Cryptanalysis

Kifflom message

Join us in something special and become one of the children of Kraff.
Travel through the dawn to the pass pictured in our brochures. Look for a red truck
with a dent on the right fender. Raise your left hand and recite the words: "Take me to
to my father-father, brother-uncle. Kifflom." We'll do the rest. Because we all know,
there is Kifflom and there is Krant, and both be praised.
Blindfold required.


This text...How many hunters tried to understand it, along all those years, hundreds hypothesis were made,
but still no good answer...

Perhaps because nobody managed to "read between the lines", as Marvin Trill says in Area53:

""Caller #5: Neil, about aliens
Caller #5;
- My name is Neil, I go to a lot of demonstrations to pick up religious pamphlets, none of them say anything about the aliens.

Marvin Trill;
- Try reading between the lines, and if that doesn’t work, do some, then you’ll understand all about the aliens,
and just where you are planted.""



To "read between the lines", to look for a hidden message inside one other is called "Cryptanalysis",
the analysis of encrypted messages.

What if this message was hiding a code, a word, or numbers?
that's perhaps why nobody managed to understand it, because they were too focused on the hints given in the text,
like the dented red truck, or the pass, without to see the real meaning of all that stuff ?

The repetition of the words "to", and "father", are a perfect indication of a encrypted message !
So let's try here, to look closely at this message, and read between the lines...



Let's start by the most simple, anagrams !

Let's try some of them !

"Take me to to my father-father, brother-uncle. Kifflom."

And here the most interesting result:


"melee me be a farm try to honk the truck at fifth floor"



Here are the most readable anagrams for Brother uncle.
totally there are 1747 so this surely deserves more attention.


Butcher Loner
Bench Ruler To
Cuber El North
Rebel Corn Hut
Brothel Rec Nu
Brothel Cur En

And funny inappropriate ones:
Boner Curl The
Herb Cunt Lore




The 2 most important words:

To + Father =


After hot
Threat of
Hate Fort
Fat Other
A Theft Or
At The For



We can also take the first letters of each words of the sentence
"Take me to to my father-father, brother-uncle. Kifflom"

T-M-T-T-M-F-F-B-U-K

-Then, translate them in numbers:
20-13-20-20-13-6-6-2-21-11
2-4-2-2-4-6-6-2-3-2 = 33

In fact we can do anything we want, and that's why this Hunt is so interesting !
However, the coding seems to be more complex, so for the ones that aren't scared by numbers,


Cryptanalysis always start with a frequency analyse of the letters of the texts, to see if the ratio of each letter is usual,
here usual in English, but also to see if the hidden message is in English, or in another language.
Let's take a look to all the info about letters in the text,


Frequency analyses of different languages for comparison
:

Here is a comparison with English, German, French, Spanish, Latin.
single, Di, Tri grams with the same book (Genesis) for best comparison.


English single gram:

No. Substring Frequency (in %) Frequency

1 E 12.7558 19436
2 A 10.2934 15684
3 H 8.8174 13435
4 T 8.8036 13414
5 N 7.4299 11321
6 O 6.7776 10327
7 D 5.9375 9047
8 S 5.8049 8845
9 I 5.5136 8401
10 R 4.9577 7554
11 L 3.4213 5213
12 M 2.6468 4033
13 F 2.4467 3728
14 U 2.2859 3483
15 W 1.9951 3040
16 Y 1.7635 2687
17 B 1.7333 2641
18 C 1.6631 2534
19 G 1.5712 2394
20 P 1.2207 1860
21 V 1.0068 1534
22 K 0.6110 931
23 J 0.4227 644
24 Z 0.0722 110
25 X 0.0368 56
26 Q 0.0118 18

English Digram:

No. Substring Frequency (in %) Frequency

1 TH 5.7794 6576
2 HE 5.1703 5883
3 AN 4.3644 4966
4 ND 3.9030 4441
5 ER 2.0179 2296
6 RE 1.7129 1949
7 HA 1.6839 1916
8 IN 1.5732 1790
9 HI 1.5134 1722
10 TO 1.3464 1532
11 AT 1.2866 1464
12 OF 1.2735 1449
13 IS 1.2515 1424
14 EN 1.2339 1404
15 ED 1.1548 1314
16 SE 1.1408 1298
17 OU 1.1012 1253
18 NT 1.0933 1244
19 AR 1.0529 1198
20 ON 0.9448 1075
21 ME 0.9421 1072
22 VE 0.9413 1071
23 OR 0.9105 1036
24 LL 0.8956 1019
25 EA 0.8771 998
26 SA 0.8674 987

English Trigram:

No. Substring Frequency (in %) Frequency

1 THE 5.4448 4155
2 AND 5.3754 4102
3 HER 1.2750 973
4 HIS 0.9999 763
5 HAT 0.8924 681
6 NTO 0.8780 670
7 UNT 0.8636 659
8 ALL 0.8033 613
9 FOR 0.7456 569
10 THA 0.7247 553
11 AID 0.7076 540
12 ERE 0.6801 519
13 ING 0.6762 516
14 SAI 0.6408 489
15 HIM 0.5753 439
16 HOU 0.5661 432
17 EAR 0.5504 420
18 TER 0.5399 412
19 AME 0.5281 403
20 ATH 0.4796 366
21 ITH 0.4678 357
22 WAS 0.4547 347
23 GHT 0.4534 346
24 SHA 0.4442 339
25 SON 0.4324 330
26 WIT 0.4220 322

