCNAK4y2hpbpTIb35Z+OXQskPKE8ljy4pHavVraPTDHnzWx1dOP1g199sc2M3P5dH2jx2jwM4Aw5J7UFaE4G2Vz5nqcVF07w80OIB2Qg4g1QijdWXeQVILmCPzV/3a3mE+03wyDL7KlNjQLTRmiOUAMAcEzjnpLKd8qxJDcTRRqRJloRmwIo0ZrRKCpvZeMu/e/EGvCap1sOZtRYbDy+BURx1BAu5FCBj0RrvnviYYTUmTj9cL1QPotmAK2CPCxgCTHQh9FlqVGXuB/IbtX0suJGGHh+8bevzAcpLMwEASe30YiIU3Jx87cwuKVA2g6Q/WzrsNwpfpZE3OWffuGkA1rnlZb9UaAWpRBd8PWjmZcyet1w7WvNjMYZZenEq/7DqQtSE5iRpJUjt9YtXY6VxetI6+nClbetLOI1wU+8qLJywzdUwEwxW4/eecwnsQePYtoEG4AVIKScoWoxbqUzZ3gWSFPbOJ0kBMOMVKg5Aw9898plifait+PT/+5//phHWgUZgUuZrBH/6DBFiMUZ8sioOw8WoX608i2a2oKSEiSKZpTO8IH09f33rZtiswXHP9d7RHhf0mBBxvWmDOk7IeyAB0GO6hL/YEr1FdupBM5ob/OnL90sdwyRA5WW5Pq3WjrgNIPKirwWApnFKqm6ABiQ0hFUMe5Dx9HgeRXBp7inxgiCYhbFaHIBkG9w+W/UDOXRZWp613lkZWuOdzetRHAAFUpV2sND+AklL/yhFUTXatY6lj2JrmWEFGsXqAXDzrVfM17aqjLMib1ZCaZFfhc9ia8JS2uSvNtff33u+1b7WFUsa0n2FL4YXPHmzZ8+DqQCIwrwodOwJq/IUYxCdfUywPIhgZFSrCNRCFPXq5x++N+/z8vrGJejEqix2a26tg3Io75d010Fe9ZjqIjezEvgz+kIUF21JhegGq21bxw3VgnUWHeS96Jb6VTWM6EgUNcQya1DKPiCFVXL6zzij5SquEaoqsGW9eet7BWb9rZQPMALUOm19t8De6vljMFp7oQTA6ji769bCakKBur567z179QFeFbhnTOoZt6zu3YsCThl07dLnmZ9SpdopfVPeub79rFpiu978nvcItsZW01NvYui66QmNd1++2t4NaOX2mMUBUOIQIrhsIsPa9nG2tcAxSoK7pwE8e/UBdaMv5utSStxaemGk+0zylfRDVDyIWrWSqugB66MPpT8PDQiLch9Ab5SejWtke7onAP789SeUfzP/7d2Xr0MiUjoeUH2/HGZCMcYjjGCxXiCjK9Yp6ihH3dbso4UerzWPf6sJ8dHGfXzx6I5X1HEdXQ/Oye3Pv2mF3a4KyPEjOjwq10YFJvZklTgV17Lg1sDGL3BzAmbvjwSmBH96i3CVxZmBDcldBVLxNJC10uvLzA2o7SJbzY9O4Yem24rql/dwfa7mbo1Ebz3PZrkA2gx4fPFI9OrsESTcdhRaR5t/RvPMvtHb/LN28zigZ/ce7zA8lcrlkLY3jHgsYZ+RoPfePIvoIMaYqTwzFVf6+GFdqEKrtiHmfUiYaWREDme3pIF9BKCE1FqH4VJQ0ghR4SJEldV0RlI9oYh2lFuRhxiw7wWgbOTff/lRRJ3RjKArx7VKnAD3XgUJYFyprShSaZq560yCnpEqn//di3iE0k8ep6kewkRkVUoDFGu9FX3at9d41ai0hvdVdV0BoFUGabUJGiHiZarRXGRWxUZ7zz59+R5km8nPtOa03gtRypNJPDvNBYi+YaPTtwpafKw1EO3aDKPnRxtzpTwErRgMakGXIwEwIi5/WfZ2ccQI5aLzvk+g9+5KwroHywKrEK1N8kgSHUMbQGvQEdVeDVgIsFKdpKjuPRo9L/mw/sLNfr/66xN680b/eEnS524EXFGyYtKJz/5yXjuaNg3vS1YyT6Q1TQzuCQBI/DqHSGsjlefGw4zV23iHPeJZoXeXRO9ZCv3evPcE+giQ0VJDvBYPVj1cBV4XlJzhB45Nh6JlkaoCS1h3r/76ZH7Win62k8Cp+M81YHkkoFSl0kBazag3o9fSogx5LtrGmvm5IaCOUysHA/oMVdWHfpVX20v33IAcRDHWRNtwq8B68UoaR63nXPqKMCwk208eG+ZUNmm0M7xldR+NvsqN19qEVkKs7nuV9dw6Aru7AUeoGQuJTHty9dZFG9nT2Zvi5oQ8qwlJOrDGby1Y8DK0AJhhNhlSkxVlkdfQDs3dA3oaCUaoUfrjQEKLgr7rKgCspHbGSDOAqo8SCydS8VRqNhrlWY6RNKoHR6Kuo6fA6QoAaYZz1XKM4QXalxTjZ+2c