Why can't you just reverse the algorithm like you could reverse a math function? How is it possible to make an algorithm that isn't reversible?
And if you use a rainbow table, what makes using a salt impossible to crack it? If you are making a rainbow table with brute force to generate it, then it invents each plaintext value possible (to a length), which would end up including the salt for each possible password and each possible salt (the salt and password/text would just come together as a single piece of text).
MD5 is designed to be cryptographically irreversible. In this case, the most important property is that it is computationally unfeasible to find the reverse of a hash, but it is easy to find the hash of any data. For example, let's think about just operating on numbers (binary files after all, could be interpreted as just a very long number).
Let's say we have the number "7", and we want to take the hash of it. Perhaps the first thing we try as our hash function is "multiply by two". As we'll see, this is not a very good hash function, but we'll try it, to illustrate a point. In this case, the hash of the number will be "14". That was pretty easy to calculate. But now, if we look at how hard it is to reverse it, we find that it is also just as easy! Given any hash, we can just divide it by two to get the original number! This is not a good hash, because the whole point of a hash is that it is much harder to calculate the inverse than it is to calculate the hash (this is the most important property in at least some contexts).
Now, let's try another hash. For this one, I'm going to have to introduce the idea of clock arithmetic. On a clock, there aren't an infinite amount of number. In fact, it just goes from 0 to 11 (remember, 0 and 12 are the same on a clock). So if you "add one" to 11, you just get zero. You can extend the ideas of multiplication, addition, and exponentiation to a clock. For example, 8+7=15, but 15 on a clock is really just 3! So on a clock, you would say 8+7=3! 6*6=36, but on a clock, 36=0! so 6*6=0! Now, for the concept of powers, you can do the same thing. 2^4=16, but 16 is just 4. So 2^4=4! Now, here's how it ties into hashing. How about we try the hash function f(x)=5^x, but with clock arithmetic. As you'll see, this leads to some interesting results. Let's try taking the hash of 7 as before.
We see that 5^7=78125 but on a clock, that's just 5 (if you do the math, you see that we've wrapped around the clock 6510 times). So we get f(7)=5. Now, the question is, if I told you that the hash of my number was 5, would you be able to figure out that my number was 7? Well, it's actually very hard to calculate the reverse of this function in the general case. People much smarter than me have proved that in certain cases, reversing this function is way harder than calculating it forward. (EDIT: Nemo has pointed out that this in fact has not been "proven"; in fact, the only guarantee you get is that a lot of smart people have tried a long time to find an easy way to do so, and none of them have succeeded.) The problem of reversing this operation is called the "Discrete Logarithm Problem". Look it up for more in depth coverage. This is at least the beginning of a good hash function.
With real world hash functions, the idea is basically the same: You find some function that is hard to reverse. People much smarter than me have engineered MD5 and other hashes to make them provably hard to reverse.
Now, perhaps earlier the thought has occurred to you: "it would be easy to calculate the inverse! I'd just take the hash of every number until I found the one that matched!" Now, for the case where the numbers are all less than twelve, this would be feasible. But for the analog of a real-world hash function, imagine all the numbers involved are huge. The idea is that it is still relatively easy to calculate the hash function for these large numbers, but to search through all possible inputs becomes harder much quicker. But what you've stumbled upon is the still a very important idea though: searching through the input space for an input which will give a matching output. Rainbow tables are a more complex variation on the idea, which use precomputed tables of input-output pairs in smart ways in order to make it possible to quickly search through a large number of possible inputs.
Now let's say that you are using a hash function to store passwords on your computer. The idea is this: The computer just stores the hash of the correct password. When a user tries to login, you compare the hash of the input password to the hash of the correct password. If they match, you assume the user has the correct password. The reason this is advantageous is because if someone steals your computer, they still don't have access to your password, just the hash of it. Because the hash function was designed by smart people to be hard to take the reverse of, they can't easily retrieve your password from it.