German singlegram:

No. Substring Frequency (in %) Frequency

1 E 16.0735 24751
2 N 10.7211 16509
3 A 7.6312 11751
4 I 7.2539 11170
5 R 7.1318 10982
6 D 6.5675 10113
7 S 6.3571 9789
8 H 5.7057 8786
9 T 5.1920 7995
10 U 4.4459 6846
11 M 3.0970 4769
12 L 2.9483 4540
13 C 2.7535 4240
14 G 2.5489 3925
15 O 2.4100 3711
16 B 2.3755 3658
17 W 1.5326 2360
18 F 1.2066 1858
19 K 1.1176 1721
20 Z 0.9962 1534
21 V 0.7741 1192
22 P 0.6280 967
23 J 0.4604 709
24 Y 0.0682 105
25 Q 0.0032 5

German Digram:

No. Substring Frequency (in %) Frequency

1 ER 4.3590 5091
2 EN 4.1766 4878
3 CH 3.4402 4018
4 ND 3.0455 3557
5 DE 2.9728 3472
6 UN 2.7981 3268
7 IN 2.5327 2958
8 TE 2.4590 2872
9 EI 2.4085 2813
10 IE 2.0626 2409
11 GE 1.7612 2057
12 NE 1.7458 2039
13 SE 1.5343 1792
14 ES 1.3922 1626
15 BE 1.3657 1595
16 AN 1.3177 1539
17 RA 1.2167 1421
18 HE 1.1696 1366
19 IC 1.1422 1334
20 DA 1.1396 1331
21 AU 1.0608 1239
22 DI 1.0557 1233
23 HA 1.0343 1208
24 ST 1.0078 1177
25 RE 0.9804 1145

German Trigram:

No. Substring Frequency (in %) Frequency

1 UND 3.3511 2733
2 EIN 2.3150 1888
3 ICH 1.6161 1318
4 INE 1.4959 1220
5 DER 1.4726 1201
6 ACH 1.2678 1034
7 CHT 1.1452 934
8 DIE 1.1121 907
9 DEN 1.0815 882
10 TER 0.9601 783
11 SEI 0.9405 767
12 SCH 0.9233 753
13 SIE 0.8767 715
14 NEN 0.7394 603
15 TEN 0.6928 565
16 RAC 0.6633 541
17 ABE 0.6450 526
18 HER 0.6057 494
19 SPR 0.5984 488
20 BER 0.5935 484
21 GEN 0.5886 480
22 PRA 0.5751 469
23 BEN 0.5579 455
24 AUF 0.5493 448
25 NDE 0.5383 439

French singlegram:

No. Substring Frequency (in %) Frequency

1 E 15.3988 21991
2 A 8.6969 12420
3 S 8.3664 11948
4 T 7.6752 10961
5 I 7.1970 10278
6 N 6.9050 9861
7 R 6.7999 9711
8 L 5.9457 8491
9 U 5.8623 8372
10 O 5.2531 7502
11 D 3.8940 5561
12 C 2.9662 4236
13 M 2.8772 4109
14 P 2.8233 4032
15 V 1.7639 2519
16 H 1.3809 1972
17 F 1.3255 1893
18 B 1.0819 1545
19 Q 1.0461 1494
20 J 0.9229 1318
21 G 0.7962 1137
22 X 0.3998 571
23 Y 0.3830 547
24 Z 0.1982 283
25 K 0.0406 58

French Digram:

No. Substring Frequency (in %) Frequency

1 ES 2.7355 2836
2 LE 2.5561 2650
3 EN 2.5339 2627
4 DE 2.3149 2400
5 RE 2.2986 2383
6 ON 2.1683 2248
7 NT 2.1047 2182
8 ET 2.0960 2173
9 IT 1.7893 1855
10 OU 1.7729 1838
11 IL 1.6793 1741
12 AN 1.6639 1725
13 AI 1.6571 1718
14 ER 1.6320 1692
15 TE 1.5645 1622
16 UR 1.5298 1586
17 SE 1.4565 1510
18 QU 1.4227 1475
19 RA 1.3832 1434
20 EU 1.3369 1386
21 LA 1.2028 1247
22 IS 1.1498 1192
23 NE 1.0253 1063
24 AR 1.0186 1056
25 UI 1.0051 1042

French Trigram:

No. Substring Frequency (in %) Frequency

1 ENT 1.5999 1097
2 LES 1.3053 895
3 OUR 0.9378 643
4 QUE 0.8867 608
5 ILS 0.8270 567
6 EUR 0.8255 566
7 SON 0.8095 555
8 OUS 0.8080 554
9 ANT 0.8036 551
10 LLE 0.7890 541
11 REN 0.7642 524
12 AIT 0.7613 522
13 TER 0.7161 491
14 DIT 0.7059 484
15 FIL 0.6651 456
16 DES 0.6607 453
17 ANS 0.6126 420
18 MME 0.6111 419
19 TOU 0.5688 390
20 DAN 0.5601 384
21 CHE 0.5498 377
22 QUI 0.5382 369
23 POU 0.5309 364
24 AIS 0.5250 360
25 TRE 0.5163 354

Spanish singelgram:

No. Substring Frequency (in %) Frequency

1 E 13.3437 18581
2 A 12.2730 17090
3 O 9.4471 13155
4 S 8.2155 11440
5 R 6.5681 9146
6 N 5.9842 8333
7 L 5.4657 7611
8 D 5.3049 7387
9 I 5.1993 7240
10 U 4.2104 5863
11 T 4.0474 5636
12 C 3.3451 4658
13 M 2.9882 4161
14 P 2.1602 3008
15 H 2.0927 2914
16 B 1.8614 2592
17 Y 1.6567 2307
18 J 1.4822 2064
19 V 1.2747 1775
20 Q 1.1576 1612
21 G 0.9092 1266
22 F 0.5759 802
23 Z 0.3986 555
24 X 0.0381 53

Spanish Digram:

No. Substring Frequency (in %) Frequency

1 DE 3.0194 3074
2 OS 3.0165 3071
3 ES 2.5784 2625
4 EN 2.5293 2575
5 ER 2.4065 2450
6 UE 2.0696 2107
7 RA 1.9812 2017
8 LA 1.9213 1956
9 EL 1.7602 1792
10 RE 1.6973 1728
11 AR 1.6207 1650
12 QU 1.5834 1612
13 ON 1.5618 1590
14 AS 1.4213 1447
15 DI 1.3309 1355
16 AN 1.3172 1341
17 TO 1.2916 1315
18 LO 1.2867 1310
19 DO 1.2828 1306
20 IE 1.2632 1286
21 NT 1.2307 1253
22 CO 1.2180 1240
23 RO 1.1522 1173
24 SE 1.0923 1112

Spanish Trigram:

No. Substring Frequency (in %) Frequency

1 QUE 1.8199 1276
2 LOS 1.1381 798
3 IER 0.9841 690
4 ENT 0.9670 678
5 EST 0.9499 666
6 IJO 0.9484 665
7 CON 0.7630 535
8 ERO 0.7530 528
9 ARA 0.6817 478
10 RON 0.6703 470
11 HIJ 0.6504 456
12 END 0.6332 444
13 BRE 0.6218 436
14 RES 0.6133 430
15 JOS 0.6004 421
16 PAR 0.5833 409
17 TIE 0.5833 409
18 POR 0.5619 394
19 NTE 0.5591 392
20 NTO 0.5448 382
21 RRA 0.5348 375
22 ADO 0.5263 369
23 ERR 0.5249 368
24 DIO 0.5092 357

Latin singlegram:

No. Substring Frequency (in %) Frequency

1 E 13.3437 18581
2 A 12.2730 17090
3 O 9.4471 13155
4 S 8.2155 11440
5 R 6.5681 9146
6 N 5.9842 8333
7 L 5.4657 7611
8 D 5.3049 7387
9 I 5.1993 7240
10 U 4.2104 5863
11 T 4.0474 5636
12 C 3.3451 4658
13 M 2.9882 4161
14 P 2.1602 3008
15 H 2.0927 2914
16 B 1.8614 2592
17 Y 1.6567 2307
18 J 1.4822 2064
19 V 1.2747 1775
20 Q 1.1576 1612
21 G 0.9092 1266
22 F 0.5759 802
23 Z 0.3986 555
24 X 0.0381 53

Latin Digram:

No. Substring Frequency (in %) Frequency

1 DE 3.0194 3074
2 OS 3.0165 3071
3 ES 2.5784 2625
4 EN 2.5293 2575
5 ER 2.4065 2450
6 UE 2.0696 2107
7 RA 1.9812 2017
8 LA 1.9213 1956
9 EL 1.7602 1792
10 RE 1.6973 1728
11 AR 1.6207 1650
12 QU 1.5834 1612
13 ON 1.5618 1590
14 AS 1.4213 1447
15 DI 1.3309 1355
16 AN 1.3172 1341
17 TO 1.2916 1315
18 LO 1.2867 1310
19 DO 1.2828 1306
20 IE 1.2632 1286
21 NT 1.2307 1253
22 CO 1.2180 1240
23 RO 1.1522 1173
24 SE 1.0923 1112

Latin Trigram:

No. Substring Frequency (in %) Frequency

1 QUE 1.8199 1276
2 LOS 1.1381 798
3 IER 0.9841 690
4 ENT 0.9670 678
5 EST 0.9499 666
6 IJO 0.9484 665
7 CON 0.7630 535
8 ERO 0.7530 528
9 ARA 0.6817 478
10 RON 0.6703 470
11 HIJ 0.6504 456
12 END 0.6332 444
13 BRE 0.6218 436
14 RES 0.6133 430
15 JOS 0.6004 421
16 PAR 0.5833 409
17 TIE 0.5833 409
18 POR 0.5619 394
19 NTE 0.5591 392
20 NTO 0.5448 382
21 RRA 0.5348 375
22 ADO 0.5263 369
23 ERR 0.5249 368
24 DIO 0.5092 357

This should give an good baseline which can be used for different analysis methods.

