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%) | || || || || ||| ||| ||| ||| ||| ||| ||| ||| ||||| |||||| ||||||||||||||||| 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…… | | | | | | | | | | | | | || | || |||| |||| |||||||||| |||||||||| |||||||||| |||||||||| |||||||||| 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/
[文/FreeBuf小编xia0k 参考来源:darknet.org.uk 转载请注明:FreeBuf.COM]