An attacker's best bet is a bruteforce attack, where they try a bunch of passwords. Just like you might try the numbers less that 12 in the previous problem, an attacker might try all the passwords just composed of numbers and letters less than 7 characters long, or all words which show up in the dictionary. The important thing here is that he can't try all possible passwords, because there are way too many possible 16 character passwords, for example, to ever test. So the point is that an attacker has to restrict the possible passwords he tests, otherwise he will never even check a small percentage of them.
Now, as for a salt, the idea is this: What if two users had the same password? They would have the same hash. If you think about it, the attacker doesn't really have to crack every users password individually. He simply goes through every possible input password, and compares the hash to all the hashes. If it matches one of them, then he has found a new password. What we'd really like to force him to do is calculate a new hash for every user+password combination he wants to check. That's the idea of a salt, is that you make the hash function be slightly different for every user, so he can't reuse a single set of precomputed values for all users. The most straightforward way to do this is to tack on some random string to each user's password before you take the hash, where the random string is different for each user. So, for example, if my password is "shittypassword", my hash might show up as MD5("6n93nshittypassword") and if your password is "shittypassword", your hash might show up as MD5("fa9elshittypassword"). This little bit "fa9el" is called the "salt", and it's different for every user. For example, my salt is "6n93n". Now, this little bit which is tacked on to your password is just stored on your computer as well. When you try to login with the password X, the computer can just calculate MD5("fa9el"+X) and see if it matches the stored hash.
So the basic mechanics of logging in remain unchanged, but for an attacker, they are now faced with a more daunting challenge: rather than a list of MD5 hashes, they are faced with a list of MD5 sums and salts. They essentially have two options:
They can ignore the fact that the hashes are salted, and try to crack the passwords with their lookup table as is. However, the chances that they'll actually crack a password are much reduced. For example, even if "shittypassword" is on their list of inputs to check, most likely "fa9elshittypassword" isn't. In order to get even a small percentage of the probability of cracking a password that they had before, they'll need to test orders of magnitude more possible passwords.
They can recalculate the hashes on a per-user basis. So rather than calculating MD5(passwordguess), for each user X, they calculate MD5( Salt_of_user_X + passwordguess). Not only does this force them to calculate a new hash for each user they want to crack, but also most importantly, it prevents them from being able to use precalculated tables (like rainbow table, for example), because they can't know what Salt_of_user_X is before hand, so they can't precalculate the hashes to test.
So basically, if they are trying to use precalculated tables, using a salt effectively greatly increases the possible inputs they have to test in order to crack the password, and even if they aren't using precalculated tables, it still slows them down by a factor of N, where N is the number of passwords you are storing.
Hopefully this answers all your questions.
Think of 2 numbers from 1 to 9999. Add them. Now tell me the final digit.
I can't, from that information, deduce which numbers you originally thought of. That is a very simple example of a one-way hash.
Now, I can think of two numbers which give the same result, and this is where this simple example differs from a 'proper' cryptographic hash like MD5 or SHA1. With those algorithms, it should be computationally difficult to come up with an input which produces a specific hash.
One big reason you can't reverse the hash function is because data is lost.
Consider a simple example function: 'OR'. If you apply that to your input data of 1 and 0, it yields 1. But now, if you know the answer is '1', how do you back out the original data? You can't. It could have been 1,1 or maybe 0,1, or maybe 1,0.
As for salting and rainbow tables. Yes, theoretically, you could have a rainbow table which would encompass all possible salts and passwords, but practically, that's just too big. If you tried every possible combination of lower case letters, upper case, numbers, and twelve punctuation symbols, up to 50 characters long, that's (26+26+10+12)^50 = 2.9 x 10^93 different possibilities. That's more than the number of atoms in the visible universe.
The idea behind rainbow tables is to calculate the hash for a bunch of possible passwords in advance, and passwords are much shorter than 50 characters, so it's possible to do so. That's why you want to add a salt in front: if you add on '57sjflk43380h4ljs9flj4ay' to the front of the password. While someone may have already computed the hash for "pa55w0rd", no one will have already calculated the has for '57sjflk43380h4ljs9flj4aypa55w0rd'.