Here is the complete cryptanalysis of the Kifflom message !!!
Frequency analysis of the Kifflom message

Frequency analysis in the whole message we get:

No. Substring Frequency (in %) Frequency

1 E 13.2911 42
2 R 8.8608 28
3 T 8.8608 28
4 O 7.9114 25
5 A 6.3291 20
6 H 6.3291 20
7 N 6.0127 19
8 I 5.6962 18
9 D 5.3797 17
10 F 4.4304 14
11 L 4.4304 14
12 S 4.1139 13
13 U 3.1646 10
14 C 2.8481 9
15 K 2.5316 8
16 B 2.2152 7
17 M 1.8987 6
18 W 1.8987 6
19 P 1.2658 4
20 G 0.9494 3
21 Y 0.6329 2
22 J 0.3165 1
23 Q 0.3165 1
24 V 0.3165 1

Then, after a letter analysis, comes the time for Digrams, which is basically the frequency of 2 letters which come after each other, also giving indications about the language and/or encryption method, and able to point unusual parts of the texts.
So for a digram on the whole text we get:

No. Substring Frequency (in %) Frequency

1 TH 6.2500 15
2 HE 4.5833 11
3 RE 4.1667 10
4 ND 2.9167 7
5 AN 2.5000 6
6 ER 2.5000 6
7 IN 2.0833 5
8 RA 2.0833 5
9 EC 1.6667 4
10 ED 1.6667 4
11 IS 1.6667 4
12 OM 1.6667 4
13 UR 1.6667 4
14 BE 1.2500 3
15 EN 1.2500 3
16 FF 1.2500 3
17 LO 1.2500 3
18 ME 1.2500 3
19 OU 1.2500 3
20 RO 1.2500 3
21 SE 1.2500 3
22 TO 1.2500 3
23 AI 0.8333 2
24 AL 0.8333 2

Message only:

No. Substring Frequency (in %) Frequency

1 E 13.5802 33
2 T 10.6996 26
3 R 9.8765 24
4 O 7.4074 18
5 A 6.9959 17
6 H 6.9959 17
7 D 4.9383 12
8 N 4.9383 12
9 I 4.5267 11
10 L 4.1152 10
11 S 4.1152 10
12 F 3.7037 9
13 U 3.2922 8
14 K 2.8807 7
15 C 2.4691 6
16 W 2.4691 6
17 B 2.0576 5
18 M 1.6461 4
19 P 1.2346 3
20 G 0.8230 2
21 Y 0.8230 2
22 V 0.4115 1

Digram of the message :

No. Substring Frequency (in %) Frequency

1 TH 7.1429 13
2 HE 5.4945 10
3 RE 3.8462 7
4 ER 3.2967 6
5 AN 2.7473 5
6 ND 2.7473 5
7 IS 2.1978 4
8 RA 2.1978 4
9 UR 2.1978 4
10 ED 1.6484 3
11 LO 1.6484 3
12 OU 1.6484 3
13 RO 1.6484 3
14 SE 1.6484 3
15 TO 1.6484 3
16 AI 1.0989 2
17 AT 1.0989 2
18 BE 1.0989 2
19 BR 1.0989 2
20 DE 1.0989 2
21 EC 1.0989 2
22 EN 1.0989 2

Intro only:

No. Substring Frequency (in %) Frequency

1 E 12.5000 7
2 N 10.7143 6
3 O 10.7143 6
4 I 8.9286 5
5 F 7.1429 4
6 A 5.3571 3
7 C 5.3571 3
8 H 5.3571 3
9 S 5.3571 3
10 D 3.5714 2
11 L 3.5714 2
12 M 3.5714 2
13 R 3.5714 2
14 T 3.5714 2
15 B 1.7857 1
16 G 1.7857 1
17 J 1.7857 1
18 K 1.7857 1
19 P 1.7857 1
20 U 1.7857 1

Digram of intro:

No. Substring Frequency (in %) Frequency

1 IN 6.9767 3
2 EC 4.6512 2
3 HI 4.6512 2
4 ME 4.6512 2
5 OF 4.6512 2
6 OM 4.6512 2
7 TH 4.6512 2
8 AF 2.3256 1
9 AL 2.3256 1
10 AN 2.3256 1
11 BE 2.3256 1
12 CH 2.3256 1
13 CI 2.3256 1
14 CO 2.3256 1
15 DR 2.3256 1
16 EN 2.3256 1
17 ET 2.3256 1
18 FF 2.3256 1
19 HE 2.3256 1
20 IA 2.3256 1

Ending only:

No. Substring Frequency (in %) Frequency

1 D 17.6471 3
2 E 11.7647 2
3 I 11.7647 2
4 L 11.7647 2
5 R 11.7647 2
6 B 5.8824 1
7 F 5.8824 1
8 N 5.8824 1
9 O 5.8824 1
10 Q 5.8824 1
11 U 5.8824 1

Digram of ending:

No. Substring Frequency (in %) Frequency

1 RE 13.3333 2
2 BL 6.6667 1
3 DF 6.6667 1
4 ED 6.6667 1
5 EQ 6.6667 1
6 FO 6.6667 1
7 IN 6.6667 1
8 IR 6.6667 1
9 LD 6.6667 1
10 LI 6.6667 1
11 ND 6.6667 1


Now we've got a complete Frequency analysis of the message, we can test every coding process,
and over all, try to find the coding key


T
his is an example of column transposition which is different from simple substitution.
usually substitution takes place before shifting them.




