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Passwords are one of the most common pieces of data that we have to store for users and one of the most dangerous to lose control of.
While a salt, as I suggested in the video, is definitely your first step, there's much, much more to safely storing passwords. This article provides a great visual for this.
I've included links to some popular hashing libraries, divided up by language. This is not an exhaustive list.
Python
Ruby
Node.js
.NET
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[MUSIC]
0:00
We've covered a lot of theory and
places to be concerned with.
0:04
So we should start to
look at some solutions or
0:07
approaches to better security.
0:09
Before we get into that though let
me make one thing absolutely clear,
0:11
you should use established measures,
tools, libraries, and services.
0:14
It's really fun to play around with
making your own algorithms and
0:18
security techniques.
0:20
But these, especially when kept secret and
0:21
internal, are often much more vulnerable
than the current industry standard ones.
0:23
We want you to be as safe and
secure as possible.
0:27
So please stick to industry
recommended tools, okay, cool.
0:29
Let's start with one of the things that
almost every security system uses,
0:33
passwords.
0:36
We need to hash passwords because despite
our best warnings, users will come up with
0:37
one decent password and use it at site
after site, application after application.
0:41
And then,
when bobsfishingspots.com gets hacked,
0:46
now the attackers can target your site or
my site and hope for password overlaps.
0:48
We however, don't want to provide hackers
with a fresh supply of passwords and
0:53
account details.
0:56
So we'll hash all
the passwords that we store.
0:57
Just a note before we
dive into a screen cast.
1:00
I'll be using languages that
I am comfortable with, but
1:02
these are only illustrations.
1:04
Anything I'm doing in Python or
JavaScript or
1:05
any other language can be done in
your language or framework of choice.
1:07
Don't think that you have to use exactly
the language and code that I'm using.
1:11
All right, let's get started.
1:14
Python has a handy built-in
tool named hashlib,
1:17
I'll use that to explore
a couple of hashing algorithms.
1:20
Then we'll looking at salting our hashes,
and finally, argon two,
1:23
which won the password
hashing competition in 2015.
1:27
Hashing algorithms come in all shapes and
sizes though, so
1:30
be sure to find the one that's best for
your use case.
1:32
First, let's take a look at
a bad algorithm to use, MD5.
1:36
Hashes return a bunch of bytes, which we
can view as either straight bytes, or
1:39
that we can turn into hexadecimal.
1:43
Hexadecimal is a little easier to read and
1:45
it's more likely what you'd store in
a database so I'll be focusing on them.
1:47
But I wanna show you both of these for
the first couple of hashes.
1:50
So let's do hashlib.md5 and
we have to send it bytes.
1:54
So, we're gonna send it bytes for
the word Treehouse and
1:58
then let's looks at the digest.
2:02
And these are just the bytes
that come back out of it.
2:04
So, bunch of bytes.
2:06
If we do the same code and
we use hexdigest, then we will get
2:08
the hexadecimal output which you can
see here is the 65492 and so on string.
2:12
There's not a lot to see here.
2:18
But it was definitely fast to execute,
right?
2:19
That was one of the things that
md5 was very well known for.
2:21
Let's try a stronger one.
2:24
Must do hashlib.sha256,
2:25
again we gonna send it some bytes,
we'll send Treehouse.
2:29
Now look at the digest, print along
digest and looks like a be hex.
2:34
So there's the head.
You could see it's much longer, right?
2:40
It's a much bigger hash output.
2:43
This was actually once considered a very
strong algorithm, but it's compromised
2:45
now to collisions being possible
within a practical amount of time.
2:49
That's how security goes.
2:53
Let's look at a currently
secure algorithm.
2:54
And this one is also from
the shar s-h-a family, and
2:56
is could by the National Institute
of Standards and Technology or NITH.
2:59
This algorithm's output is a little
different though in that it has a variable
3:04
amount of it.
3:07
We can control the amount of overall
security that goes into creating the hash
3:08
and the amount of hash
data that comes out.
3:11
So lets do hashlib.shake_128
we're gonna again send it
3:13
Treehouse and let's ask for
a hexdigest that is 20 bytes long.
3:20
There we go.
3:27
The 128 there is gonna
be overall security and
3:28
this affects how the algorithm
manipulates the data that's fed into it.
