- Enigma Python Github
- Enigma Ball Python
- Enigma Python Script
- Enigma Code Python
- Python Enigma Cracker
- Enigma Python Code
This enigma-simulator project is an educational tool which simulates the workings of an Enigma machine, the Germans' main military encryption tool during World War II. The software allows users to encrypt and decrypt messages. Additionally, the simulation includes a step-by-step guide that teaches users how to recover Enigma keys. Implementation of a simulated Enigma Machine in python. Used in IB Math Exploration. User is expected to run Enigma/Enigma.py. The Bombe directory contains a simple and a bit more complex implementation of the Bombe machine.
In May 2018 we visited the The Government Code and Cypher School at Bletchley Park in the UK. It left a lasting impression on us: How the work done there by the British, and the earlier work by the Polish, was instrumental in bringing about an early end to World War II, saving countless lives. Central to their effort was decoding messages from the infamous German Enigma machine.
Bletchley Park Mansion and the Enigma Machine
We always wanted to commemorate this experience by writing something about it for school students here. However, we are not historians and there are already so many on-line resources, including some very good Enigma machine software simulators, so we wondered how we could contribute in some other way? In the end we decided to start a project of our own: To build a working Enigma machine toy for kids.
We started by researching how the Enigma machine worked. Our first effort was to build a software simulator of the Enigma machine, written in Python 3. However, this was just a proof of concept, to show that we had correctly understood the design of the real Enigma machine. After testing this program against authentic, historical, messages, from different models of the machine, we progressed to the next stage of building a battery-operated, toy Enigma machine.
Our python 3 Enigma Machine simulator program, is here and the output is here. Please note that this program is still under development and testing. So far it has been verified to work correctly on 9/11, 3-rotor messages and 3/3, 4-rotor messages. We note that authentic, historical messages, complete with the full Enigma machine settings and decrypted message keys are somewhat hard to come by.. There is a scene in the movie 'The imitation game' where the BP team are ordered to 'burn everything'. So, maybe that's why? We don't know.
Here is brief recap of how the Enigma machine works. See the above references for more details:
- When one of 26 letter keys (A-Z) is pressed on the keyboard, it is scrambled progressively by:
- The plugboard wiring;
- 3 or 4 rotors, each with specific wiring, in the forward, or right-to-left, direction;
- the static reflector wiring;
- the same 3 or 4 rotors, but in the reverse, or left-to-right, direction;
- and finally, the plugboard wiring again.
- Each stage is a simple substitution cipher: The rotors have 26 substitutions, the plugboard has 13 pairs of substitutions
- The message is further scrambled using the following methods:
- Inserting cables into the plugboard (usually 10 out of a possible 13). Each cable creates a symmetrical substitution of keys and lamps.
- Setting the rotor starting positions
- Offsetting the rotor positions with a ring
- When a button is pressed, but before any output is displayed:
- If any rotor is at one or two predetermined notch positions on its ring, the rotor to its left is advanced one step
- The right hand rotor is unconditionally advanced one step
- The output is then illuminated on one of 26 letter lamps (A-Z)
- The output changes each time a key is pressed, even if it is the same key. However, the output cannot be the same as the keyed letter
- There is no space. Uncommon letters, like X, may be used instead.