I don't think the md5 gives you the whole result - so you can't work backwards to find the original things that was md5-ed
md5 is 128bit, that's 3.4*10^38 combinations.
the total number of eight character length passwords:
only lowercase characters and numbers: 36^8 = 2.8*10^12
lower&uppercase and numbers: 62^8 = 2.18*10^14
You have to store 8 bytes for the password, 16 for the md5 value, that's 24 bytes total per entry.
So you need approx 67000G or 5200000G storage for your rainbow table.
The only reason that it's actually possible to figure out passwords is because people use obvious ones.
Related
I was just messing around with some code on python and realized it was not that difficult to the find out what a password is if you have the md5 (basically a brute force attack, imputing md5, going through millions of passwords, converting them to md5 and checking if it matches, and then outputting the password) but what is difficult is getting the md5. I did some digging and all i found was some videos of people using randomly generated md5 hashes of passwords and then finding out what password it corresponded to. What i was wondering was if there was any way you could find the md5 hash of a password without having the original password. Thx
-If anything is unclear just tell me in the comments and i will clean it up
You're correct that you can brute-force an md5 hash to retrieve the original password, provided that the original password and the brute-force attempts hash to the same value. To compensate for this, often password systems use what's known as "salt" to make this significantly more difficult. (See also: What is SALT and how do i use it?)
The answer to your question, in general, is no, there is no easy way to obtain the hash of some value without having that value first.
Originally, hashing algorithms were designed to take some input and manipulate it so the output of the algorithm can be used as an index into a table of values. The goal is to have a 1:1 hash (ideally that's extremely fast, hopefully constant time). This means that given some input value x, y = hash(x) should be such that ONLY x hashes to y. In other words, y1 = hash(x1) = hash(x) if, and only if, x1 = x.
As time went on, algorithms were developed that had other properties. Since it became common for hashing algorithms to be used to things like password storage and quick comparison, one of the things that was valued with a hashing algorithm is how small changes to the input should lead to differences in the output. In other words, the hashing function hash(x) should change if x changes entirely, (as in the case of not(x)), or if it changes by a single bit.
One corollary is that, if hash(x) changes significantly when you change a single bit (as in the case of hash(x+0x000001), then it makes the comparison function much faster (since you really only need to check the higher order bits to determine if two objects are the same, in the average case). This means that you can't easily compute the hash of sequential items simply by iterating through hashes (i.e. "guessing" the hash output of the function hash(x) without first having x).
I create Antiplagiat. I use a shingle method. For example, I have the following shingles:
I go to the cinema
I go to the cinema1
I go to th cinema
Is there a method of calculating the equal hash for these lines?
I know of the existence of Levenshtein distance. However, I do not know what I should take source word. Maybe there is a better way than to consider Levenshtein distance.
The problem with hashing is that, logically, you'll run into 2 strings that differ by a single character that hash to different values.
Small proof:
Consider all possible strings.
Assume all of these hash to at least 2 different values.
Take any 2 strings A and B that hash to different values.
You can obviously go from A to B by just changing one character at a time.
Thus at some point the hash will change.
Thus at this point the hash will be different for a single character change.
Some options I can think of:
Hash multiple parts of the string and check each of these hashes. Probably won't work too well since a single character omission will cause significant difference in the hash values.
Check a range of hashes. A hash is one dimensional, but string similarity is not, thus this probably won't work either.
All in all, hashing is probably not the way to go.
This questions is a bit old but you may be interested in this paper by two researchers at AT&T. They employ a technique that is reminiscent of the Nilsimsa hash to detect when similar sms messages have been seen an "abnormal" number of times in a time window.
It sounds Locality Sensitive hashing would also be pertinent to your problem.
I'm aware that MD5 has had some collisions but this is more of a high-level question about hashing functions.
If MD5 hashes any arbitrary string into a 32-digit hex value, then according to the Pigeonhole Principle surely this can not be unique, as there are more unique arbitrary strings than there are unique 32-digit hex values.
