If you know the length of a string and apply a SHA1 hash to it, can you unhash it? - sha1

Just wondering if knowing the original string length means that you can better unlash a SHA1 encryption.

No, not in the general case: a hash function is not an encryption function and it is not designed to be reversible.
It is usually impossible to recover the original hash for certain. This is because the domain size of a hash function is larger than the range of the function. For SHA-1 the domain is unbounded but the range is 160bits.
That means that, by the Pigeonhole principle, multiple values in the domain map to the same value in the range. When such two values map to the same hash, it is called a hash collision.
However, for a specific limited set of inputs (where the domain of the inputs is much smaller than the range of the hash function), then if a hash collision is found, such as through an brute force search, it may be "acceptable" to assume that the input causing the hash was the original value. The above process is effectively a preimage attack. Note that this approach very quickly becomes infeasible, as demonstrated at the bottom. (There are likely some nice math formulas that can define "acceptable" in terms of chance of collision for a given domain size, but I am not this savvy.)
The only way to know that this was the only input that mapped to the hash, however, would be to perform an exhaustive search over all the values in the range -- such as all strings with the given length -- and ensure that it was the only such input that resulted in the given hash value.
Do note, however, that in no case is the hash process "reversed". Even without the Pigeon hole principle in effect, SHA-1 and other cryptographic hash functions are especially designed to be infeasible to reverse -- that is, they are "one way" hash functions. There are some advanced techniques which can be used to reduce the range of various hashes; these are best left to Ph.D's or people who specialize in cryptography analysis :-)
Happy coding.
For fun, try creating a brute-force preimage attack on a string of 3 characters. Assuming only English letters (A-Z, a-z) and numbers (0-9) are allowed, there are "only" 623 (238,328) combinations in this case. Then try on a string of 4 characters (624 = 14,776,336 combinations) ... 5 characters (625 = 916,132,832 combinations) ... 6 characters (626 = 56,800,235,584 combinations) ...
Note how much larger the domain is for each additional character: this approach quickly becomes impractical (or "infeasible") and the hash function wins :-)
One way password crackers speed up preimage attacks is to use rainbow tables (which may only cover a small set of all values in the domain they are designed to attack), which is why passwords that use hashing (SHA-1 or otherwise) should always have a large random salt as well.

Hash functions are one-way function. For a given size there are many strings that may have produced that hash.
Now, if you know that the input size is fixed an small enough, let's say 10 bytes, and you know that each byte can have only certain values (for example ASCII's A-Za-z0-9), then you can use that information to precompute all the possible hashes and find which plain text produces the hash you have. This technique is the basis for Rainbow tables.

If this was possible , SHA1 would not be that secure now. Is it ? So no you cannot unless you have considerable computing power [2^80 operations]. In which case you don't need to know the length either.
One of the basic property of a good Cryptographic hash function of which SHA1 happens to be one is
it is infeasible to generate a message that has a given hash

Theoretically, let's say the string was also known to be solely of ASCII characters, and it's of size n.
There are 95 characters in ASCII not including controls. We'll assume controls weren't used.
There are 95ⁿ possible such strings.
There are 1.461501×10⁴⁸ possible SHA-1 values (give or take) and a just n=25, there are 2.7739×10⁴⁹ possible ASCII-only strings without controls in them, which would mean guaranteed collisions (some such strings have the same SHA-1).
So, we only need to get to n=25 when this becomes impossible even with infinite resources and time.
And remember, up until now I've been making it deliberately easy with my ASCII-only rule. Real-world modern text doesn't follow that.
Of course, only a subset of such strings would be anything likely to be real (if one says "hello my name is Jon" and the other says "fsdfw09r12esaf" then it was probably the first). Stil though, up until now I was assuming infinite time and computing power. If we want to work it out sometime before the universe ends, we can't assume that.
Of course, the nature of the attack is also important. In some cases I want to find the original text, while in others I'll be happy with gibberish with the same hash (if I can input it into a system expecting a password).
Really though, the answer is no.

I posted this as an answer to another question, but I think it is applicable here:
SHA1 is a hashing algorithm. Hashing is one-way, which means that you can't recover the input from the output.
This picture demonstrates what hashing is, somewhat:
As you can see, both John Smith and Sandra Dee are mapped to 02. This means that you can't recover which name was hashed given only 02.
Hashing is used basically due to this principle:
If hash(A) == hash(B), then there's a really good chance that A == B. Hashing maps large data sets (like a whole database) to a tiny output, like a 10-character string. If you move the database and the hash of both the input and the output are the same, then you can be pretty sure that the database is intact. It's much faster than comparing both databases byte-by-byte.
That can be seen in the image. The long names are mapped to 2-digit numbers.
To adapt to your question, if you use bruteforce search, for a string of a given length (say length l) you will have to hash through (dictionary size)^l different hashes.
If the dictionary consists of only alphanumeric case-sensitive characters, then you have (10 + 26 + 26)^l = 62^l hashes to hash. I'm not sure how many FLOPS are required to produce one hash (as it is dependent on the hash's length). Let's be super-unrealistic and say it takes 10 FLOP to perform one hash.
For a 12-character password, that's 62^12 ~ 10^21. That's 10,000 seconds of computations on the fastest supercomputer to date.
Multiply that by a few thousand and you'll see that it is unfeasible if I increase my dictionary size a little bit or make my password longer.

