Anyone know if MD5, Whirlpool, SHA[n], etc., have any "special" input that might get a hexdigest output to align into:
All numeric characters
All alpha characters
All of the same character/pattern repeated consistently or entirely
Example in python:
>>> from hashlib import sha1
>>> hash = sha1('magic_word').hexdigest()
>>> hash
4040404040404040404040404040404040404040
>>> hash = sha1('^3&#b d *#"').hexdigest()
aedefeebadcdccebefadcedddcbeadaedcbdeadc
Is this even possible? My knowledge of hashing functions is limited to the scope of applying them in databases for storing passwords, which is essentially none.
But sometimes I wonder, when testing for collisions, that these sorts of cases might arise...
A hash function models a random oracle: for each input, if it was not yet queried before, we throw some dice to find an output, then note it to some book. If an input is queried again, simply give back this old value.
By throwing a 16-sided dice 40 times (for each input), we get enough output for an SHA-1 like oracle. (For MD5, we only need 32 times.)
So, we can calculate the probability of "40 times only letters" as (6/16)^40 ≈ 9.15·10^-18, "40 times only digits" has probability (10/16)^40 ≈ 6.8·10^-9.
As "number of tries needed until the first success" is geometrically distributed, we need 1/p tries in average, i.e. around 10^17 tries for "only letters", and 1.5 ·10^8 tries for "only digits".
(Now, SHA-1 is not a real random oracle, but there is no weakness known which would say that SHA-1 would have better or worse probabilities for one of these. And for now, brute-force really seems to be the best way to do this.)
I'm sure with the right input, those sorts of outputs are possible. Why does it matter? Just curious?
Yes, it is possible. Given the right input, any desired bit pattern can be output. It might take a few million years to find the right input though.
For a reasonably wide target, like all hex 0-9 or all hex a-f it should be relatively easy. Calculating the proportion of acceptable outputs, in all possible outputs will help you get an estimate of the running time. Brute force or random searching will eventually find something that hits the target. For a broken hash, like MD4, you might be able to shave something off the expected time.
Related
Is it possible to write a code that can crack the sha256 hash when you know the form of password? For example the password form is *-********** which is 12-13 characters long and:
The first char is one number from 1 to 25
Second one is hyphen
In each char from the third one to the end, you can put a...z, A...Z and 0...9
After guessing each pass, code converts the pass to sha256 and see whether the result hash is equal to our hash or not and then print the correct pass.
I know all possible numbers is a big number (26+26+10)^10 but I want to know that:
Is it possible to write such code?
If yes, is it possible to run whole code in less than one day (because I think it takes a lot of time to complete the whole code)?
Since I can't ask you to write a code for me, how and where can I ask for this code?
You cannot "crack" a SHA256 hash no matter how much information you know about the plaintext (assuming by crack you mean derive the plaintext from the hash). Even if you knew the password you could not determine any procedure for reversing the hash. In technical terms, there is no known way to perform a preimage attack on a SHA256 hash.
That means you have to resort to guessing or brute forcing the password:
You have a prefix, which can be any value in [1-25]- and 10 additional characters in [a-zA-Z0-9]. That means the total number of possible passwords is: 25 * 62^10 or 20,982,484,146,708,505,600.
If you were able to compute and check a billion passwords per second it would take you 20,982,484,146 seconds to generate every possible hash. If you start now you'll be finished in about 665 years.
If you are able to leverage some more computing power and generate a trillion hashes per second it would only take a bit more than half a year. The good news is that computing hashes can be done in parallel, so it is easy to utilize multiple machines. The bad news is that kind of computing power isn't going to be cheap.
To answer your questions:
Is it possible to write such code? It is possible to write a program that will iterate over the entire range of possible passwords and check it against the hash(es) you want to determine the plaintext for.
If yes, is it possible to run whole code in less than one day. Yes, if you can compute and check around 10^15 hashes per second.
How and where can I ask for this code? This is the least of your problems.
Fortunately, since bitcoin uses sha256, it is pretty easy to find rough numbers on the amount of computing power it takes to generate the number of hashes you need.
If the numbers in this article are correct a Raspberry Pi can generate 2*10^5 hashes per second. I believe the newer Raspberry Pis are more powerful than that so I'm going to double that to 4*10^5. You need to generate about 10^15 hashes per second to be done in less than a day.
You're going to need 250,000,000 Raspberry Pis.
For example commit list on GitHub shows only first 10, or this line from tornadoweb which uses only 5
return static_url_prefix + path + "?v=" + hashes[abs_path][:5]
Are only the first 5 chars enough to make sure that 2 different hashes for 2 different files won't collide?