4pc3IjSFiGUw0ZOrt92xQOgo1+PSRwANeBpFIX1nTUVK1ZQUXmdBpw/O/JOMgKccJikF75hzC1UU0kZ0ARHNazPqX8r+I6IBWC6wSNAM/LEImjmF+ciIakPAQnrOSAIAmpiBxWqRVCNgJPVIy7JKS7YG5Pgh0QflbxLPl/MmWcV59g5WYx8KAC/13yNkdK/QDMzRhDa9VMEagY9Y2kfxNORswBm0hUc0bWF1FdOD/qj2Je4G0wLWwg/5O+tmoFEpYqky2b0+oNdYad42W+KqUaLcqm8IZrR43NOAvekIck39bJyQOSl5MStz/uzVB5Py6y/efDziV28cNS2z8aIuBpG4JKFsI8KlC7078TRpizDuM9aG1BrqagAtyYGVLi2UbTy+eJRevPlIbmsGyBfj4uGDOxpKYJh7eX3TbKNHC/Y+PQ4wfWhetLIq6nnFrFdNfop9QKBnByqevnzPOq9HSS6hPLO6XSCDOgfR7DQ9UPIFeufxCEZCDEhGQO1BRjUOURCpDrxkf9qbO7fPvZvgjDGmRkDIUUAaLeMQ5H41KUi2RzWutWgo1VHIHJQGLIxRDTLnUCPsCCM+5/Zr/p1tJ8IopUEk6Qr5ckZUsaOFk3rM6Sqq/wjWV8zPoNXfORkICK0wU26k4J6gVb9BGpE+lBlYm0TmNSoO4Pr2853ahrkGGtN+jZZ1XdNjgPU/pzRX80fWYIhnxfvqcUl+j9rKsRQaV3pLjiHCMaTeF3/++hPquH63ZiWkTyR1iFtsI0tGaPkxTr8a0IgvPyMepOYZHQlIMQpKf7FH/f3vg/9C95nbu779fCcZIcan8rd3X76C+9P0/1O+Tr13IkUy9rACjRRojKs5z1RpApUwlGe4kDQOrvJ19C5VbQVKht9exq6B3RoBPW7O3ba1FlvEDRONf9HoqYG5KKc1lqYAoA4aEkkV0XVnjagpuhw7xp4CdiBrVMrmg6ktiX2uRG9MagVBLBDR3xzFGAgB9pow7SIaVm3tCZQ9QC4KGlFlnAET332GHTjzoiH4uYJ71XU19QLU/v6WTzuCX7QHCG3cMONRTISnlRqSjVbSjs1e4+Te1/OCmadRGPIsK7OHP3/96Y4Xl9c3qDDplOz3AGRdlc90+bJtupVcV64SywE3eUayXHcEQC4gaZ1TqefiFcOtqSXYoXY1sBGQShSlrZbqRWVE1DpyGVD6oKWfKEeySIJDkxaJtq145Rm8FepqsNWA+ZJJts9539JI+fTl+/DxCRbViXv9er6fYaoBQEEJKPJeSJkGq+IZkpqP5Cbw9BS0YOUpKnmo6c7LkPrIuGkAUlGDezsrrwTs/Kw8F1brzEJDK/tQEQArT/QIXsLGi5/Qfq2qA5Xw0lik+2/BshYBqyBIrTpG3fhUK2n0uAdJqzkF0nyQOop4netXhEggEBcWk0VRraQviKCM8+nL99336r9pFV/dy2aCrAGJYp8RhWsPotmAUHhYya1zEHJ/FK2KupFXrL7cA+cs7D0W7/4xGGoAKyXulIsfowJ6nOtHbUbMb6BAahwtXmlvMI8+vaB2N6AkNM6a0YERviuMRwtS3qQaz1/fhuKr1sf4KBcAGrdufYOMdJy1xA1HKenyAVNOfMQf6tg0aj5KoXXLUol6Xijrh1rOncI3yDr6/ZcfddablCTxTIPVMrpc/fUp1FfAEhKBVqfKOwtI7TdwTcCZ9LGsXFtX8J190alfwYuHD9SzvKjZa1zMst3yuPMXjcKHPwBfUelsyRk/vfgdFUe3A1vdWruX23H3Mo4zThdHGoDVYpY6g1vC44o0LkZ3HZyBQ3knxgyjegI13DWS8kyxJ8tzdPpK9JJIJDLpIrsVvcunSfAmekrzDPeMgBaGr2gGJWwWF7Q9LURJN9Zsd9SGhOCQzFqM8rGhjKnrBZg1FvnLEgmW6aicv3Ph/TVfAdA5kAhHhuK72rrfs6zXkLgeuodsedbwe3LOZpSz9OtP/yK9h31nNl8YewWm7/wsxgukEWOgYeeAnM8xdhZIzEJKfV5i5hDM41Ia5K/VSNL01E9ttZ6i9kbP5jsDB4l589ZUJDVCCX6oFwThqDMr5SJsm//i4oJyzqXMUbR5hWxKTuFNyN8ofW0bbs2V7WZawPUA9vDVtBjDaDFFW/hcRF0TEutYwwbmza9W/7u9GzACIBPOdfX1CrJoZzF6eTpmmXoeng2q5mftQmz9dhQJCIVFBNz17WcxQ6MWvdh26+ehBtcVIM3j3vyfoy9lMcwF6FnhLSYAu/lHFtvHF4/QN71A0OID5DaccuP//MP33echNxSN+rOMAJytCSwtzzvzGSWK9MWbj+J9u2RgqukgRtA6V2sY9LzPgGfQYKmqSxhbIfaJphFQAxrXKO8dpxxkBXFFawLb72iuZm2N9oZpTUAtaHgVVvPta4cX782zYI1I64YiTKAf2N779wTA3jemJD2Wfn8JjwL3PYty2ytV1KVA+pJYar9iRwBvVY0reLQCkjB8keSh9iaNvLn2DI0gom0DagCnfCbVRiRjI/RWYk9YV2ke/d2bF1i0hMORG7Dn9tNM/Dl1vPvyFfTcs1cfpskpdVxBqzRa+b96vusklFERFGjZtd7vGJeXtqtv5sLsuWq94xFGPGzt5avGb6BAoFZQxh4CMjTGgG3z2asPavUUL69v0m8PH9xN/M8/fH8kcH7+4fvups/PRptjyQCxHvawtltojeu78o89tBg+YlDkktIcQMYVbeH8/suP6fHFo/T44lH689ef7v6d/zujLmNVaybSX2FMea0Ss80vQad0UFMUtDSZOwHQGzSlZpnWF01CbZzVlB+9W28YCcyOALkfTG0ECm2lYLAApB9IJKQHtHl0eX1zt+8o4+6tlea+tDRCzKKeJC33JTSMmFI30miNmfN+Lgu3ovFX0jDnXTPQgv/gewEkUEvO2X9D2+khawzYMyOlusuKVYN7yPzSOmtTKz1Rq+5QITF+Dj0WxndTAcAFVh2mHkUok0ad6FZ2YInSsi+pBs94qCm8Lh4+IB9TSkSwNWFKgkU6xtxBXcdQREu9OofG3ofURZejHHPqcY7ar8a73JiMaNWuIRATAJYD8WYaBVyaZ+fBWWJJ632rTWs1XxLCf4VQZ8n+l9AAvL/qVoY6LVCMplHHMoN3aDr09yhwtwFAznHlVc3Yc5+FX3j23IiG+iwuXQqdMv5cjKPH65ZruPdsq3/MszPM3tG8wn3mUtYOKJJY26SSYJaQZCKmrb1clPrizcd0dfuZfC9ANE/GjF/QSMG9RvthwdYAvOO0Ibi8vknPXn1ABZ+M3HzaY5Zs//dffgRd010jj7/82kewYktdWLPy5h9pwbM5uue1gJ4Vop9laqxizPEItsln/Py/2oCYbS5YI6FmWfnV1p8nMLxqCoBVNk8UrG4k3Lb7QmFUV0C6aAwHFmXARx4NCo8iXSBzJwD2XkSC8/Vq3ahiDetKORqeAG9vzl6Bnafy+akGYD1p2jX0LMGZGC3UX/YIfMJCak1GdHdyL4rBQjwOIJqUrxc8lT6M2uaxqCxsCaVtwDvyD6J6z8rGQfryEOL1GtVcT1MBEE1C9uB9rvLoX8voZjXnGkLjVEraSfGuGwfw4s3HowAcLiwquVgg4jik54oCrl9dszISFpw5hvIhwpylNIgDmBGHregiuWk40V1cX7bEOKT86bmdCAuJ61fX3vwYnuc5hr5Txkr0+FD77r3m7N7eEdEjBOB51FjlmKMF7Th2D/7uaU5bY5E6coYPBV4VWcWTUm25NxFjUNK8Wsis9RFtNf7UAIUCQ0pAe4eJzvqn1DbkIKt4UqotdvP/9q3oxos3H9FHppJmTL8SPOauo96twlpYcfMfFYAV0SO+IYrahaGjfpaqWkUZuxYgLjVsW6PfIkUbSvZFKVCi6cUIYwPoYUWXlGab22br1sL2ZeUO7fE202vtll31A6AWCKQZKIKB1cam5gOMApNWECDRAr+gaAkIDaOnJK811oOrBqAdkrqC9Xn2JZNGr7+nL98f/a33BR2Nr6Q5SvDNql9mDbTmtJkMFIFpGumjEbP2JPvCfI17/Up+0bXPyJrtjrIhZ+1G2D8t1ALgydXbtgZgpdZFZVQP1hl5kdqPNFeYTRcxIavuy1NbuucGvLy+QUcpUV03HD81FlgXVcv12aJXs+YcBdJuqcxrSlUhLWDGiL3nj8o/zj0HrqHlPcmwqnEnY9Uv7Qirz4kXOF9YTZ5rz+fI0Jn7do8DgBTbkKquwvUtjwxoVEQ6J2sDeq7mAJPjL2n1nwmZqHMWPg6gBcmCEBj0audlaG1m7Vh9LrTcXhRI5/dz+9N+n4t7AuDJ1f0ikVaQYgZFQOxVvfZcYD2eQtbXk6u3bnOCFWLemxiKVgxKMxegF79ONfYdxR4PUF6AyYkJp6RaQt7RynfQvORS0iiIHX+Pp5D8iMcXj0jzmNcaJy8Ba5TDGhqpkF5/V7efU5I8B1mrqpZlqFaR8qcIb1989LXRi87dtuoIIHmWi84UbczUXO8jR/QQVW5/VP7ODL51u97ziMEwEnBvkKqXR90op5ZVaJFfEJk3kWkbzc2RDQB7xhg9j7kQE/OuBDDn4vI8iKGLWgdgxfzylO6fmzVsOBF507tKDvpuj0+Se6CemyP7yEhyRJZq26ZX+ZZTT0Ab0eekRHRaW5pG9DoE0q7mJY4APRUG4rLUNBRGX+ArYqSuepd+HyHaWoAaRk1rAkYq/bw31LkKq9eqwyDaWGfrHErv6Llc9o1dXbiWDBJSNoqk1swaOxV4R/bV6GlhFvOHKeYi2Q/0b5T2wxwBuG6b/O+9bGQtQQUVztE2fg9R5xtDl0QdB2qbIAHQ6pRayirqhNWgVMSxhIY9gmMAswqfjeJ3j7IOuEDbAKKdtzwRlRdR6aKCOx7puwI0+Os1Z6B7AUqMiOT4LiX9oVZ3FDy+eDSMaWjR0Yv7z89i8gJ648QsJM08hBEwc4QZT2s+MJsfmrMy6o8CyBjLuZKK2Tk8uXq7rWQ9lpTm0ceqjevbz+n1p3+J31Mn7e3BtHf2NOEg5gaMspmi0AHBs1cf0rsvX+/+++cfvkct3izVa3dQlJtnz2gD+xGr13R+X2See8YByUIHWLfgqgaWPE7PSylW5R0V0cYrmV1rgTBuQCwomyxaNZhThEetRo95kuxTwyWb6VMTAFGCgTKg9HjXBeCWsa7dZJ7zwHH11ReVaOBU8jjC5QJIJlzM/OGcApFRviZeaAkXS4EieQzFtrVKIBQXKgIg0iaJKHUt27BsP1qYtbawirDOuQFh4gIAIjk1pSs3lXf2flleyXMBeH+hvAvHYnlvdeVZhEjFmSAu1w7JDch1tVHf5xRfoPRD6SuqG7Km6xRdhbO5iTp3mpgKgFNkChZaPIrAeykapMNxS0TgExTRaJ2GAlsRu2LJ7QxsqCp0rBwtqeyjdc8hFJkG7vxobH5JjVBi/ZWltnrlvriaszh6ZwaO9dwCmDMo9+ourKFFumxTiUjuVUlasBmn3jYQLCLYBlpAGQEjW6W51tAIFt0WotKlCU46uUeRjpUxtAHs2VBkeRbTPP+ecbrIa5izvoY2gNbm555DrFJ1Zxht/pHdgGJTgE4OlTfXt5/Ztg7JeeGkyEZZH1bgjDev4dn6GvVx2LZt87RMavYNbfucQhobluuT01c0Cz8E36WkV+QDAirDel+Z8ndo29Kbn3OJ6orA0A3RDur2LDcVpy/NDxnn2eFv2/Yfi+rTl+9NrataF3tI9yXZhjSo3gNtYxp1HWnwWPqiFw6NGl4czlxNvQDR4ruxiEhnPWFRaIxChyZWHKNm6XNUIBA1RDa/l9W/nkpDMWTN1KNoZzKuZ2V07z3XECjJK2itROtjD3SMJV11gI81Ms0qa1lcpCgDq+5ApSfE92yVANRKY7X6cpX99GoLaBRjif5ljk4fFWgBEC0CayYQMBMnMTaPhSJxqcroN0tYrS/vcWoDOj4xDSAaQ6PREwk1b6iGKUjBjZ7xUTM0tjceqHDRvtgmUljwPQHQGmDJUKoKDsXz17fqcfFSsfpe2lDu17rGocTC5RxpJI9g3NBxyXY0PlZQr89QA9ir64yLPY5JEtjEHqk+euj1Lenyk14TkI+LRJ/sIwB2YmdfbcykRNiIml9h76o7Gu1QBIFEvIj2lznCWqQglBcgEhOp6qaUKolB+bXQtrZf/fWp+XXSDODZS2ZnxkgItoS+5nhCCQAOpM500nRIvRd9UWPtISuWK/cG1UYzMtYeCQCoZF+VgSPUC3K2QCGqrDWfrI2C0tBaa3tcrxBAxq2qAUQKedU810q+FymGHgtr95Z33oBHe5j23QWAFrxcLRE2WQs9bSVS+TBrcIUR5n1JdzBXs4TEZpRAlQX3yneW6pdTjlxj3Ne3n9PzNx/D5SvsAStUYSrXlUb1rXz79HB9UaQMBdG+ntHo0UAeI0YTkHC5YdGjr2cT0C5GGgESdEH4lFZRE/fmCtKA5ZgjfiC857wnnCB0WUeVZpqWtAGsBmvfrkb73PZKHoxiLGbxF/nvvQ0jES7sLUhqGqjeEbYRMMpXV8JHjjWOeCAqXSUienIkQ3q1MPrCe9JGuhvQGnso2pmLdaw+Dg2sVEyTesdiNAP0Hd3WEsdbEmvAw3Bm1Q9H++JmjkaJ7oRAkjbLHIQUKbGmBW+6vLLBtMENIGkhikF5DwZFCZBsANEHDqEvykKkIBL/n1y9DVW8QgO1cZIDKK88U6NrLGEDaIF6NvK87myls64UWmNeIUhnbyjnofx3syow92KL3vujirZYUDeS1uaHjA1D86zC7yqXiLTGjN38rbFyrh/j9l0CUomZMleX1zci+6V1hfrRnEirFHsEhB+eqvKMvuyCWkmdHxkAVz7ilaAa+yRTx0legJUW0gwSab8z9IJTogvaWXQa1UrvFS+CAScyT0NASY2tHhdYAFBLOdWEewsPaet3Ho+3KzC6MGlh1XHndR2J59R1vctQ4ChfAg606w5wgdVoIm2WGlEiXj0QQgCMvqLSG3C1GPyo8NDkoLyVdO1pIQpd5gJA24BjEfOvHakVgW6J9yBoCfiVjHxeG5lzyUn5m6gAiHZtGOWcJjWhFgsD8hW++utTmK8NR2vQyvCLwhtt9MaZIAyQ3EQSRjMrWNK4Aj+4kHRfQSGZiu2R1q0NsgbgPXBpweU9HklwVX1vT8226SQCSRwteryJwLNtw/MtTCjwqim/EqHFmjUHzyG3fP7uiY81L5qhwNgGJQDZ/JTQSO2QWczm79GilR9QL1rL8OFIocpc/mpufms+1by4EwBUQiDMhbRdP9OK9Z5ttsvrm3vtSG0uidjzGS3UmHGp/iX79aoe7Q0IDeWHzDs5LMwRYASMCieh7j3/NkF1O9hjilQVmFE7I5r2pLqeoYMwAqC1yOvFfYrptFaA8tbzboiUZL6Y5/sYCujYItsWSGlL+wqx5NLtWwbJcC3bETwrUvyKsnZngT3YQDi3UGAtBvR+G8UfUKP1MLHvlAjF/Bx3EUfYiJKwGM+K6ccUvhwdAVZWsa1px/a3Mm8hyOOzGufe+WmFIzegJEOfvfpg6razXgyQ/krPAZa+GR80LN4jT8doLsvNyJ0H6LjK8lbUNiTooL4XwWORUjq2AUjGamPVXO2qO7N3pZN29qZ2Z2iPSzOfxCMUmdPX7JgpsV9DewEs35dqL7+nVXyUolV5FUHVgNY8R1t/mL5GY+jRdfc7RFpAjSAa8dCnnMWlOca98c/rck2t57XbyQCFAr/78hUkmSy/NKdgAKJqIJS2R+9BKt9qAHNO5gY8Yc/k2LmRWq/S656dC9CDlJEDO2DJ0uOWkCpz3eMXJ3TXI0lLUqWGrMWsQluj7NNF0EqrF16qTrRiJBHAMWxCj311HxLzEPF4AqXJ8hgsgaEAsCiv5Q3JIA9vHnH7f/761n0MNaQ21EqFPy2jU48EgGXEGXaQ1EpCXCHmtRAiuaygiEhTdJQCzoN/Ym7AnHkGObtpF/84R4mtAYzb6gwaZvwUMwJmK+wfAE+AtlEJG6XXg5f1eyVwDGetedIyxo3apPQXxdjMrcswFADYsMbL65tl8s9bdNaXm1pav7mLXiMkVnrTQCGtAYy+gj0tpET+WJS/Y13ekpeZlnS0UuhHH6578zY6H8zCdDXOLFbBL6W9I0pBxxLRwlJL1PyilF/XRjR6tMAdZ4I2wl0kWujRFWmDR1mM2UXnFWEYhQ8c9NZSFoLPX98ukz68bd8EgPcGmWE1TYPav1UBDu7YPRe4dtKYFGY8osZLSK9bdkEQbWZ7b1RNaGhes/c1A6b2eHHGSqDMbZhswDN0EaVQx6xQKYbOVe+SSIk2H5QM0xmPwG7AMAUMOmi5ZbSKRVBR911aayWsxKOxWfnWZ/3Um78eN6bMfF7YEkU4rN16lBLxo83fWz+tzX80VoiaYFmDTTofQSqcOaKlGwOpWogWiHyUiEKHFNSyAbGQKinVa7f+N1YT+O3hg5ARar1x1F+0XtBNRLz78hVEPxQ9HmHXQMQoxXIMJO3WWwLtAZ6ZYiNolGWr4XHlt6S2CKFlpUSiGjPDoJoRUMpAs7KhJyq0ypWlZHuLk1WbUdGLYvzt4QP4/HqngEr33cqushxfPr9a166n/N0aXBuMVtunDNIR4BSZvcqYJQqpRA5DjhAUloX8ShF/GfV8J8wgoi4MzPkt+kZecVF5QDMiMOqewGJG2/PXt9t3ueAnxA8N9dFeXt/cs+K2fkvp7/Po6Frv1t8wdNV/0yy0iX22hbO9429IXD9OtXPUF9LW/x5l482guZawz1/dfu57AaiSTeMCjhmk24wi1b1j2qXzFaLwNSNSHUkP3jy5ejv3AnCsqtmCr2WZjWDxlaIhwlioyNdtp/SfL2KOcmxpNLOrvsv2Whbt1hdYg3+zsOWMSJ4qLB/OuQBn3MNsg2r2+8cvP6bnbz6SLl6NfkFsDaiASaktZKju3LLf/wcOsj2d8Pa/YQAAAABJRU5ErkJggg==
|
base64解码后即可得到下面这张图片
赛后和别的师傅交流的过程中发现有的师傅说这里直接 foremost 也可以得到这张图片
虽然是不完整的，但是 zsteg 一下也可以得到下面的 Hint
感觉这里也算是非预期吧，出题人如果隐写的内容不放在开头，可能就要把图片完整提取出来才行了
之前睿抗也遇到过这样的情况，也算是给自己提了个醒，以后出题别把隐写的内容放在图片头部(坏笑)
zsteg一下，发现有一个Hint：Y3p_Ke9_1s_?????