For example the complete text shifted column by column, with Kifflom for key:


Edin ou rb rochuresl ookfora red truckw ith ad ent ontherig ht Fende.
Rraise yourlef tha ndan dr eci teth ewordren of kra fftravelt. Hrou ght h eda wntot
hepa s spic tu rjo inusi nsomet. Hings peci alan dbec ome oneoft hec hilds: "Take me to
to my father-father, brother-uncle. Kifflom." Wt'he re isk rant. Andboth be pra ised,
blind fo Ldrequi red elldo th Erest, bec ause we allknow.
Thereiski fflomand.


Singlegram of this text:

No. Substring Frequency (in %) Frequency
1 E 13.2911 42
2 R 8.8608 28
3 T 8.8608 28
4 O 7.9114 25
5 A 6.3291 20
6 H 6.3291 20
7 N 6.0127 19
8 I 5.6962 18
9 D 5.3797 17
10 F 4.4304 14
11 L 4.4304 14
12 S 4.1139 13
13 U 3.1646 10
14 C 2.8481 9
15 K 2.5316 8
16 B 2.2152 7
17 M 1.8987 6
18 W 1.8987 6
19 P 1.2658 4
20 G 0.9494 3
21 Y 0.6329 2
22 J 0.3165 1
23 Q 0.3165 1
24 V 0.3165 1

Digram of this text:

No. Substring Frequency (in %) Frequency

1 TH 4.1667 10
2 HE 3.3333 8
3 RE 3.3333 8
4 ER 2.5000 6
5 RA 2.5000 6
6 AN 2.0833 5
7 EC 2.0833 5
8 ED 2.0833 5
9 ND 2.0833 5
10 IN 1.6667 4
11 IS 1.6667 4
12 NT 1.6667 4
13 OM 1.6667 4
14 BE 1.2500 3
15 DR 1.2500 3
16 EN 1.2500 3
17 FF 1.2500 3
18 LD 1.2500 3
19 ME 1.2500 3
20 OT 1.2500 3
21 OU 1.2500 3
22 RO 1.2500 3
23 SE 1.2500 3
24 TO 1.2500 3

Same methode as before with the keyword kifflomkrant ( capitals don't matter):

Beca us ew eallknowt hereisk iff ftrave lth ro ugh thedawnt ot Hepas.
Spictu redinou rbr ochu re slb ecom eoneofth ec hil drenofkra. Join usi n som ethin
gspe c iala nd met otomy father. Fathe rbro theo okfo rar edtruc kwi thade: "Nton th an
da nd recite-thewor, dstakef-loman. Dtherei." Sk'ra nt and both. Therigh tf end erra,
iseyo ur Lefrunc lek ifflo mw Elldo, the rest be praised.
Blindfold required.

Check the last sentence !

Singlegram of this text:

No. Substring Frequency (in %) Frequency
1 E 13.2911 42
2 R 8.8608 28
3 T 8.8608 28
4 O 7.9114 25
5 A 6.3291 20
6 H 6.3291 20
7 N 6.0127 19
8 I 5.6962 18
9 D 5.3797 17
10 F 4.4304 14
11 L 4.4304 14
12 S 4.1139 13
13 U 3.1646 10
14 C 2.8481 9
15 K 2.5316 8
16 B 2.2152 7
17 M 1.8987 6
18 W 1.8987 6
19 P 1.2658 4
20 G 0.9494 3
21 Y 0.6329 2
22 J 0.3165 1
23 Q 0.3165 1
24 V 0.3165 1

Digram of this text:

No. Substring Frequency (in %) Frequency

1 TH 5.8333 14
2 HE 4.1667 10
3 RE 3.7500 9
4 RA 2.5000 6
5 ED 2.0833 5
6 ER 2.0833 5
7 ND 2.0833 5
8 EC 1.6667 4
9 IN 1.6667 4
10 OM 1.6667 4
11 AN 1.2500 3
12 EO 1.2500 3
13 IS 1.2500 3
14 NO 1.2500 3
15 NT 1.2500 3
16 OT 1.2500 3
17 AL 0.8333 2
18 AT 0.8333 2
19 BE 0.8333 2
20 BR 0.8333 2
21 DA 0.8333 2
22 DT 0.8333 2
23 EF 0.8333 2
24 EI 0.8333 2


Doing it with 23 is impossible but i did a simple shift encryption (aka Cesar method ).
Which is the most basic method there is simply shifting letter forward and this can be broken in a second with a computer and within minutes by humans.

Glfk rp fk pljbqefkd pmbzfxi xka ybzljb lkb lc qeb zefiaobk lc Hoxcc.
Qoxsbi qeolrde qeb axtk ql qeb mxpp mfzqroba fk lro yolzerobp. Illh clo x oba qorzh
tfqe x abkq lk qeb ofdeq cbkabo. Oxfpb vlro ibcq exka xka obzfqb qeb tloap: "Qxhb jb ql
ql jv cxqebo-cxqebo, yolqebo-rkzib. Hfccilj." Tb'ii al qeb obpq. Ybzxrpb tb xii hklt,
qebob fp Hfccilj xka qebob fp Hoxkq, xka ylqe yb moxfpba.
Yifkaclia obnrfoba.

