How many md5 hashes are possible

This could be a password, or a file you downloaded in which case you won't have O but rather the hash of it h O that came with P , most likely.

First, you hash P to get h P. As you stated, because of the Pigeonhole Principle this could mean that different objects hashed to the same value, and further action may need to be taken. This may work for passwords if you restrict the length and complexity of characters, for example. It is why you see hashes of passwords stored in databases rather than the passwords themselves. You may decide that just because the hash came out equal doesn't mean the objects are equal, and do a direct comparison of O and P.

You may have a false positive. So while you may have false positive matches, you won't have false negatives. Depending on your application, and whether you expect the objects to always be equal or always be different, hashing may be a superfluous step. Cryptographic one-way hash functions are, by nature of definition, not Injective. In terms of hash functions, "unique" is pretty meaningless.

These functions are measured by other attributes, which affects their strength by making it hard to create a pre-image of a given hash. For example, we may care about how many image bits are affected by changing a single bit in the pre-image.

We may care about how hard it is to conduct a brute force attack finding a prie-image for a given hash image. We may care about how hard it is to find a collision: finding two pre-images that have the same hash image, to be used in a birthday attack.

While it is likely that you get collisions if the values to be hashed are much longer than the resulting hash, the number of collisions is still sufficiently low for most purposes there are 2 possible hashes total so the chance of two random strings producing the same hash is theoretically close to 1 in 10 MD5 was primarily created to do integrity checks, so it is very sensitive to minimal changes. A minor modification in the input will result in a drastically different output.

This is why it is hard to guess a password based on the hash value alone. While the hash itself is not reversible, it is still possible to find a possible input value by pure brute force.

This is why you should always make sure to add a salt if you are using MD5 to store password hashes: if you include a salt in the input string, a matching input string has to include exactly the same salt in order to result in the same output string because otherwise the raw input string that matches the output will fail to match after the automated salting i. So hashes are not unique, but the authentication mechanism can be made to make it sufficiently unique which is one somewhat plausible argument for password restrictions in lieu of salting: the set of strings that results in the same hash will probably contain many strings that do not obey the password restrictions, so it's more difficult to reverse the hash by brute force -- obviously salts are still a good idea nevertheless.

Bigger hashes mean a larger set of possible hashes for the same input set, so a lower chance of overlap, but until processing power advances sufficiently to make brute-forcing MD5 trivial, it's still a decent choice for most purposes.

Cryptographic hash functions are designed to have very, very, very, low duplication rates. For the obvious reason you state, the rate can never be zero. The Wikipedia page is informative. As Mike and basically every one else said, its not perfect, but it does the job, and collision performance really depends on the algo which is actually pretty good. What is of real interest is automatic manipulation of files or data to keep the same hash with different data, see this Demo. As others have answered, hash functions are by definition not guaranteed to return unique values, since there are a fixed number of hashes for an infinite number of inputs.

Their key quality is that their collisions are unpredictable. In other words, they're not easily reversible -- so while there may be many distinct inputs that will produce the same hash result a "collision" , finding any two of them is computationally infeasible. Stack Overflow for Teams — Collaborate and share knowledge with a private group.

Create a free Team What is Teams? Collectives on Stack Overflow. A typical use of hash functions is to perform validation checks. One frequent usage is the validation of compressed collections of files, such as.

Given an archive and its expected hash value commonly referred to as a checksum , you can perform your own hash calculation to validate that the archive you received is complete and uncorrupted. For instance, I can generate an MD5 checksum for a tar file in Unix using the following piped commands:. The generated checksum can be posted on the download site, next to the archive download link.

The receiver, once they have downloaded the archive, can validate that it came across correctly by running the following command:. Successful execution of the above command will generate an OK status like this:. If you read this far, tweet to the author to show them you care. Tweet a thanks.

Learn to code for free. Get started. Forum Donate. Jeff M Lowery. What's a hash function? An ideal hash function has the following properties: it is very fast it can return an enormous range of hash values it generates a unique hash for every unique input no collisions it generates dissimilar hash values for similar input values generated hash values have no discernable pattern in their distribution No ideal hash function exists, of course, but each aims to operate as close to the ideal as possible.

For example, take the following two very similar sentences: 1. So, nowadays it is actually possible to artificially produce MD5 collisions. All you need is time, hardware and the proper software. Some time ago we got some samples with identical MD5 hash but different SHA and we were surprised. There was a possibility that it was a natural fortuity but as this seemed rather unlikely, we took a deeper look into the files. Here is what we found:. The difference between the two samples is the leading bit in each nibble has been flipped.

For example, the 20th byte offset 0x in the top sample File A , 0xE2, is in binary. The leading bit in the first nibble is flipped to make , which is 0x62 as shown in the lower sample File B. All that is needed to generate two colliding files is a template file with a byte block of data, aligned on a byte boundary that can be changed freely by the collision-finding algorithm.

Additionally, it was also discovered that it is possible to build collisions between two files with separately chosen prefixes. This technique was used in the creation of the rogue CA certificate in