``
然后我们在回头查看那个内存镜像，尝试一下常用的文件头，看看有没有别的文件
发现存在 7z 的文件头 37 7A BC AF 27 1C ，内存镜像的末尾藏了一个7z压缩包
因此我们手动提取出来，然后结合刚才的提示 Y3p_Ke9_1s_?????，猜测是压缩包掩码爆破
因此我们使用 ARCHPR 爆破上面提取得到的 7z 压缩包
爆破后得到压缩包解压密码：Y3p_Ke9_1s_29343
解压压缩包后得到 flag.txt ，内容如下：
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
|
31 226 PUSH_NULL
228 LOAD_NAME 8 (key_encode)
230 LOAD_NAME 7 (key)
232 PRECALL 1
236 CALL 1
246 STORE_NAME 7 (key)
32 248 PUSH_NULL
250 LOAD_NAME 10 (len)
252 LOAD_NAME 7 (key)
254 PRECALL 1
258 CALL 1
268 LOAD_CONST 7 (16)
270 COMPARE_OP 2 (==)
276 POP_JUMP_FORWARD_IF_FALSE 43 (to 364)
33 278 PUSH_NULL
280 LOAD_NAME 9 (sm4_encode)
282 LOAD_NAME 7 (key)
284 LOAD_NAME 5 (flag)
286 PRECALL 2
290 CALL 2
300 LOAD_METHOD 11 (hex)
322 PRECALL 0
326 CALL 0
336 STORE_NAME 12 (encrypted_data)
34 338 PUSH_NULL
340 LOAD_NAME 6 (print)
342 LOAD_NAME 12 (encrypted_data)
344 PRECALL 1
348 CALL 1
358 POP_TOP
360 LOAD_CONST 2 (None)
362 RETURN_VALUE
32 >> 364 LOAD_CONST 2 (None)
366 RETURN_VALUE
Disassembly of <code object key_encode at 0x14e048a00, file "make.py", line 10>:
10 0 RESUME 0
11 2 LOAD_GLOBAL 1 (NULL + list)
14 LOAD_FAST 0 (key)
16 PRECALL 1
20 CALL 1
30 STORE_FAST 1 (magic_key)
12 32 LOAD_GLOBAL 3 (NULL + range)
44 LOAD_CONST 1 (1)
46 LOAD_GLOBAL 5 (NULL + len)
58 LOAD_FAST 1 (magic_key)
60 PRECALL 1
64 CALL 1
74 PRECALL 2
78 CALL 2
88 GET_ITER
>> 90 FOR_ITER 105 (to 302)
92 STORE_FAST 2 (i)
13 94 LOAD_GLOBAL 7 (NULL + str)
106 LOAD_GLOBAL 9 (NULL + hex)
118 LOAD_GLOBAL 11 (NULL + int)
130 LOAD_CONST 2 ('0x')
132 LOAD_FAST 1 (magic_key)
134 LOAD_FAST 2 (i)
136 BINARY_SUBSCR
146 BINARY_OP 0 (+)
150 LOAD_CONST 3 (16)
152 PRECALL 2
156 CALL 2
166 LOAD_GLOBAL 11 (NULL + int)
178 LOAD_CONST 2 ('0x')
180 LOAD_FAST 1 (magic_key)
182 LOAD_FAST 2 (i)
184 LOAD_CONST 1 (1)
186 BINARY_OP 10 (-)
190 BINARY_SUBSCR
200 BINARY_OP 0 (+)
204 LOAD_CONST 3 (16)
206 PRECALL 2
210 CALL 2
220 BINARY_OP 12 (^)
224 PRECALL 1
228 CALL 1
238 PRECALL 1
242 CALL 1
252 LOAD_METHOD 6 (replace)
274 LOAD_CONST 2 ('0x')
276 LOAD_CONST 4 ('')
278 PRECALL 2
282 CALL 2
292 LOAD_FAST 1 (magic_key)
294 LOAD_FAST 2 (i)
296 STORE_SUBSCR
300 JUMP_BACKWARD 106 (to 90)
15 >> 302 LOAD_GLOBAL 3 (NULL + range)
314 LOAD_CONST 5 (0)
316 LOAD_GLOBAL 5 (NULL + len)
328 LOAD_FAST 0 (key)
330 PRECALL 1
334 CALL 1
344 LOAD_CONST 6 (2)