You're correct that it cannot guarantee uniqueness, however there are approximately 3.402823669209387e+38 different values in a 32 digit hex value (16^32). That means that, assuming the math behind the algorithm gives a good distribution, your odds are phenomenally small that there will be a duplicate. You do have to keep in mind that it IS possible to duplicate when you're thinking about how it will be used. MD5 is generally used to determine if something has been changed (I.e. it's a checksum). It would be ridiculously unlikely that something could be modified and result in the same MD5 checksum.
Edit: (given recent news re: SHA1 hashes)
The answer above, still holds, but you shouldn't expect an MD5 hash to serve as any kind of security check against manipulation. SHA-1 Hashes as 2^32 (over 4 billion) times less likely to collide, and it has been demonstrated that it is possible to contrive an input to produce the same value. (This was demonstrated against MD5 quite some time ago). If you're looking to ensure nobody has maliciously modified something to produce the same hash value, these days, you need at SHA-2 to have a solid guarantee.
On the other hand, if it's not in a security check context, MD5 still has it's usefulness.
The argument could be made that an SHA-2 hash is cheap enough to compute, that you should just use it anyway.
You are absolutely correct. But hashes are not about "unique", they are about "unique enough".
As others have pointed out, the goal of a hash function like MD5 is to provide a way of easily checking whether two objects are equivalent, without knowing what they originally were (passwords) or comparing them in their entirety (big files).
Say you have an object O and its hash hO. You obtain another object P and wish to check whether it is equal to O. This could be a password, or a file you downloaded (in which case you won't have O but rather the hash of it hO that came with P, most likely). First, you hash P to get hP.
There are now 2 possibilities:
hO and hP are different. This must mean that O and P are different, because using the same hash on 2 values/objects must yield the same value. Hashes are deterministic. There are no false negatives.
hO and hP are equal. 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.
a. Because the number of possibilities is so high, if you have faith in your hash function it may be enough to say "Well there was a 1 in 2128 chance of collision (ideal case), so we can assume O = P. 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.
b. 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 2128 possible hashes total so the chance of two random strings producing the same hash is theoretically close to 1 in 1038).
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.e. you can't just "reverse" the MD5 and use it to log in because the reversed MD5 hash will most likely not be the salted string that originally resulted in the creation of the hash).
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.
(It seems to be Hash Function Sunday.)
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.
This is basically a math problem, but very programing related: if I have 1 billion strings containing URLs, and I take the first 64 bits of the MD5 hash of each of them, what kind of collision frequency should I expect?
How does the answer change if I only have 100 million URLs?
It seems to me that collisions will be extremely rare, but these things tend to be confusing.
Would I be better off using something other than MD5? Mind you, I'm not looking for security, just a good fast hash function. Also, native support in MySQL is nice.
EDIT: not quite a duplicate
If the first 64 bits of the MD5 constituted a hash with ideal distribution, the birthday paradox would still mean you'd get collisions for every 2^32 URL's. In other words, the probability of a collision is the number of URL's divided by 4,294,967,296. See http://en.wikipedia.org/wiki/Birthday_paradox#Cast_as_a_collision_problem for details.
I wouldn't feel comfortable just throwing away half the bits in MD5; it would be better to XOR the high and low 64-bit words to give them a chance to mix. Then again, MD5 is by no means fast or secure, so I wouldn't bother with it at all. If you want blinding speed with good distribution, but no pretence of security, you could try the 64-bit versions of MurmurHash. See http://en.wikipedia.org/wiki/MurmurHash for details and code.
You have tagged this as "birthday-paradox", I think you know the answer already.
P(Collision) = 1 - (2^64)!/((2^64)^n (1 - n)!)
where n is 1 billion in your case.
You will be a bit better using something other then MD5, because MD5 have pratical collusion problem.
From what I see, you need a hash function with the following requirements,
Hash arbitrary length strings to a 64-bit value
Be good -- Avoid collisions
Not necessarily one-way (security not required)
Preferably fast -- which is a necessary characteristic for a non-security application
This hash function survey may be useful for drilling down to the function most suitable for you.
