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Tuesday
Jun122012

Preliminary, incomplete analysis of LinkedIn Passwords

Of the passwords that were not cracked by the perpetrators, I've been working on reversing the rest and analyzing the passwords.  At this time, I have broken 698,238 of the non-000000-ed ones from combo_not.txt dump.

 I ran the results of these through pipal and here are some initial statistics:

Top 10 base words
link = 288 (0.04%)
june = 83 (0.01%)
john = 77 (0.01%)
july = 68 (0.01%)
jack = 62 (0.01%)
home = 61 (0.01%)
pass = 60 (0.01%)
blue = 57 (0.01%)
sept = 53 (0.01%)
alex = 53 (0.01%)

Password length (length ordered)
1 = 17 (0.0%)
2 = 27 (0.0%)
3 = 43 (0.01%)
4 = 64 (0.01%)
5 = 102 (0.01%)
6 = 18452 (2.64%)
7 = 42947 (6.15%)
8 = 208920 (29.92%)
9 = 161127 (23.08%)
10 = 113480 (16.25%)
11 = 69077 (9.89%)
12 = 44927 (6.43%)
13 = 21584 (3.09%)
14 = 11944 (1.71%)
15 = 5518 (0.79%)

Password length (count ordered)
8 = 208920 (29.92%)
9 = 161127 (23.08%)
10 = 113480 (16.25%)
11 = 69077 (9.89%)
12 = 44927 (6.43%)
7 = 42947 (6.15%)
13 = 21584 (3.09%)
6 = 18452 (2.64%)
14 = 11944 (1.71%)
15 = 5518 (0.79%)
5 = 102 (0.01%)
4 = 64 (0.01%)
3 = 43 (0.01%)
2 = 27 (0.0%)
1 = 17 (0.0%)
 
One to six characters = 18699 (2.68%)
One to eight characters = 270564 (38.75%)
More than eight characters = 427650 (61.25%)

Only lowercase alpha = 180827 (25.9%)
Only uppercase alpha = 4241 (0.61%)
Only alpha = 185068 (26.51%)
Only numeric = 1124 (0.16%)

First capital last symbol = 16374 (2.35%)
First capital last number = 103966 (14.89%)

Months
january = 19 (0.0%)
february = 17 (0.0%)
march = 200 (0.03%)
april = 209 (0.03%)
may = 1736 (0.25%)
june = 440 (0.06%)
july = 299 (0.04%)
august = 108 (0.02%)
september = 14 (0.0%)
october = 50 (0.01%)
november = 37 (0.01%)
december = 34 (0.0%)

Days
monday = 17 (0.0%)
tuesday = 10 (0.0%)
wednesday = 9 (0.0%)
thursday = 6 (0.0%)
friday = 35 (0.01%)
saturday = 7 (0.0%)
sunday = 23 (0.0%)

Months (Abreviated)
jan = 2949 (0.42%)
feb = 526 (0.08%)
mar = 10029 (1.44%)
apr = 928 (0.13%)
may = 1736 (0.25%)
jun = 1492 (0.21%)
jul = 1669 (0.24%)
aug = 907 (0.13%)
sept = 190 (0.03%)
oct = 696 (0.1%)
nov = 1156 (0.17%)
dec = 913 (0.13%)

Days (Abreviated)
mon = 4437 (0.64%)
tues = 29 (0.0%)
wed = 309 (0.04%)
thurs = 14 (0.0%)
fri = 1082 (0.15%)
sat = 866 (0.12%)
sun = 1724 (0.25%)

Years (Top 10)
2008 = 1624 (0.23%)
2011 = 1605 (0.23%)
2010 = 1349 (0.19%)
2007 = 1168 (0.17%)
2006 = 958 (0.14%)
2009 = 934 (0.13%)
2005 = 763 (0.11%)
2000 = 695 (0.1%)
2004 = 594 (0.09%)
2003 = 558 (0.08%)

Single digit on the end = 106649 (15.27%)
Two digits on the end = 83142 (11.91%)
Three digits on the end = 21164 (3.03%)

Last number
0 = 24173 (3.46%)
1 = 82216 (11.78%)
2 = 34044 (4.88%)
3 = 33782 (4.84%)
4 = 20619 (2.95%)
5 = 19959 (2.86%)
6 = 17228 (2.47%)
7 = 21710 (3.11%)
8 = 20312 (2.91%)
9 = 20092 (2.88%)

Last digit
1 = 82216 (11.78%)
2 = 34044 (4.88%)
3 = 33782 (4.84%)
0 = 24173 (3.46%)
7 = 21710 (3.11%)
4 = 20619 (2.95%)
8 = 20312 (2.91%)
9 = 20092 (2.88%)
5 = 19959 (2.86%)
6 = 17228 (2.47%)

Last 2 digits (Top 10)
23 = 10331 (1.48%)
01 = 9357 (1.34%)
11 = 8553 (1.22%)
12 = 7312 (1.05%)
10 = 5519 (0.79%)
08 = 4953 (0.71%)
00 = 4857 (0.7%)
07 = 4531 (0.65%)
99 = 3428 (0.49%)
13 = 3379 (0.48%)

Last 3 digits (Top 10)
123 = 7570 (1.08%)
007 = 1781 (0.26%)
008 = 1523 (0.22%)
011 = 1403 (0.2%)
234 = 1387 (0.2%)
010 = 1239 (0.18%)
001 = 1117 (0.16%)
000 = 1106 (0.16%)
006 = 917 (0.13%)
009 = 901 (0.13%)

Last 4 digits (Top 10)
2008 = 1355 (0.19%)
1234 = 1223 (0.18%)
2011 = 1221 (0.17%)
2010 = 978 (0.14%)
2007 = 971 (0.14%)
2006 = 770 (0.11%)
2009 = 765 (0.11%)
2005 = 604 (0.09%)
2000 = 559 (0.08%)
2004 = 472 (0.07%)

Last 5 digits (Top 10)
12345 = 277 (0.04%)
23456 = 118 (0.02%)
54321 = 79 (0.01%)
00000 = 51 (0.01%)
55555 = 30 (0.0%)
56789 = 30 (0.0%)
12008 = 27 (0.0%)
21981 = 26 (0.0%)
12006 = 26 (0.0%)
99999 = 24 (0.0%)

 More later when I have a better dataset.