346 PRECALL 3
350 CALL 3
360 GET_ITER
>> 362 FOR_ITER 105 (to 574)
364 STORE_FAST 2 (i)
16 366 LOAD_GLOBAL 7 (NULL + str)
378 LOAD_GLOBAL 9 (NULL + hex)
390 LOAD_GLOBAL 11 (NULL + int)
402 LOAD_CONST 2 ('0x')
404 LOAD_FAST 1 (magic_key)
406 LOAD_FAST 2 (i)
408 BINARY_SUBSCR
418 BINARY_OP 0 (+)
422 LOAD_CONST 3 (16)
424 PRECALL 2
428 CALL 2
438 LOAD_GLOBAL 11 (NULL + int)
450 LOAD_CONST 2 ('0x')
452 LOAD_FAST 1 (magic_key)
454 LOAD_FAST 2 (i)
456 LOAD_CONST 1 (1)
458 BINARY_OP 0 (+)
462 BINARY_SUBSCR
472 BINARY_OP 0 (+)
476 LOAD_CONST 3 (16)
478 PRECALL 2
482 CALL 2
492 BINARY_OP 12 (^)
496 PRECALL 1
500 CALL 1
510 PRECALL 1
514 CALL 1
524 LOAD_METHOD 6 (replace)
546 LOAD_CONST 2 ('0x')
548 LOAD_CONST 4 ('')
550 PRECALL 2
554 CALL 2
564 LOAD_FAST 1 (magic_key)
566 LOAD_FAST 2 (i)
568 STORE_SUBSCR
572 JUMP_BACKWARD 106 (to 362)
18 >> 574 LOAD_CONST 4 ('')
576 LOAD_METHOD 7 (join)
598 LOAD_FAST 1 (magic_key)
600 PRECALL 1
604 CALL 1
614 STORE_FAST 1 (magic_key)
19 616 LOAD_GLOBAL 17 (NULL + print)
628 LOAD_FAST 1 (magic_key)
630 PRECALL 1
634 CALL 1
644 POP_TOP
20 646 LOAD_GLOBAL 7 (NULL + str)
658 LOAD_GLOBAL 9 (NULL + hex)
670 LOAD_GLOBAL 11 (NULL + int)
682 LOAD_CONST 2 ('0x')
684 LOAD_FAST 1 (magic_key)
686 BINARY_OP 0 (+)
690 LOAD_CONST 3 (16)
692 PRECALL 2
696 CALL 2
706 LOAD_GLOBAL 11 (NULL + int)
718 LOAD_CONST 2 ('0x')
720 LOAD_FAST 0 (key)
722 BINARY_OP 0 (+)
726 LOAD_CONST 3 (16)
728 PRECALL 2
732 CALL 2
742 BINARY_OP 12 (^)
746 PRECALL 1
750 CALL 1
760 PRECALL 1
764 CALL 1
774 LOAD_METHOD 6 (replace)
796 LOAD_CONST 2 ('0x')
798 LOAD_CONST 4 ('')
800 PRECALL 2
804 CALL 2
814 STORE_FAST 3 (wdb_key)
21 816 LOAD_GLOBAL 17 (NULL + print)
828 LOAD_FAST 3 (wdb_key)
830 PRECALL 1
834 CALL 1
844 POP_TOP
22 846 LOAD_FAST 3 (wdb_key)
848 RETURN_VALUE
magic_key:7a107ecf29325423
encrypted_data:f2c85bd042247896b43345e589e3ad025fba1770e4ac0d274c1f7c2a670830379195aa5547d78bcee7ae649bc3b914da
|
发现是python的字节码，内容是加密了密钥然后用SM4算法加密了flag，手搓一个脚本逆向一下密钥
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
|
def restore(mk):
magic_key = [_ for _ in mk]
for i in range(0, len(mk), 2):
magic_key[i] = hex(int("0x" + magic_key[i], 16) ^ int("0x" + magic_key[i + 1], 16)).replace("0x", "")
for i in range(len(mk) - 1, 0, -1):
magic_key[i] = hex(int("0x" + magic_key[i], 16) ^ int("0x" + magic_key[i - 1], 16)).replace("0x", "")