- The enigma machine can be used symmetrically, for either encryption or decryption, with exactly the same starting settings
Copyright (c) 2020, Julie VK3FOWL and Joe VK3YSP
For the School Amateur Radio Club Network https://www.sarcnet.org/
This is free software released into the public domain under the GNU General Public License
Configuration:
Rotor Name: I
Rotor Reverse Wiring: UWYGADFPVZBECKMTHXSLRINQOJ
Rotor Forward Wiring: AJDKSIRUXBLHWTMCQGZNPYFVOE
Rotor Notch Positions: E
Rotor Name: III
Rotor Reverse Wiring: TAGBPCSDQEUFVNZHYIXJWLRKOM
Rotor Forward Wiring: ESOVPZJAYQUIRHXLNFTGKDCMWB
Rotor Notch Positions: J
Rotor Name: V
Rotor Reverse Wiring: QCYLXWENFTZOSMVJUDKGIARPHB
Rotor Forward Wiring: JPGVOUMFYQBENHZRDKASXLICTW
Rotor Notch Positions: ZM
Rotor Name: VII
Rotor Reverse Wiring: QMGYVPEDRCWTIANUXFKZOSLHJB
Rotor Forward Wiring: FKQHTLXOCBJSPDZRAMEWNIUYGV
Rotor Notch Positions: ZM
Rotor Name: BETA
Rotor Reverse Wiring: RLFOBVUXHDSANGYKMPZQWEJICT
Rotor Forward Wiring: FSOKANUERHMBTIYCWLQPZXVGJD
Rotor Notch Positions: ZM
Reflector Name: A
Reflector Wiring: YRUHQSLDPXNGOKMIEBFZCWVJAT
![Enigma Python Enigma Python](https://miro.medium.com/max/1200/1*jKqW7a6yTLWAFbqAL71Pxw.png)
Reflector Name: C
Reflector Wiring: ENKQAUYWJICOPBLMDXZVFTHRGS
Reflector Name: C THIN
Rotor order: ['II', 'IV', 'V']
Message key: BLA
Plug pairs: AV BS CG DL FU HZ IN KM OW RX
NOWAX KURTI NOWAX NORDW ESTLX
ASZER IQTUN GXDUB ROWKI XDUBR
UMXEI NSAQT DREIN ULLXU HRANG
Ciphertext: EDPUD NRGYS ZRCXN UYTPO MRMBO
EQMIK UBPMM YLKLT TDEIS MDICA
LRNBZ SZWNR FXWFY SSXJZ VIJHI
TLPIF SVKDA SCTAC DPBOP VHJK
Decoding: VERIFIED
Message: Operation Barbarossa, 1941 Pt 2
Ring positions: [2, 21, 12]
Reflector: B
Plaintext: DREIG EHTLA NGSAM ABERS IQERV
QSXUH RXROE MXEIN SXINF RGTXD
NFANG XEINS SEQSX KMXKM XOSTW
Ciphertext: SFBWD NJUSE GQOBH KRTAR EEZMW
VVGBI MHUSZ YDAJQ IROAX SSSNR
QDGRE RVBIL EKXYQ IRGIR QNRDN
Encoding: VERIFIED
Message: Scharnhorst (Konteradmiral Erich Bey), 1943
Ring positions: [1, 8, 13]
Reflector: B
Plaintext: YKAEN ZAPMS CHZBF OCUVM RMDPY
BOTGO XGRET DWTJI QHLMX VJWKZ
Ciphertext: STEUE REJTA NAFJO RDJAN STAND
OFAHR TZWON ULSMX XSCHA RNHOR
Encoding: NOT VERIFIED
Enigma Python Github
Rotor order: ['II', 'I', 'III']
Message key: ABL
Plug pairs: AM FI NV PS TU WZ
EBEOB AQTET XANFA NGSUE DAUSG
TWAER TSNEU STADT
VYMIG MMNMF DXTGN VHVRM MEVOU
RDISI KBGPM YVXUZ
Decoding: VERIFIED
Message: 215 AAA FRA ABIRUXKP
Ring positions: AAA
Reflector: B
Plaintext: ANBUL MEGRA ZGOES TINGS TRENG
Ciphertext: PCDAO NONEB CJBOG LYMEE YGSHR
Encoding: VERIFIED
Message: PAGE_40_AFDFX (Norrköping Enigma message)
Ring positions: KSH
Reflector: B
Plaintext: WAETI GKEIT SBERI QTVOM XSEQS
LFLXK DOXEI NSXXP REIXS TRIQX
Ciphertext: DSBDB DCOSG CYAMD SITWW ZUSDL
OHKGO WRCDK BNYZE LVKWY MWOPN
Encoding: VERIFIED
Message: PAGE_40_AYDJM (Norrköping Enigma message)
Ring positions: KSH
Reflector: B
Plaintext: TAETI GKEIT SBERI QTVOM XSEQS
GEXZW OXSXI TEXZW OXLGX KDOXR