LE: The example above from tornadoweb uses md5 hash for generating a query sting for static file caching.
In general, No.
In fact, even if a full MD5 hash were given, it wouldn't be enough to prevent malicious users from generating collisions---MD5 is broken. Even with a better hash function, five characters is not enough.
But sometimes you can get away with it.
I'm not sure exactly what the context of the specific example you provided is. However, to answer your more general question, if there aren't bad guys actively trying to cause collisions, than using part of the hash is probably okay. In particular, given 5 hex characters (20 bits), you won't expect collisions before around 2^(20/2) = 2^10 ~ one thousand values are hashed. This is a consequence of the the Birthday paradox.
The previous paragraph assumes the hash function is essentially random. This is not an assumption anyone trying to make a cryptographically secure system should make. But as long as no one is intentionally trying to create collisions, it's a reasonable heuristic.
I have read that it has something to do with time, also you get from including time.h, so I assumed that much, but how does it work exactly? Also, does it have any tendencies towards odd or even numbers or something like that? And finally is there something with better distribution in the C standard library or the Foundation framework?
Briefly:
You use time.h to get a seed, which is an initial random number. C then does a bunch of operations on this number to get the next random number, then operations on that one to get the next, then... you get the picture.
rand() is able to touch on every possible integer. It will not prefer even or odd numbers regardless of the input seed, happily. Still, it has limits - it repeats itself relatively quickly, and in almost every implementation only gives numbers up to 32767.
C does not have another built-in random number generator. If you need a real tough one, there are many packages available online, but the Mersenne Twister algorithm is probably the most popular pick.
Now, if you are interested on the reasons why the above is true, here are the gory details on how rand() works:
rand() is what's called a "linear congruential generator." This means that it employs an equation of the form:
xn+1 = (*a****xn + ***b*) mod m
where xn is the nth random number, and a and b are some predetermined integers. The arithmetic is performed modulo m, with m usually 232 depending on the machine, so that only the lowest 32 bits are kept in the calculation of xn+1.
In English, then, the idea is this: To get the next random number, multiply the last random number by something, add a number to it, and then take the last few digits.
A few limitations are quickly apparent:
First, you need a starting random number. This is the "seed" of your random number generator, and this is where you've heard of time.h being used. Since we want a really random number, it is common practice to ask the system what time it is (in integer form) and use this as the first "random number." Also, this explains why using the same seed twice will always give exactly the same sequence of random numbers. This sounds bad, but is actually useful, since debugging is a lot easier when you control the inputs to your program
Second, a and b have to be chosen very, very carefully or you'll get some disastrous results. Fortunately, the equation for a linear congruential generator is simple enough that the math has been worked out in some detail. It turns out that choosing an a which satisfies *a***mod8 = 5 together with ***b* = 1 will insure that all m integers are equally likely, independent of choice of seed. You also want a value of a that is really big, so that every time you multiply it by xn you trigger a the modulo and chop off a lot of digits, or else many numbers in a row will just be multiples of each other. As a result, two common values of a (for example) are 1566083941 and 1812433253 according to Knuth. The GNU C library happens to use a=1103515245 and b=12345. A list of values for lots of implementations is available at the wikipedia page for LCGs.
Third, the linear congruential generator will actually repeat itself because of that modulo. This gets to be some pretty heady math, but the result of it all is happily very simple: The sequence will repeat itself after m numbers of have been generated. In most cases, this means that your random number generator will repeat every 232 cycles. That sounds like a lot, but it really isn't for many applications. If you are doing serious numerical work with Monte Carlo simulations, this number is hopelessly inadequate.
A fourth much less obvious problem is that the numbers are actually not really random. They have a funny sort of correlation. If you take three consecutive integers, (x, y, z), from an LCG with some value of a and m, those three points will always fall on the lattice of points generated by all linear combinations of the three points (1, a, a2), (0, m, 0), (0, 0, m). This is known as Marsaglia's Theorem, and if you don't understand it, that's okay. All it means is this: Triplets of random numbers from an LCG will show correlations at some deep, deep level. Usually it's too deep for you or I to notice, but its there. It's possible to even reconstruct the first number in a "random" sequence of three numbers if you are given the second and third! This is not good for cryptography at all.
The good part is that LCGs like rand() are very, very low footprint. It typically requires only 32 bits to retain state, which is really nice. It's also very fast, requiring very few operations. These make it good for noncritical embedded systems, video games, casual applications, stuff like that.
PRNGs are a fascinating topic. Wikipedia is always a good place to go if you are hungry to learn more on the history or the various implementations that are around today.
rand returns numbers generated by a pseudo-random number generator (PRNG). The sequence of numbers it returns is deterministic, based on the value with which the PRNG was initialized (by calling srand).