return "".join(magic_key)
def encode_key(key):
magic_key = [_ for _ in key]
for i in range(1, len(key)):
magic_key[i] = hex(int("0x" + magic_key[i], 16) ^ int("0x" + magic_key[i - 1], 16)).replace("0x", "")
for i in range(0, len(key), 2):
magic_key[i] = hex(int("0x" + magic_key[i], 16) ^ int("0x" + magic_key[i + 1], 16)).replace("0x", "")
magic_key = "".join(magic_key)
wdb_key = hex(int("0x" + magic_key, 16) ^ int("0x" + key, 16)).replace("0x", "")
return wdb_key
print(encode_key(restore("7a107ecf29325423")))
|
得到SM4的密钥为：ada1e9136bb16171
最后CyberChef解一个SM4即可得到flag：wdflag{815ad4647b0b181b994eb4b731efa8a0}
题目名称 Misc03
题目附件给了一个流量包，翻看流量包发现有upload.php的路由
并且发现都上传了一句话木马，因此过滤器过滤一下upload.php，然后试一下这几个ip
最后发现 wdflag{39.168.5.60} 是正确的flag
题目名称 Misc04
题目附件给了下面这张图片：
之前在某个群里好像有看到过类似的，感觉是希尔伯特-皮亚诺曲线
根据参考链接中的脚本复原一下图片
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
|
from PIL import Image
from tqdm import tqdm
def peano(n):
if n == 0:
return [[0,0]]
else:
in_lst = peano(n - 1)
lst = in_lst.copy()
px,py = lst[-1]
lst.extend([px - i[0], py + 1 + i[1]] for i in in_lst)
px,py = lst[-1]
lst.extend([px + i[0], py + 1 + i[1]] for i in in_lst)
px,py = lst[-1]
lst.extend([px + 1 + i[0], py - i[1]] for i in in_lst)
px,py = lst[-1]
lst.extend([px - i[0], py - 1 - i[1]] for i in in_lst)
px,py = lst[-1]
lst.extend([px + i[0], py - 1 - i[1]] for i in in_lst)
px,py = lst[-1]
lst.extend([px + 1 + i[0], py + i[1]] for i in in_lst)
px,py = lst[-1]
lst.extend([px - i[0], py + 1 + i[1]] for i in in_lst)
px,py = lst[-1]
lst.extend([px + i[0], py + 1 + i[1]] for i in in_lst)
return lst
order = peano(6)
img = Image.open(r"C:\Users\ASUSROG\Desktop\chal.png")
width, height = img.size
block_width = width # // 3
block_height = height # // 3
new_image = Image.new("RGB", (width, height))
for i, (x, y) in tqdm(enumerate(order)):
# 根据列表顺序获取新的坐标
new_x, new_y = i % width, i // width
# 获取原图像素
pixel = img.getpixel((x, height - 1 - y))
# 在新图像中放置像素
new_image.putpixel((new_x, new_y), pixel)
new_image.save("rearranged_image.jpg")
|
复原后可以得到一个二维码，彩色的可能不好识别，分离一下通道，扫码即可得到flag：
wdflag{4940e8dc-5542-4eee-9243-202ae675d77f}
最后，有兴趣的师傅也可以尝试复原一下下面这张图片(感觉比上面的简单)
但是感觉可以帮助大家理解原理
参考链接：
https://zhuanlan.zhihu.com/p/305623626
https://almostgph.github.io/2024/01/08/IrisCTF2024/
Lunatic