Singlegram of this text:

No. Substring Frequency (in %) Frequency
1 B 13.2911 42
2 O 8.8608 28
3 Q 8.8608 28
4 L 7.9114 25
5 E 6.3291 20
6 X 6.3291 20
7 K 6.0127 19
8 F 5.6962 18
9 A 5.3797 17
10 C 4.4304 14
11 I 4.4304 14
12 P 4.1139 13
13 R 3.1646 10
14 Z 2.8481 9
15 H 2.5316 8
16 Y 2.2152 7
17 J 1.8987 6
18 T 1.8987 6
19 M 1.2658 4
20 D 0.9494 3
21 V 0.6329 2
22 G 0.3165 1
23 N 0.3165 1
24 S 0.3165 1

A Digram of this text:

No. Substring Frequency (in %) Frequency

1 QE 6.2500 15
2 EB 4.5833 11
3 OB 4.1667 10
4 KA 2.9167 7
5 BO 2.5000 6
6 XK 2.5000 6
7 FK 2.0833 5
8 OX 2.0833 5
9 BA 1.6667 4
10 BZ 1.6667 4
11 FP 1.6667 4
12 LJ 1.6667 4
13 RO 1.6667 4
14 BK 1.2500 3
15 CC 1.2500 3
16 IL 1.2500 3
17 JB 1.2500 3
18 LR 1.2500 3
19 OL 1.2500 3
20 PB 1.2500 3
21 QL 1.2500 3
22 YB 1.2500 3
23 AB 0.8333 2
24 BP 0.8333 2



Here is the "column transposition" with keyword kifflomkrantkraft

Itet he wo rdstakeme toifflo man dthere isk rt hec hildreno fk Rafft.
Ravelt hrought hed awna nt and both bepraise ec ial andbecome. Oneo fjo i nus insom
ethi n gspn th eri ghtfe nderra. Isell doth eres tbec aus tothep ass pictu: "Redi na re
dt ru ckwith-adento, tomyfat-herfa. Therbro." Ur'br oc hur eslo. Okforey ou rle ftha,
ndand re Ceweall kno wther ei Skoth, eru ncle ki fflomwd.
Blindfold required.

And yet again the last sentence stays the same :O

Singlegram of this text:

1 E 13.2911 42
2 R 8.8608 28
3 T 8.8608 28
4 O 7.9114 25
5 A 6.3291 20
6 H 6.3291 20
7 N 6.0127 19
8 I 5.6962 18
9 D 5.3797 17
10 F 4.4304 14
11 L 4.4304 14
12 S 4.1139 13
13 U 3.1646 10
14 C 2.8481 9
15 K 2.5316 8
16 B 2.2152 7
17 M 1.8987 6
18 W 1.8987 6
19 P 1.2658 4
20 G 0.9494 3
21 Y 0.6329 2
22 J 0.3165 1
23 Q 0.3165 1
24 V 0.3165 1

A Digram of the text:

No. Substring Frequency (in %) Frequency

1 TH 4.5833 11
2 RE 3.7500 9
3 ER 3.3333 8
4 HE 3.3333 8
5 ND 2.5000 6
6 AN 1.6667 4
7 EC 1.6667 4
8 OM 1.6667 4
9 OT 1.6667 4
10 RA 1.6667 4
11 TO 1.6667 4
12 BE 1.2500 3
13 ED 1.2500 3
14 FF 1.2500 3
15 IS 1.2500 3
16 LO 1.2500 3
17 AL 0.8333 2
18 BR 0.8333 2
19 DE 0.8333 2
20 DT 0.8333 2
21 EL 0.8333 2
22 EN 0.8333 2
23 EP 0.8333 2
24 ES 0.8333 2


Then, as a question, have we got to count the "-" in the text?
As spaces, or letters ?

In the way we did it we let the - stay the same. but we can try to make it count / encrypt it with the rest but that takes a little
more effort and will probably result in an other special character or an letter giving an unbalanced result.

What about the mystery of the last sentence in the message?
The reason it wasn't changed is because the keywords are too short.
Here are the results with the keywords for "Blindfold required." only


kifflomkrant:
Rdfolinbl udrqeeid.

kifflomkrantkraft:
Rrinelblu doefdiqd.


We can also try to substract some words,, look:

Travel through the dawn to the pass pictured in our brochures. Look for a red truck
with a dent on the right fender. Raise your left hand and recite the words: "Take me to
to my father-father, brother-uncle. Kifflom." We'll do the rest. Because we all know,
there is Kifflom and there is Krant, and both be praised.

Without kifflom:
Travel through the dawn to the pass pictured in our brochures. Look for a red truck
with a dent on the right fender. Raise your left hand and recite the words: "Take me to
to my father-father, brother-uncle." We'll do the rest. Because we all know,
there is and there is Krant, and both be praised.


When using that last text with the key kifflom inputting the text as text and not as binary data and
permutating it row by row will deliver this:

Kwitha dentont her ight fe nde rrai seyourle ft han dandrecit. Ethe wor d sta kemeu
redi n ourb ro chu reslo okfora. Redtr uctr avel thro ugh thedaw nto thepa: "Sspi ct to
to my father-father, brother-uncle." We'ls an dth erei. Skranta nd bot hbep,
raise dl dot heres tb Ecaus, ewe allk no wtherei.

