Hear you and welcome back now into this week, we will be discussing about one of the interesting security
services, which is missing.
So nowadays you will see a trend where a lot of organizations are completely migrating their data from
their on premise storage devices to a single cloud storage services like S3.
And in fact, even in one of the organization that I was working with, we used to have hundreds of
terabytes of data.
It is 311.
Now, when you have terabytes of data in S3 and it's someone has uploaded, let's say, access key,
a secret key in a text file in the S3 service.
How will you quickly identify it?
Because it is a little difficult to search data bits of data to see if any data has been accidentally
uploaded.
So this is where the mercy comes in.
So at a high level overview, one of the core feature of Messi is to go ahead and search and look for
the sensitive data that is stored in the S3 service.
Now what is the sensitive data?
It can be the bad data.
It can be certain SSL private keys that you have.
It can be unreadable success, secret keys, etc. So this is one of the primary features.
Why me see the extensively used along with that message will also go ahead and give you various findings
related to the policies, the budget policies and similar areas.
So let's do one thing less directly jumping to the more you understand this in a better way.
So currently, I'm within the messy dashboard and within year, you see, it basically gives in or a
view related to the buckets if there are any publicly accessible bucket or may be publicly readable
buckets, etc. It gives you details related to whether encryption is being used and whether there is
sharing that is enabled at the market level.
This is fine.
However, the main important thing that organizations use me for is to look for sensitive data.
Now, if you look into your top finding tapes, you see that sensitive data S3 object credentials.
You also had media, so they're finding tapes.
But let's go ahead and explore what this is all about and also know that it also shows you in which
S3 bucket the findings were discovered.
Now, if you're quickly looking to the credentials alert here, let's open this up.
So if you'll observe this one?
Let me go back.
So within.
If we look into the finding Typekit states sensitive data S3 object credentials and there is also vector.
It basically gives you the data bucket location, which is they must be Project Access Open Secret zero
2.0.
So this is the file under the bucket name where the sensitive credentials have been detected.
So let's quickly identify this so-called entertainment industry console and we have our demo ACB bucket
available and within.
You'll see that there is a file called Access Secret Zero 2.0.
And this is the file that the MSI has been referencing to within the alert.
So if you quickly open this file, let me download it.
Let me open it.
And within a year, you see you have access and a secret key that is available.
So the messy service will basically go ahead and scan the files to see if sensitive data or bad data
is available or not.
So let's go back to the messy service here and if we look into various policy findings.
So again, as we're discussing, finding the sensitive data is one of the primary use cases by organizations
using me extensively.
However, apart from that, it can also give you an alert based on various other policy findings like
S3 bucket public, that application related findings, the findings related to encryption and so on.
Now, if you're wondering on what is the exact files, that means he can look into.
So let's quickly look into their documentation here.
So basically, they have given the exact details associated with various things that it can capture.
So you have database access security that it says is related private key.
If you go don't, it basically shows your bank account numbers.
So basically, this comes under the dated April financial information.
It can look into the credit card expiration, credit card number related data.
And if you go back down again, you have various keywords for bank account numbers, various viability
data.
It can capture a huge amount of data it can capture depending upon your requirement.
So in case if you want to wonder if the data that you're looking for will be captured in methey, you
can look into the documentation as well.
Now what happens if some of the data types are not captured at only sea level?
So in such cases, you can also go ahead and create your own regs.
Let me quickly show you.
So you can create your own regular expression to identify a specific data that you do not want to be
uploaded in a state and based on their regular expressions that you write, the message will evaluate
the files in history if it finds the file that matches your regular expression.
Then again, you will see an alert grid.
So this is the basics about the messy service, and with this will conclude today's video.