The numbers should be distributed such that they appear somewhat random, so, for example, odd and even numbers should be returned at roughly the same frequency. The actual implementation of the random number generator is left unspecified, so the actual behavior is specific to the implementation.
The important thing to remember is that rand does not return random numbers; it returns pseudo-random numbers, and the values it returns are determined by the seed value and the number of times rand has been called. This behavior is fine for many use cases, but is not appropriate for others (for example, rand would not be appropriate for use in many cryptographic applications).
How does rand() work?
http://en.wikipedia.org/wiki/Pseudorandom_number_generator
I have read that it has something to
do with time, also you get from
including time.h
rand() has nothing at all to do with the time. However, it's very common to use time() to obtain the "seed" for the PRNG so that you get different "random" numbers each time your program is run.
Also, does it have any tendencies
towards odd or even numbers or
something like that?
Depends on the exact method used. There's one popular implementation of rand() that alternates between odd and even numbers. So avoid writing code like rand() % 2 that depends on the lowest bit being random.
I need to know the cost of succeeding with a Preimage attack ("In cryptography, a preimage attack on a cryptographic hash is an attempt to find a message that has a specific hash value.", Wikipedia).
The message I want to hash consists of six digits (the date of birth), then four random digits. This is a social security number.
Is there also a possibility to hash something using a specific password. This would introduce another layer of security as one would have to know the password in order to produce the same hash values for a message.
I am thinking about using SHA-2.
If you want to know how expensive it is to find a preimage for the string you're describing, you need to figure out how many possible strings there are. Since the first 6 digits are a date of birth, their value is even more restricted than the naive assumption of 10^6 - we have an upper bound of 366*100 (every day of the year, plus the two digit year).
The remaining 4 'random' digits permit another 10^4 possibilities, giving a total number of distinct hashes of 366 * 100 * 10^4 = 366,000,000 hashes.
With that few possibilities, it ought to be possible to find a preimage in a fraction of a second on a modern computer - or, for that matter, to build a lookup table for every possible hash.
Using a salt, as Tom suggests, will make a lookup table impractical, but with such a restricted range of valid values, a brute force attack is still eminently practical, so it alone is not sufficient to make the attack impractical.
One way to make things more expensive is to use iterative hashing - that is, hash the hash, and hash that, repeatedly. You have to do a lot less hashing than your attacker does, so increases in cost affect them more than they do you. This is still likely to be only a stopgap given the small search space, however.
As far as "using a password" goes, it sounds like you're looking for an HMAC - a construction that uses a hash, but can only be verified if you have the key. If you can keep the key secret - no easy task if you're assuming the hashes can only be obtained if your system is compromised in the first place - this is a practical system.
Edit: Okay, so 'fractions of a second' may have been a slight exaggeration, at least with my trivial Python test. It's still perfectly tractable to bruteforce on a single computer in a short timeframe, however.
SHA-2, salts, preimage atttacks, brute forcing a restricted, 6-digit number - man it would be awesome if we have a dial we could turn that would let us adjust the security. Something like this:
Time to compute a hash of an input:
SHA-2, salted Better security!
| |
\|/ \|/
|-----------------------------------------------------|
.01 seconds 3 seconds
If we could do this, your application, when verifying that the user entered data matches what you have hashed, would in fact be a few seconds slower.
But imagine being the attacker!
Awesome, he's hashing stuff using a salt, but there's only 366,000,000 possible hashes, I'm gonna blaze through this at 10,000 a second and finish in ~10 hours!
Wait, what's going on! I can only do 1 every 2.5 seconds?! This is going to take me 29 years!!
That would be awesome, wouldn't it?
Sure would.
I present unto you: scrypt and bcrypt. They give you that dial. Want to spend a whole minute hashing a password? They can do that. (Just make sure you remember the salt!)
I'm unsure what your question is exactly, but to make your encrypted value more secure, use salt values.
Edit: I think you are sort of describing salt values in your question.
This question already has answers here:
Probability of SHA1 collisions
(3 answers)
Closed 6 years ago.
Given two different strings S1 and S2 (S1 != S2) is it possible that:
SHA1(S1) == SHA1(S2)
is True?
If yes - with what probability?
If not - why not?
Is there a upper bound on the length of a input string, for which the probability of getting duplicates is 0? OR is the calculation of SHA1 (hence probability of duplicates) independent of the length of the string?
The goal I am trying to achieve is to hash some sensitive ID string (possibly joined together with some other fields like parent ID), so that I can use the hash value as an ID instead (for example in the database).