I will suggest trying out multiple functions from here and characterizing them for your likely input set (pick a few billion URL that you think you will see).
You can actually generate another column like this test survey for your test URL list to characterize and select from the existing or any new hash functions (more rows in that table) that you might want to check. They have MSVC++ source code to start with (reference to ZIP link).
Changing the hash functions to suit your output width (64-bit) will give you a more accurate characterization for your application.
If you have 2^n hash possibilities, there's over a 50% chance of collision when you have 2^(n/2) items.
E.G. if your hash is 64 bits, you have 2^64 hash possibilities, you'd have a 50% chance of collision if you have 2^32 items in a collection.
Just by using a hash, there is always a chance of collisions. And you don't know beforehand wether collisions will happen once or twice, or even hundreds or thousands of times in your list of urls.
The probability is still just a probability. Its like throwing a dice 10 or 100 times, what are the chances of getting all sixes? The probability says it is low, but it still can happen. Maybe even many times in a row...
So while the birthday paradox shows you how to calculate the probabilities, you still need to decide if collisions are acceptable or not.
...and collisions are acceptable, and hashes are still the right way to go; find a 64 bit hashing algorithm instead of relying on "half-a-MD5" having a good distribution. (Though it probably has...)
I was reading this question on MD5 hash values and the accepted answer confuses me. One of the main properties, as I understand it, of a cryptopgraphic hash function is that it is infeasible to find two different messages (inputs) with the same hash value.
Yet the consensus answer to the question Why aren't MD5 hash values reversible? is Because an infinite number of input strings will generate the same output. This seems completely contradictory to me.
Also, what perplexes me somewhat is the fact that the algorithms are public, yet the hash values are still irreversible. Is this because there is always data loss in a hash function so there's no way to tell which data was thrown away?
What happens when the input data size is smaller than the fixed output data size (e.g., hashing a password "abc")?
EDIT:
OK, let me see if I have this straight:
It is really, really hard to infer the input from the hash because there are an infinite amount of input strings that will generate the same output (irreversible property).
However, finding even a single instance of multiple input strings that generate the same output is also really, really hard (collision resistant property).
Warning: Long answer
I think all of these answers are missing a very important property of cryptographic hash functions: Not only is it impossible to compute the original message that was hashed to get a given hash, it's impossible to compute any message that would hash to a given hash value. This is called preimage resistance.
(By "impossible" - I mean that no one knows how to do it in less time than it takes to guess every possible message until you guess the one that was hashed into your hash.)
(Despite popular belief in the insecurity of MD5, MD5 is still preimage resistant. Anyone who doesn't believe me is free to give me anything that hashes to 2aaddf751bff2121cc51dc709e866f19. What MD5 doesn't have is collision resistance, which is something else entirely.)
Now, if the only reason you can't "work backwards" in a cryptographic hash function was because the hash function discards data to create the hash, then it would not guarantee preimage resistance: You can still "work backwards", and just insert random data wherever the hash function discards data, and while you wouldn't come up with the original message, you'd still come up with a message that hashes to the desired hash value. But you can't.
So the question becomes: Why not? (Or, in other words, how do you make a function preimage resistant?)
The answer is that cryptographic hash functions simulate chaotic systems. They take your message, break it into blocks, mix those blocks around, have some of the blocks interact with each other, mix those blocks around, and repeat that a lot of times (well, one cryptographic hash function does that; others have their own methods). Since the blocks interact with each other, block C not only has to interact with block D to produce block A, but it has to interact with block E to produce block B. Now, sure, you can find values of blocks C, D, E that would produce the blocks A and B in your hash value, but as you go further back, suddenly you need a block F that interacts with C to make D, and with E to make B, and no such block can do both at the same time! You must have guessed wrong values for C, D, and E.
While not all cryptographic hash functions are exactly as described above with block interaction, they have the same idea: That if you try to "work backwards", you're going to end up with a whole lot of dead ends, and the time it takes for you to try enough values to generate a preimage is on the order of hundreds to millions of years (depending on the hash function), not much better than the time it would take just to try messages until you find one that works.