SEITE XDREI XLGXK DOXRO EMXDR
ROEMX DREI
HLICK JOHFJ FVNAV AUHAW SXEIL
CDDAV BXBQO PTYRN ZTPUP ABQBO
OGQHK TTOPH ZROKU MSSJL ONINR
Encoding: VERIFIED
Message: PAGE_40_PYCMW (Norrköping Enigma message)
Ring positions: XLG
Reflector: B
Plaintext: TAETI GSKEI TSBER IQTFU ERDEN
ANLAG EZWOX SEITE NZAHL ZWOXL
ENFXL GXKDO XROEM ZWOX
LFHFM NFYMW EGDEC HKKGX HLTRQ
XUSJX DACDT BBWUJ IFEGI YZZJX
Encoding: NOT VERIFIED
Message: PAGE_40_ZBAQW (Norrköping Enigma message)
Ring positions: XLG
Reflector: B
Plaintext: TAETI GKEIT SBIRI CHTVO MXSEQ
NOMME NXNUL LXMEF OERDE RTXLE
OXROE MXAQT X
ISIGZ DZMCH ECVVZ GIZOY UJIDT
QEYYT WITHH BYXAW AYXRT BUOOX
Encoding: VERIFIED
Message: PAGE_47_RTQSX (Norrköping Enigma message)
Ring positions: PVG
Reflector: B
Plaintext: KOMMA HIERZ UWIRD DERVE RKGHR
ETUND BXIAB GABEE IFESF UERDI
WIQTV GENFU KKSPR UQESU SWPUN
GSLUE CKEX
RIFLD WNMOQ IBQZG JGIHR PTIWP
Enigma Ball Python
IVNQA OYVFC XKJNO JQVPU MUZHF
VBOXM UAKRE MODLB XHYGT XLUNF
Encoding: VERIFIED
Enigma Python Script
Message: PAGE_47_KRNV (Swedish Enigma M3 intercept)
Ring positions: AGW
Reflector: B
Plaintext: SEENA CHRIC HTLEU CHTSC HIFFE
RDREI EINSL IEGTW IEDER AUFST
Ciphertext: IWNOX NFTRJ NPMRA WPZNK QECKK
CUDIJ DLGQQ PRYUR GKGTF KRQEP
Encoding: VERIFIED
Rotor order: ['BETA', 'II', 'IV', 'I']
Message key: MCSF
Plug pairs: AT CL DH EP FG IO JN KQ MU RX
RSFUE NFFUE NFGRA DNICH TSGEF
SQUAD RATXS TANRO RTMAR QUANT
SSOOO VIERY SEEDR EMYEI NSNUL
BSTEI GTYNB BELSI CHTEI NSSMT
Ciphertext: TMKFN WZXFF IIYXU TIHWM DHXIF
XHYRP ACZUG RREMV PANWX GTKTH
HHPVP XKMBH OKCCP DPEVX VVHOZ
JDJKJ PKCSD SUZTQ CXJDV LPAMG
Decoding: VERIFIED
Message: M4 Looks Message
Ring positions: AAAV
Reflector: B THIN
Plaintext: VONVO NJLOO KSJHF FTTTE INSEI
XXBEI ANGRI FFUNT ERWAS SERGE
ERSTA NDNUL ACHTD REINU LUHRM
SDREI YZWOZ WONUL GRADY ACHTS
ELLTY NNNNN NOOOV IERYS ICHTE
Ciphertext: NCZWV USXPN YMINH ZXMQX SFWXW
SEINJ USBLK IOSXC KUBHM LLXCS
AHXRH KKFVD REWEZ LXOBA FGYUJ
HABCJ WMAKL FKLMY FVNRI ZRVVR
RHOWO PBEKV WMUQF MPWPA RMFHA
Encoding: VERIFIED
Message: M4 SOLUTION OF THE LAST OF THE “HMS HURRICANE” INTERCEPTS
Ring positions: ZZTG
Reflector: B THIN
Plaintext: BOOTK LARXB EIJSC HNOOR BETWA
PROVI ANTBI SZWON ULXDE ZXBEN
RXSTE HEMAR QUBRU NOBRU NFZWO
TWWWF UNFYE INSFU NFMBS TEIGE
Ciphertext: HCEYZ TCSOP UPPZD ICQRD LWXXF
GLYXW TMJPQ UEFSZ BOTVR LALZX
JMKLD UYUPF UQDOW VHAHC DWAUA
GRMBP XXZCA NKMON FHXPC KHJZB
Encoding: VERIFIED
We decided to design and build a miniature, battery operated, toy Enigma machine for kids, with the following specifications:
- Authentic Enigma encryption and decryption
- Slim, hand-held device
- Battery operated
- On-Off switch
- Read-in-the-dark display for both settings and messages
- Non-volatile storage of settings
- Single press-button rotary-encoder type control
- Built-in Morse code beeper