Example:
Resource ID: X123
Parent ID: P123
I don't want to expose the nature of my resource identifies to allow client to see "X123-P123".
Instead I want to create a new column hash("X123-P123"), let's say it's AAAZZZ. Then the client can request resource with id AAAZZZ and not know about my internal id's etc.
What you describe is called a collision. Collisions necessarily exist, since SHA-1 accepts many more distinct messages as input that it can produce distinct outputs (SHA-1 may eat any string of bits up to 2^64 bits, but outputs only 160 bits; thus, at least one output value must pop up several times). This observation is valid for any function with an output smaller than its input, regardless of whether the function is a "good" hash function or not.
Assuming that SHA-1 behaves like a "random oracle" (a conceptual object which basically returns random values, with the sole restriction that once it has returned output v on input m, it must always thereafter return v on input m), then the probability of collision, for any two distinct strings S1 and S2, should be 2^(-160). Still under the assumption of SHA-1 behaving like a random oracle, if you collect many input strings, then you shall begin to observe collisions after having collected about 2^80 such strings.
(That's 2^80 and not 2^160 because, with 2^80 strings you can make about 2^159 pairs of strings. This is often called the "birthday paradox" because it comes as a surprise to most people when applied to collisions on birthdays. See the Wikipedia page on the subject.)
Now we strongly suspect that SHA-1 does not really behave like a random oracle, because the birthday-paradox approach is the optimal collision searching algorithm for a random oracle. Yet there is a published attack which should find a collision in about 2^63 steps, hence 2^17 = 131072 times faster than the birthday-paradox algorithm. Such an attack should not be doable on a true random oracle. Mind you, this attack has not been actually completed, it remains theoretical (some people tried but apparently could not find enough CPU power)(Update: as of early 2017, somebody did compute a SHA-1 collision with the above-mentioned method, and it worked exactly as predicted). Yet, the theory looks sound and it really seems that SHA-1 is not a random oracle. Correspondingly, as for the probability of collision, well, all bets are off.
As for your third question: for a function with a n-bit output, then there necessarily are collisions if you can input more than 2^n distinct messages, i.e. if the maximum input message length is greater than n. With a bound m lower than n, the answer is not as easy. If the function behaves as a random oracle, then the probability of the existence of a collision lowers with m, and not linearly, rather with a steep cutoff around m=n/2. This is the same analysis than the birthday paradox. With SHA-1, this means that if m < 80 then chances are that there is no collision, while m > 80 makes the existence of at least one collision very probable (with m > 160 this becomes a certainty).
Note that there is a difference between "there exists a collision" and "you find a collision". Even when a collision must exist, you still have your 2^(-160) probability every time you try. What the previous paragraph means is that such a probability is rather meaningless if you cannot (conceptually) try 2^160 pairs of strings, e.g. because you restrict yourself to strings of less than 80 bits.
Yes it is possible because of the pigeon hole principle.
Most hashes (also sha1) have a fixed output length, while the input is of arbitrary size. So if you try long enough, you can find them.
However, cryptographic hash functions (like the sha-family, the md-family, etc) are designed to minimize such collisions. The best attack known takes 2^63 attempts to find a collision, so the chance is 2^(-63) which is 0 in practice.
git uses SHA1 hashes as IDs and there are still no known SHA1 collisions in 2014. Obviously, the SHA1 algorithm is magic. I think it's a good bet that collisions don't exist for strings of your length, as they would have been discovered by now. However, if you don't trust magic and are not a betting man, you could generate random strings and associate them with your IDs in your DB. But if you do use SHA1 hashes and become the first to discover a collision, you can just change your system to use random strings at that time, retaining the SHA1 hashes as the "random" strings for legacy IDs.
A collision is almost always possible in a hashing function. SHA1, to date, has been pretty secure in generating unpredictable collisions. The danger is when collisions can be predicted, it's not necessary to know the original hash input to generate the same hash output.
For example, attacks against MD5 have been made against SSL server certificate signing last year, as exampled on the Security Now podcast episode 179. This allowed sophisticated attackers to generate a fake SSL server cert for a rogue web site and appear to be the reaol thing. For this reason, it is highly recommended to avoid purchasing MD5-signed certs.
What you are talking about is called a collision. Here is an article about SHA1 collisions:
http://www.rsa.com/rsalabs/node.asp?id=2927
Edit: So another answerer beat me to mentioning the pigeon hole principle LOL, but to clarify this is why it's called the pigeon hole principle, because if you have some holes cut out for carrier pigeons to nest in, but you have more pigeons than holes, then some of the pigeons(an input value) must share a hole(the output value).