3:30
In the hexdigest, you can see that
I ask for 20 bytes of data back.
3:34
Now, regardless of the hash that you use,
it's very important to salt them.
3:38
Result is a little bit of extra
random data that your task to
3:41
the thing that you're salting.
3:44
Some people use the time stamp of
when you signed up, your username or
3:46
some other bit of known data.
3:49
I'm going to use a randomly generated
string from Python UUID library,
3:51
which means I need to import that.
3:54
And this can generate
universally unique identifiers.
3:59
So let's create a couple
of variables here first.
4:03
So we'll create a variable
of the string Treehouse.
4:05
We'll make a salt.
4:10
And then we'll do hashlib.shake_128.
4:13
And then we will put in
our ( salt+password.
4:20
And the we will call
hexdigest (40) on that.
4:25
And we get this nice big long harsh.
4:30
So, there's a thing I can save in my data,
it's a good thing to save.
4:34
Except, wait a minute, I wouldn't have
any way of finding what the salt was.
4:37
So I can never verify this harsh.
4:42
So to fix that, I'm going to append
the salt on to the end of the hash.
4:44
So I do exactly like we did before, and
4:49
then I would add a : and
then I would + the salt.
4:52
So now we get a big long hash,
we get a : right over here,
4:57
and then we get our salt at the end here.
5:02
Excellent.
5:05
Now, I need to decode it,
I'll just reverse that process.
5:06
Since hexidecimal doesn't include the :,
5:09
we know that it can be part of
the hash password, or the salt.
5:11
That means that we can chop
off the bit after the :.
5:14
Add that to the password
that the user gives us,
5:17
hash the whole thing with shake eight,
and then see if the two match.
5:19
So why do we want to salt things?
5:23
Aren't we making it easier to break the
hash by including the salt in plain text?
5:25
Adding a salt makes it much
harder to use precomputed attacks
5:29
like lists of prehashed words and
phrases against your hashes.
5:33
You should always salt your hashes.
5:37
If you're worried about attackers
being able to see your salt you
5:39
could always use another piece of data
that are calculated like sign up date.
5:42
Where users applied,
like an email address as the salt.
5:45
Before we wrap up,
5:48
I wanna look at Argon2, which one
the last password hashing competition.
5:49
Argon2 does something,
5:53
too, that many of the password
focused hashing algorithms do.
5:54
Let me use it, and
I'll show you what this is.
5:57
So I'll say from argon2
import PasswordHasher.
6:01
And then I will hash ("Treehouse").
6:10
And we get back a big long string.
6:15
See how it has the $argon2i,
here at the beginning.
6:19
That tells us that it was hashed
using the argon2i algorithm.
6:24
The other dollar sign separated
values that are in here,
6:28
tell us more about how
the hash was generated.
6:31
And finally, after this last dollar sign,
is the hash itself.
6:34
You might think that this is less secure,
6:37
since then a tag would be able
to simulate your hashing set up.
6:39
But due to how Argon2 works, where it
stresses the process and fills up memory,
6:42
this was what matters much.
6:46
All of this things here like the m and the
t and the p, those are settings you can
6:47
tweak to determine how much memory and
processor time we're hashing uses.
6:52
This has a major benefit because when
you save your user's password into your
6:57
database, you know how you half them.
7:01
You can use that to
hash them next time and
7:04
you can use that to upgrade hashes in
the future, pretty clever Argon2 too.
7:07
So remember use a hashing mechanism
that protects the infotax from GP use.
7:12
Uses of time and memory against
an attacker and avoid collisions.
7:17
It's also a good idea to be sure and keep
track of the algorithm that you used for
7:20
hashing, so you can upgrade stored
hashes as a tax and algorithms change.
7:23
I've talked about it before but
it's important so
7:28
I'm gonna talk about it again.
7:29
Systems like Argon2 are great to use for
specific use cases like passwords.
7:31
For other hashing situations though there
are usually existing tools in place
7:35
that are more specialized and
appropriate for the situation.
7:39
Things like checking
the contents of a file,
7:42
validating the origin of a message,
or fingerprinting a user or
7:44
a machine have existing solutions
that you should investigate.
7:46
Okay, now that we have things safely
stored in an unreadable format,
7:49
what would be some of our weak courses for
encrypting data to get it back?
7:52
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