We had a previous design of a similar Arduino product, which we called My1stMicro, that we used as a starting point. The device already had an Arduino microcontroller, an oLED display and a single press-button rotary-encoder type control on a small PCB. With a redesign for a suitable case and the addition of a beeper, it would do the job. Of course the Python 3 code we developed for the simulator above would have to be converted into C and a Morse code generator added. The design of an easy to use, Graphical User Interface for the tiny 0.6-inch oLED display would also be quite a challenge.
My1stMicro Printed Circuit Board
Back to contentAn ~Enigma~ machine, famed for its inner complexity.
Recurrent Neural Networks (RNNs) are Turing-complete. In other words, they can approximate any function. As a tip of the hat to Alan Turing, let’s see if we can use them to learn the Enigma cipher.
A Brief History of Cryptanalysis
According to Wikipedia, “Cryptanalysis is the study of analyzing information systems in order to study their hidden aspects.”
By hand. Long ago, cryptanalysis was done by hand. People would count the frequencies of symbols, compare encrypted text to decrypted text, and try to find patterns. It was a meticulous process which required days and weeks of concentration. Starting with World War II, the heavy lifting was transferred to machines and humans experts started spending their time on problems in pure mathematics which enabled them to crack all but the toughest ciphers. Mac videoripper pro 1 0 7 download free. But even today, cryptanalysts spend much of their time meticulously dissecting the structure of the cipher they’re trying to crack. Does this need to be the case?
The frequency table is a classic codebreaking tool
Black boxes. The Black Box theory of cryptograpy states “If the output of an algorithm when interacting with the [encrytion] protocol matches that of a simulator given some inputs, it ‘need not know’ anything more than those inputs” (Wikipedia). If that’s the case, we should be able to mimic complicated ciphers such as the Enigma without knowing anything about how they work. All we need is a way to approximate the function (f_{Enigma}) which maps from plaintext to ciphertext
[mathbf{ciphertext} = f_{Enigma}(mathbf{key}, mathbf{plaintext})]Can neural nets help? In this post, I’ll do this with an RNN parameterized by weights (theta) which we’ll train using gradient descent. In other words, we’ll try
[begin{align} L_t[i,j] &= f_{Enigma}(mathbf{key}, mathbf{plaintext}) &approx f_{RNN}(theta, mathbf{key}, mathbf{plaintext})end{align}]Deep Learning for Cryptanalysis
Framing the problem. Let’s consider the general problem of decryption where there is a 1:1 mapping between the plaintext and ciphertext. If you think of the plaintext as English and the ciphertext as a strange foriegn language, the training objective resembles that of machine translation. Appgraphics 1 1 – app icon and screenshot generator. Given a string of letters in English - let’s use “You know nothing Jon Snow” as an example - we should learn to scramble them according to the rules of the cipher.