Related

Calculation of Internet Checksum of two 16-bit streams

I want to calculate Internet checksum of two bit streams of 16 bits each. Do I need to break these strings into segments or I can directly sum the both?
Here are the strings:
String 1 = 1010001101011111
String 2 = 1100011010000110
Short answer
No. You don't need to split them.
Somewhat longer answer
Not sure exactly what you mean by "internet" checksum (a hash or checksum is just the result of a mathematical operation, and has no direct relation or dependence on the internet), but anyway:
The checksum of any value should not depend on the length of the input. In theory, your input strings could be of any length at all.
You can test this with a basic online checksum generator such as this one, for instance. That appears to generate a whole slew of checksums using lots of different algorithms. The names of the algorithms appear on the left in the list.
If you want to do this in code, a good starting point might be to search for examples using one of them in whatever language / environment you are working in.

What are buckets in terms of hash functions?

Looking at the book Mining of Massive Datasets, section 1.3.2 has an overview of Hash Functions. Without a computer science background, this is quite new to me; Ruby was my first language, where a hash seems to be equivalent to Dictionary<object, object>. And I had never considered how this kind of datastructure is put together.
The book mentions hash functions, as a means of implementing these dictionary data structures. This paragraph:
First, a hash function h takes a hash-key value as an argument and produces
a bucket number as a result. The bucket number is an integer, normally in the
range 0 to B − 1, where B is the number of buckets. Hash-keys can be of any
type. There is an intuitive property of hash functions that they “randomize”
hash-keys
What exactly are buckets in terms of a hash function? it sounds like buckets are array-like structures, and that the hash function is some kind of algorithm / array-like-structure search that produces the same bucket number every time? What is inside this metaphorical bucket?
I've always read that javascript objects/ruby hashes/ etc don't guarantee order. In practice I've found that keys' order doesn't change (actually, I think using an older version of Mozilla's Rhino interpreter that the JS object order DID change, but I can't be sure...).
Does that mean that hashes (Ruby) / objects (JS) ARE NOT resolved by these hash functions?
Does the word hashing take on different meanings depending on the level at which you are working with computers? i.e. it would seem that a Ruby hash is not the same as a C++ hash...
When you hash a value, any useful hash function generally has a smaller range than the domain. This means that out of a large list of input values (for example all possible combinations of letters) it will output any of a smaller list of values (a number capped at a certain length). This means that more than one input value can map to the same output value.
When this is the case, the output values are refered to as buckets.
Consider the function f(x) = x mod 2
This generates the following outputs;
1 => 1
2 => 0
3 => 1
4 => 0
In this case there are two buckets (1 and 0), with a bunch of input values that fall into each.
A good hash function will fill all of these 'buckets' equally, and so enable faster searching etc. If you take the mod of any number, you get the bucket to look into, and thus have to search through less results than if you just searched initially, since each bucket has less results in it than the whole set of inputs. In the ideal situation, the hash is fast to calculate and there is only one result in each bucket, this enables lookups to take only as long as applying the hash function takes.
This is a simplified example of course but hopefully you get the idea?
The concept of a hash function is always the same. It's a function that calculates some number to represent an object. The properties of this number should be:
it's relatively cheap to compute
it's as different as possible for all objects.
Let's give a really artificial example to show what I mean with this and why/how hashes are usually used.
Take all natural numbers. Now let's assume it's expensive to check if 2 numbers are equal.
Let's also define a relatively cheap hash function as follows:
hash = number % 10
The idea is simple, just take the last digit of the number as the hash. In the explanation you got, this means we put all numbers ending in 1 into an imaginary 1-bucket, all numbers ending in 2 in the 2-bucket etc...
Those buckets don't really exists as data structure. They just make it easy to reason about the hash function.
Now that we have this cheap hash function we can use it to reduce the cost of other things. For example, we want to create a new datastructure to enable cheap searching of numbers. Let's call this datastructure a hashmap.
Here we actually put all the numbers with hash=1 together in a list/set/..., we put the numbers with hash=5 into their own list/set ... etc.
And if we then want to lookup some number, we first calculate it's hash value. Then we check the list/set corresponding to this hash, and then compare only "similar" numbers to find our exact number we want. This means we only had to do a cheap hash calculation and then have to check 1/10th of the numbers with the expensive equality check.
Note here that we use the hash function to define a new datastructure. The hash itself isn't a datastructure.
Consider a phone book.
Imagine that you wanted to look for Donald Duck in a phone book.
It would be very inefficient to have to look every page, and every entry on that page. So rather than doing that, we do the following thing:
We create an index
We create a way to obtain an index key from a name
For a phone book, the index goes from A-Z, and the function used to get the index key, is just getting first letter from the Surname.
In this case, the hashing function takes Donald Duck and gives you D.
Then you take D and go to the index where all the people with Surnames starting with D are.
That would be a very oversimplified way to put it.
Let me explain in simple terms. Buckets come into picture while handling collisions using chaining technique ( Open hashing or Closed addressing)
Here, each array entry shall correspond to a bucket and each array entry (if nonempty) will be having a pointer to the head of the linked list. (The bucket is implemented as a linked list).
The hash function shall be used by hash table to calculate an index into an array of buckets, from which the desired value can be found.
That is, while checking whether an element is in the hash table, the key is first hashed to find the correct bucket to look into. Then, the corresponding linked list is traversed to locate the desired element.
Similarly while any element addition or deletion, hashing is used to find the appropriate bucket. Then, the bucket is checked for presence/absence of required element, and accordingly it is added/removed from the bucket by traversing corresponding linked list.

