在很多情况下，我们需要进行各种各样的分析工作，这里为大家介绍一款密码分析工具——Pipal。
Pipal是一款密码分析工具，功能主要是进行密码合集文件分析。说白了，就是对拿到的裤子中的密码进行特征分析，找出其中的“各种最”，你没看错，这个东西功能就是这么简单。。不过，工具的分析的速度还是很快的，同时也会从各个方面给出相应的分析结果。工具是作者为了满足自己和朋友的需要写的，现在被挂在了Git上面，这里我搬运过来，希望能为大家带来帮助。
工具安装
这个不用多说，git一下就好了：
git clone https://github.com/digininja/pipal.git /opt/pipal
运行环境
Pipal是运行在ruby下的，需要的ruby版本是1.9.x，其他环境会报错无法运行，这点需要大家注意一下。
简要介绍
工具本身带的参数不多，我们可以使用./pipal.rb -?来查看帮助界面：
可用选项不多，也很简洁。只说一下里面的top参数。top参数指定在所分析的密码文件中位于最高频率的前N位，N即为top的参数，比如我们需要待分析的密码文件中的频率前50的密码，我们可以使用:
./pipal.rb --top 50 exmple.file
默认的top值为10.
使用很简单，直接在命令后面跟上待分析的文件就可以了，比如我这里随便分析一个文件
./pipal.rb 100W.txt
会显示一个进度条
分析的速度也是比较快的。我这里找了一个100W左右的文件作为示例(9.4M)，大约用了不到5分钟的时间就给出了分析结果。
分析结果
root@linvex:/opt/pipal# ./pipal.rb 100W.TXT
Generating stats, hit CTRL-C to finish early and dump stats on words already processed.
Please wait...
Processing: 100% |ooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooo| Time: 00:03:54
Basic Results
Total entries = 1000001
Total unique entries = 999754
Top 10 passwords
palaeodendrologi = 4 (0.0%)
palaeodictyopter = 4 (0.0%)
microspectroscop = 3 (0.0%)
hypsibrachycepha = 3 (0.0%)
hypsidolichoceph = 3 (0.0%)
hypsistenocephal = 3 (0.0%)
labyrinthibranch = 3 (0.0%)
microcinematogra = 3 (0.0%)
hyperdolichoceph = 3 (0.0%)
nonrepresentatio = 3 (0.0%)
Top 10 base words
ghjkl = 635 (0.06%)
guest = 379 (0.04%)
pass = 378 (0.04%)
love = 378 (0.04%)
info = 378 (0.04%)
happy = 378 (0.04%)
lady = 378 (0.04%)
moon = 378 (0.04%)
money = 378 (0.04%)
lucky = 378 (0.04%)
Password length (length ordered)
1 = 1 (0.0%)
2 = 38 (0.0%)
3 = 354 (0.04%)
4 = 1306 (0.13%)
5 = 30082 (3.01%)
6 = 49142 (4.91%)
7 = 54443 (5.44%)
8 = 206435 (20.64%)
9 = 286516 (28.65%)
10 = 325970 (32.6%)
11 = 19805 (1.98%)
12 = 14092 (1.41%)
13 = 4702 (0.47%)
14 = 3017 (0.3%)
15 = 1897 (0.19%)
16 = 2201 (0.22%)
Password length (count ordered)
10 = 325970 (32.6%)
9 = 286516 (28.65%)
8 = 206435 (20.64%)
7 = 54443 (5.44%)
6 = 49142 (4.91%)
5 = 30082 (3.01%)
11 = 19805 (1.98%)
12 = 14092 (1.41%)
13 = 4702 (0.47%)
14 = 3017 (0.3%)
16 = 2201 (0.22%)
15 = 1897 (0.19%)
4 = 1306 (0.13%)
3 = 354 (0.04%)
2 = 38 (0.0%)
1 = 1 (0.0%)
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00000000001111111
01234567890123456
One to six characters = 80923 (8.09%)
One to eight characters = 341801 (34.18'%)
More than eight characters = 658200 (65.82%)
Only lowercase alpha = 819102 (81.91%)
Only uppercase alpha = 0 (0.0%)
Only alpha = 819102 (81.91%)
Only numeric = 0 (0.0%)
First capital last symbol = 0 (0.0%)
First capital last number = 0 (0.0%)
Single digit on the end = 6178 (0.62%)
Two digits on the end = 10472 (1.05%)
Three digits on the end = 45573 (4.56%)
……SNIP……
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0123456789
……SNIP……
根据上面的回显我们大体就可以看出分析结果中所包含的部分，主要有密码频率TOP N，词语频率TOP N，密码长度频率分析(同时从序列和排名两项给出)，更加创新的在terminal中给出了一个图形化的分析(这点可是让作者本人十分自豪的说)，等等还有很多，大家可以自行挖掘。
最后放上git地址，防止有人问我为什么不给下载链接：https://github.com/digininja/pipal/