Singlegram of this text:

1 E 14.4105 33
2 T 11.3537 26
3 R 10.4803 24
4 A 7.4236 17
5 H 7.4236 17
6 O 6.9869 16
7 D 5.2402 12
8 N 5.2402 12
9 S 4.3668 10
10 I 3.9301 9
11 L 3.4934 8
12 U 3.4934 8
13 C 2.6201 6
14 W 2.6201 6
15 B 2.1834 5
16 F 2.1834 5
17 K 2.1834 5
18 P 1.3100 3
19 G 0.8734 2
20 M 0.8734 2
21 Y 0.8734 2
22 V 0.4367 1

Digram :

No. Substring Frequency (in %) Frequency

1 TH 5.8824 10
2 HE 5.2941 9
3 ER 4.1176 7
4 RE 4.1176 7
5 AN 2.3529 4
6 NT 2.3529 4
7 RA 2.3529 4
8 TO 2.3529 4
9 ED 1.7647 3
10 ND 1.7647 3
11 OT 1.7647 3
12 RO 1.7647 3
13 AI 1.1765 2
14 AT 1.1765 2
15 CT 1.1765 2
16 DA 1.1765 2
17 DE 1.1765 2
18 DT 1.1765 2
19 EC 1.1765 2
20 EI 1.1765 2
21 EP 1.1765 2
22 ES 1.1765 2


With the key "krantom" without quotation marks of course:

Edin ou rb rochuresl ookfora red truckw ith ad ent onthjoin us Insom.
Ething special and beco me one ofth echildth er eis krantandb. Othb epr a ise dblin
dfol d requ ir ede right fender. Raise your left hand and recite the worde: "Lldo th er
es tb ecause-weallk, nowther-eiski. Ffloman." Dr'en of kra fftr. Avelthr ou ght heda,
wntot he Passpic tur stake me Totom, yfa ther fa therbro.
Theruncle kifflomw.



Singlegram:

No. Substring Frequency (in %) Frequency

1 E 13.2911 42
2 R 8.8608 28
3 T 8.8608 28
4 O 7.9114 25
5 A 6.3291 20
6 H 6.3291 20
7 N 6.0127 19
8 I 5.6962 18
9 D 5.3797 17
10 F 4.4304 14
11 L 4.4304 14
12 S 4.1139 13
13 U 3.1646 10
14 C 2.8481 9
15 K 2.5316 8
16 B 2.2152 7
17 M 1.8987 6
18 W 1.8987 6
19 P 1.2658 4
20 G 0.9494 3
21 Y 0.6329 2
22 J 0.3165 1
23 Q 0.3165 1
24 V 0.3165 1



Digram:

No. Substring Frequency (in %) Frequency

1 TH 5.4167 13
2 ER 2.9167 7
3 HE 2.9167 7
4 AN 2.5000 6
5 EC 2.0833 5
6 IN 2.0833 5
7 ND 2.0833 5
8 ED 1.6667 4
9 IS 1.6667 4
10 NT 1.6667 4
11 OM 1.6667 4
12 RA 1.6667 4
13 RE 1.6667 4
14 DE 1.2500 3
15 EN 1.2500 3
16 FF 1.2500 3
17 FT 1.2500 3
18 OT 1.2500 3
19 OU 1.2500 3
20 SE 1.2500 3
21 TO 1.2500 3
22 UR 1.2500 3
23 AL 0.8333 2
24 CH 0.8333 2





It's not impossible for a sentence that long to be encrypted but to me it seems very counterproductive to encrypt it in a way that it
reveals an entirely different message it's not impossible but you have to develop an entire new way to do that since cryptography
is the purpose of making it unreadable.

Now, let's try some standard old algorithms since they wouldn't go as deep as doing it with a modern
cipher and then reinterpreting it different in such a way it's still readable.


1: vigenére analysis yielded nothing .

2: Ciphertext-only analysis according to Schroedel against Vigenère cipher.
Time needed to perform analysis:43 seconds
Length of analyzed ciphertext: 316 characters
Keyword language(s): English
Ciphertext language: English
not successful


3: automated substitution analysis based on digrams yielded this result:
Qsro cm ro mshealrou mwepriv ion yepshe soe sd ale plrvnteo sd Ftidd.

Atibev altscul ale nigo as ale wimm wrpacten ro sct ytsplctem. Vssf dst i ten atcpf

gral i neoa so ale trula deonet. Tirme ksct veda lion ion teprae ale gstnm: "Aife he as

as hk dialet-dialet, ytsalet-copve. Frddvsh." Ge'vv ns ale tema. Yepicme ge ivv fosg,

alete rm Frddvsh ion alete rm Ftioa, ion ysal ye wtirmen.

Yvrondsvn texcrten.

4: automated substitution analysis based on frequency got this result:
join up in pomething ppecial and become one of the children of kraff.
Travel through the dawn to the papp pictured in our brochurep. Look for a red truck
with a dent on the right fender. Raipe your left hand and recite the wordp: "Take me to
to my father-father, brother-uncle. kifflom." We'll do the rept. becaupe we all know,
there ip kifflom and there ip krant, and both be praiped.
blindfold required.

5: hill analysis yielded nothing.

6: solitaire analysis yielded nothing.