Choose a model. Framed as a 1:1 sequence-to-sequence task, we can see that an RNN (we’ll use a Long Short Term Memory (LSTM) cell) might perform well. These models are capable of capturing complex sequential patterns where events that happened many time steps in the past can determine the next symbol.
Solve something simpler. Before tackling a really tough problem like the Enigma, it’s a good idea to solve something simpler. One of my favorite ciphers is the Vigenere cipher, which shifts the plaintext according to the letters in a keyword (see gif below). For a more in-depth description, check out the Vigenere Wikipedia page.
Using the Vigenere cipher to encrypt plaintext 'CALCUL' with keyword 'MATHS' (repeated).
Results. The Vigenere cipher was easy. A mere 100,000 steps of gradient descent produced a model which learned the decryption function with 99% accuracy.
A sample output from the model I trained on the Vigenere cipher.
You can find the code on my GitHub.
Learning the Enigma
The Enigma. Now we’re ready for something a lot more complex: the Nazi Enigma. Its innards consisted of three rotating alphabet wheels, several switchboards, and ten cables. All told, the machine had 150,738,274,900,000 possible configurations!
How the Enigma works. Note that the three wheels can rotate as the decoding process unfolds
Background. Breaking the Enigma was an incredible feat - it even inspired the 2014 film The Imitation Game starring Benedict Cumberbatch as Alan Turing. Turing was one of the most important figures in the project. He also introduced the notion of Turing-completeness. In an ironic twist, we’ll be using a Turing-complete algorithm (the LSTM) to learn the Enigma.
We’ll train the model on only one permutation of switchboards, cables, and wheels. The keyword, then, is three letters which tell the model the initial positions of the wheels.
Enigma Code Python
Basic training objective where 'EKW' is the keyword. The keyword defines the initial positions of the three alphabet wheels
Making it happen. I synthesized training data on-the-fly using the crypto-enigma Python API and checked my work on a web-based Enigma emulator. I used each training example only once to avoid the possibility of overfitting.
The model needed to be very large to capture all the Enigma’s transformations. I had success with a single-celled LSTM model with 3000 hidden units. Training involved about a million steps of batched gradient descent: after a few days on a k40 GPU, I was getting 96-97% accuracy!
![Enigma Python Enigma Python](https://www.101computing.net/wp/wp-content/uploads/enigma-paper.png)
A sample output from the model I trained on the Enigma cipher.
You can find the code on my GitHub.
Python Enigma Cracker
The Holy Grail: RSA
Learning the Enigma is interesting, but these days it has no practical use. Modern encryption uses public-key factoring algorithms such as RSA. RSA is a different beast from the Enigma, but in theory we could also learn it with deep learning. In practice, this is difficult because RSA uses modulus and multiplication of large integers. These operations are difficult to approximate with RNNs. We need further algorithmic advances in deep learning like the Neural GPU or the Differential Neural Computer to make this problem feasible.
Public-key encryption. In theory, we could learn the RSA with deep learning but it presents many practical difficulties
Implications
Cryptanalysis. In this post I’ve shown that it is possible to use deep learning to learn several polyalphabetic ciphers including the Enigma. This approach is interesting because it’s very general: given any “blackbox” cipher, we can learn the function that maps the ciphertext to the plaintext. There are countless programs that can analyze only one type or class of cypher, but this is the first instance(^{*}) of a cipher-agnostic cryptanalysis program powered by deep learning.
AI. In the past several years, Deep Reinforcement Learning has enabled an impressive series of breakthroughs in the field of Artificial Intelligence (AI). Many believe that these breakthroughs will enable machines to perform complex tasks such as driving cars, understanding text, and even reasoning over memory. This project suggests that AIs built from neural networks could also become effective code breakers.
The original Enigma cracker (a Bombe machine). Crypto Museum
Enigma Python Code
(^{*})based on an Arxiv search and Google Scholar results