1: The primary purpose of a hash is to map a very, very large space to a smaller but still very large space (e.g., MD5, which will take 'anything' and convert it into a space of size 2^128 -- big, but not nearly as big as aleph-0.)
In addition to other features, good hashes fill the destination space homogeneously. Bad hashes fill the space in a clumpy fashion, coming up with the same hash for many common inputs.
Imagine the idiotic hash function sum(), which just adds all the digits of the input number: it succeeds in mapping down, but there are a bunch of collisions (inputs with the same output, like 3 and 12 and 21) at the low end of the output space and the upper end of the space is nearly empty. As a result it makes very poor use of the space, is easy to crack, etc.
So a good hash that makes even use of the destination space will make it difficult to find two inputs with the same output, just by the odds: if MD5 were perfect, the odds that two inputs would have the same output would be 2^-128. That's pretty decent odds: the best you can do without resorting to a larger output space. (In truth MD5 isn't perfect, which is one of the things that makes it vulnerable.)
But it will still be true that a huge number of inputs will map to any given hash, because the input space is 'infinite', and dividing infinity by 2^128 still gives you infinity.
2: Yes, hashes always cause data loss, except in the case where your output space is the same as, or larger than, your input space -- and in that case you probably didn't need to hash!
3: For smaller inputs, best practice is to salt the input. Actually, that's good practice for any cryptographic hashing, because otherwise an attacker can feed you specific inputs and try to figure out which hash you are using. 'Salt' is just a set of additional information that you append (or prepend) to your input; you then hash the result.
edit: In cryptography, it is also important that the hash function is resistant to preimage attacks, intuitively, that is hard to guess the input for a given output even knowing many other input/output pairs. The "sum" function could probably be guessed rather easily (but since it destroys data still might not be easy to reverse).
You may be confused, because the answer to the question you cite is confusing.
One of the requirements for a cryptographic hash function is that it should be preimage resistant. That is, if you know MD5(x) but not the message x, then it is difficult to find any x' (either equal x or different from x) such that MD5(x') = MD5(x).
Being preimage resistant is a different property than being reversible. A function is reversible if given y = f(x) there is exactly one x which fits (whether this is easy or not). For example define f(x) = x mod 10.
Then f is not reversible. From f(x) = 7 you can't determine whether x was 17, 27 or something else. But f is not preimage resistant, since values x' such that f(x) = 7 are easy to find. x' = 17, 27, 12341237 etc all work.
When doing crypto you usually need functions that are preimage resistant (and other properties such as collision resistance), not just something that is not reversible.
These are the properties of hash functions in general.
A word of caution though, MD5 shouldn't be used anymore because of vulnerabilities that have been found in it. Check the 'Vulnerabilities' section and external links detailing these attacks. http://en.wikipedia.org/wiki/Md5 You can make an MD5 collision by changing only 128 bits in a message.
SHA-1 is safe for simple hashing although there are some attacks that would make it weaker against well-funded entities (Governments, large corporations)
SHA-256 is a safe starting point against technology for the next couple decades.
Yet the consensus answer to the question "why aren't MD5 hash values reversible?" is because "an infinite number of input strings will generate the same output."
This is true for any hash function, but it is not the essence of a cryptographic hash function.
For short input strings such as passwords it is theoretically possible to reverse a cryptographic hash function, but it ought to be computationally infeasible. I.e. your computation would run too long to be useful.
The reason for this infeasibility is that the input is so thoroughly "mixed together" in the hash value that it becomes impossible to disentangle it with any less effort than the brute force attack of computing the hash value for all inputs
"why aren't MD5 hash values reversible?" is because "an infinite number of input strings >will generate the same output"
this is the reason that it isn't possible to reverse the hash function (get the same input).
cryptographic hash functions are collision resistant, that means that it's also hard to find another input value that maps to the same output (if your hash function was mod 2 : 134 mod 2 = 0; now you can't get the 134 back from the result, but we can stil find number 2 with the same output value (134 and 2 collide)).
When the input is smaller than the block size, padding is used to fit it to the block size.