We also tried some modern methods described:

modern encryption methods we tried but each takes thousands of years to decrypt if we try to brute force it.
for those curious we tried:
des in ecb and cbc mode (both the normal and triple variant)
idea, rc4 and even the unlikely RSA lattice attack with small secret key analysis based on Bloemer/May method




Conclusion :
If there is an hidden message, Rockstar did a great job, but a job we can break, with the good key and method...
Any idea is welcome, of course, plus you all can try some homework, by for example, analysing this, and give
your conclusions, in our board, The Epsilon Project


A big, big thanks to Mad_Mike
, for this awesome work.
Perhaps the key for the truth, but at least, a really interesting lead to Hunt.




 T  A  K  E  M  E  T  O  T O  M  Y  F  A  T  H  E  R  
 F  A  T  H  E  R  B  R  O T
 H  E  R  U  N  C  L  E    
 K  I  F  F  L  O  M                          
                                       
 T  A  K  E  M  E  T  O  T  O  M  Y  F  A  T  H  E  R    
   F  A  T  H  E  R  B  R  O  T  H  E  R    U  N  C    
 L  E  K  I  F  F  L  O  M                      
                                       
 T  A  K  E  M  E  T  O  T  O  M  Y                
 F  A  T  H  E  R  F  A  T  H  E R
   

       
 B  R  O  T  H  E  R  U  N  C  L  E                
 K  I  F  F  L  O  M                          
                                       
 T  A  K  E  M  E  T  O  T  O  M  Y                
 F  A  T  H  E  R    F  A  T  H  E                
 R  B  R  O  T  H  E R
   U  N  C                
L
E  K  I  F  F  L  O  M                      
                                       
                                       
                                       



 T  A  K  E  M  E  T  O  T  O    T  A  K  E  M  E  T  O  
 M  Y  F  A  T  H  E  R  F  A    T  O  M  Y  F  A  T  H  
 T  H  E  R  B  R  O  T  H E
   E  R  F  A  T  H  E  R  
 R  U  N  C  L  E  K  I  F  F    B  R  O  T  H  E  R  U  
 L  O  M                  N  C  L  E  K  I  F  F  
                       L  O  M            
 T  A  K  E  M E
 T  O  T  O                    
 M  Y  F  A  T  H  E  R    F    T  A  K  E  M  E  T  O  
 A  T  H  E  R  B  R  O  T  H    T  O  M  Y  F  A  T  H  
E
 R    U  N  C  L  E  K  I    E  R   F
A
T
H
E
 
 F  F  L  O  M              R  B  R  O  T  H  E  R  
                         U  N  C  L  E  K  I  
                       F  F  L  O  M        
                                       
                                       
                                       
                                       
                                       
                                       
                                       


 T  A  K  E  M  E  T    T  A  K  E  M  E  T          
 O  T  O M
Y  F  A    O  T  O  M  Y  F  A          
 T  H  E  R  F  A  T    T  H  E  R
F
A
         
 H  E  R  B  R  O  T   T
H
E
R

B
R
         
 H  E  R  U  N  C  L   O
T
H
E
R

U
         
 E  K  I  F  F  L  O   N
C
L
E
   K  I          
 M                F  F  L  O  M              
                                       
T
 A  K  E  M  E      T  A  K  E  M  E            
 T  O  T  O  M  Y      T  O  T  O  M  Y            
 F  A  T  H  E  R      F  A  T  H  E  R            
 F  A  T H
 E  R        F  A  T  H  E            
 B  R  O  T  H  E      R  B  R  O  T  H            
 R  U  N  C  L  E      E  R    U  N  C            
 K  I  F  F  L  O      L  E  K  I F
 F            
 M                L  O  M                  
                                       
                                       
                                       
                                       


 T  A  K  E  M    T  A  K  E  M    T  A  K  E        
 E  T  O  T  O    E  T  O  T  O    M  E  T  O        
 M  Y  F  A  T    M  Y  F  A  T    T  O  M  Y        
 H  E  R  F  A    H  E  R    F    F  A  T  H        
 T  H  E  R  B    A  T  H  E  R    E  R  F  A        
 R  O  T  H  E    B  R  O  T  H    T  H  E  R        
 R  U  N  C  L    E  R    U  N    B  R  O  T        
 E  K  I  F  F    C  L  E  K  I    H  E  R  U        
 L  O  M        F  F  L  O  M    N  C  L  E        
                         K  I  F  F        




                 L  O  M          




                               




                               




                               




                               




                               




                               




                               




                               




                               

 T  A  K  E    T  A  K    T  A  K                
 M  E  T  O    M  E  T    M  E  T  

         
 T  O  M  Y    O  T  O    O  T  O    
         
 F  A  T  H    M  Y  F    M  Y  F                
 E  R    F    A  T  H    A  T  H                
 A  T  H  E    E  R  F    E  R                  
 R  B  R  O    A  T  H    F  A  T  

         
 T  H  E  R    E  R  B    H  E  R                
   U  N  C    R  O  T    B  R  O    
         
 L  E  K  I    H  E  R    T  H  E    
         
 F  F  L  O    U  N  C    R    U                
 M          L  E  K    N  C  L    
         
           I  F  F    E  K  I    
         
           L  O  M    F  F  L                
                   O  M    

         
                           
         
                                       
                           
         
                                       
                                       

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