For a given hash value, is it possible to guess whether it is generated by MD5 or SHA-1?

Given a hash value, is it possible to guess the hash function used to generate it?
For example, let's say that 9b35a8503abcecadfb85726cfefb99a9 is generated by MD5 or SHA-1(If it's SHA-1, let's say that it is only the first 16 bytes of it), and the content was plain english text. Is there any hint that makes it more likely to be generated by MD5 than SHA-1 or vice versa?
No. If there was, that would indicate some defect in the hashing algorithm.
Of course, you can search against a rainbow table or by brute force. But other than that, there's no significant hint.

Convert SHA1 back to string

I have a user model on my app, and my password field uses sha1. What i want is to, when i get the sha1 from the DB, to make it a string again. How do i do that?
You can't - SHA1 is a one-way hash. Given the output of SHA1(X), is not possible to retrieve X (at least, not without a brute force search or dictionary/rainbow table scan)
A very simple way of thinking about this is to imagine I give you a set of three-digit numbers to add up, and you tell me the final two digits of that sum. It's not possible from those two digits for me to work out exactly which numbers you started out with.
See also
Is it possible to reverse a sha1?
Decode sha1 string to normal string
Thought relating MD5, these other questions may also enlighten you:
Reversing an MD5 Hash
How can it be impossible to “decrypt” an MD5 hash?
You can't -- that's the point of SHA1, MDB5, etc. Most of those are one-way hashes for security. If it could be reversed, then anyone who gained access to your database could get all of the passwords. That would be bad.
Instead of dehashing your database, instead hash the password attempt and compare that to the hashed value in the database.
If you're talking about this from a practical viewpoint, just give up now and consider it impossible. Finding the original string is impossible (except by accident). Most of the point of a cryptographically secure hash is to ensure you can't find any other string that produces the same hash either.
If you're interested in research into secure hash algorithms: finding a string that will produce a given hash is called a "preimage". If you can manage to do so (with reasonable computational complexity) for SHA-1 you'll probably become reasonably famous among cryptanalysis researchers. The best "break" against SHA-1 that's currently known is a way to find two input strings that produce the same hash, but 1) it's computationally quite expensive (think in terms of a number of machines running 24/7 for months at a time to find one such pair), and does not work for an arbitrary hash value -- it finds one of a special class of input strings for which a matching pair is (relatively) easy to find.
SHA is a hashing algorithm. You can compare the hash of a user-supplied input with the stored hash, but you can't easily reverse the process (rebuild the original string from the stored hash).
Unless you choose to brute-force or use rainbow tables (both extremely slow when provided with a sufficiently long input).
You can't do that with SHA-1. But, given what you need to do, you can try using AES instead. AES allows encryption and decryption.

Method for generating numerical values from a URL

In the 90s there was a toy called Barcode Battler. It scanned barcodes, and from the values generated an RPG like monster with various stats such as hit points, attack power, magic power, etc. Could there be a way to do a similar thing with a URL? From just an ordinary URL, generate stats like that. I was thinking of maybe taking the ASCII values of various characters in the URL and using them, but this seems too predictable and obvious.
Take the MD5 sum of the ASCII encoding of the URL? Incredibly easy to do on most platforms. That would give you 128 bits to come up with the stats from. If you want more, use a longer hash algorithm.
(I can't remember the details about what's allowed in a URL - if non-ASCII is allowed, you could use UTF-8 instead.)

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