WEBVTT

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 Incident Management with the Hive.

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 In this video, we're going to be taking
 a look at incident management,

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 you know, in terms of what it
 means and what it entails.

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 And then we'll be getting an introduction
 to the Hive, which is a quite

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 comprehensive incident management platform,
 you know, at least in this

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 context it is. It can be used
 for a lot more than that.

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 But generally speaking, if you again
 work in a C-set or within a SOC,

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 you'll typically come across one or two
 other incident management platforms.

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 But at the moment, at least in so far,
 my experience is concerned, the

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 Hive, you know, ranks quite high up
 the list in terms of, you know, the

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 incident management platforms that
 you'll typically see deployed.

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 So I thought it would be a very, very
 good idea to introduce you to it

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 so that, you know, when you do, if you
 are looking to become an incident

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 responder, when you do start, you know,
 working as one, you're not going

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 to be, you know, you're going to have
 an understanding of these tools

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 and how to use them.

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 So before we even get into the Hive,
 we need to understand what incident

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 management is. So what
 is incident management?

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 Incident management is the structured
 process of identifying, managing

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 and resolving security incidents in a
 way that minimizes impact, restores

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 normal operations, and
 preserves evidence.

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 It is a call function within the broader
 discipline of incident response.

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 So it's more so as the name suggests
 management of the process of incident

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 response and it sort of entails or
 encompasses, you know, the broader,

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 or I should say, the management aspect
 of the entire incident response

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 process. So transitions from one phase to
 the other, communication, collaboration,

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 the transfer of data in a structured
 way, so on and so forth.

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 So just think of it as that allows
 for the management of the incident

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 response process.

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 So what is the primary goal
 of incident management?

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 Well, it obviously ties back into
 the incident response process.

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 So, you know, detect and respond.

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 So it in terms of the key objectives,
 detect and respond to incidents

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 quickly and efficiently.

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 That's really the primary goal there.

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 Contain the threat before it spreads.

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 So it's essentially aiding the incident
 response process by, you know,

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 addressing detection and response, containment,
 restoration, eradication,

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 etc. But specifically now, if we talk
 about some of the other aspects,

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 you know, to do with management of any
 process, you can see that the other

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 goal is to ensure all actions
 are documented and traceable.

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 So think of it as having a system to
 log activity within each phase of

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 the incident response process.

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 And then of course, learn from incidents
 to improve defenses and response

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 capabilities. So that begs the question,
 what is an incident management

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 platform? Well, an incident management
 platform is a dedicated software

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 solution that enables security teams
 or incident responders to centrally

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 manage, track and coordinate their
 response to cybersecurity incidents

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 in a structured and consistent manner.

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 So it serves as the operational hub during
 a cybersecurity incident, that

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 being where alerts are ingested, cases
 are created, tasks are assigned,

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 progress is tracked and and
 collaboration occurs.

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 So think of it as a hub where all incident
 responders meet, including

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 SOC analysts and anyone else who's part
 of the incident response process

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 or the, you know, CSERT, the incident
 response team or, you know, whatever

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 variation of the team.

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 So this is a central hub where, you
 know, you all sort of come together

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 to, as the paragraph here sort of explains,
 to, you know, essentially

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 view alerts. And then from those alerts,
 you create cases, you then perform

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 the investigation and or response.

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 And you can track progress
 of particular cases.

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 And you can collaborate.

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 So again, this may not make much sense
 right now until you actually see

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 it in person. If you are familiar with
 this, then you know, the benefit

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 of an instant management platform.

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 So what are the core functions of
 an incident management platform?

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 Or at least what should it be able to
 do or what should it offer, ideally?

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 Well, you have obviously alert ingestion.


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 So this is where, you know, this essentially
 involves collection of alerts

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 from various sources like SEEMS, EDRs
 or email reports, and then case

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 management. This is sort of the really
 cool aspect of an incident management

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 platform. So this allows responders
 to convert alerts into structured

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 investigation cases.

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 You have built in investigation
 capabilities.

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 And as a result, you have the ability
 to take a log or an alert and say,

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 I want to create a case based on
 this to investigate it further.

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 And it gives you sort of this isolated
 space to investigate just that

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 alert. You then have task
 assignment and tracking.

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 So this is where you break incidents
 into specific tasks and, you know,

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 assign them to analysts.

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 So, you know, if you have a alert, you
 create a case from the alert, you

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 know, and there's all sorts of categorization
 that happens there in terms

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 of severity, priority, etc.

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 And you then say, for example, you
 know, you create a task that has to

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 do with analysis and you assign it
 to a particular incident responder.

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 And then you can assign, you know, eradication
 or containment, eradication,

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 recovery, all of that good stuff.

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 So essentially, as I said, when we
 talk about project management, for

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 example, but in this case, tailored
 to the incident response process as

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 a whole. So, you know, you break incidents
 into specific tasks and then,

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 you know, with that functionality, you
 have the ability to assign specific

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 tasks related to a specific
 case to a specific analyst.

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 You then have evidence handling.

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 This is also a very, very useful and powerful
 aspect of an instant management

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 platform. And this is, you know, the
 ability to centralize observables.

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 Observables for all intents and purposes
 are IOCs, so indicators of compromise.

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 And in addition to that documentation
 for analysis, and some of these

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 tools, just like the Hive, actually
 have automated analysis built into

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 them. So you can actually perform quick
 analysis or initial analysis of

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 IOCs like hashes, URLs, so on and so
 forth, and actually get to know what

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 you're dealing with relatively quickly.

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 You then have collaboration, which
 is again, very, very important.

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 So, you know, an incident management
 platform should enable multiple team

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 members to work on a case simultaneously
 with full visibility.

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 And now you have a very important aspect
 here, which is audit logging.

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 So you need to have a log of
 activities or actions taken.

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 So, the platform should be able to track
 actions, decisions, and timelines,

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 because within your report, your incident
 response report, you're going

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 to have a timeline of the incident
 as well as your response and tools

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 like the Hive automate this process
 for you, because analysts just need

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 to need to fill in within their log
 that at this time, I did this.

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 And this is when we completed analysis
 or investigation, and then it went

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 to this analyst who handled, you know,
 containment, or, you know, let's

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 say there's further analysis of a,
 you know, a piece of malware, etc.

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 And then you have reporting and metrics.

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 So, you know, that goes without saying,
 you know, good incident management

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 platform should be able to generate
 reports for executives compliance

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 and, of course, said,
 welcome to the Hive.

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 So what is the Hive?

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 This is your first time hearing about it.


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 The Hive, as its name suggests, or
 I should say the word Hive suggests

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 is an open source incident response and
 case management platform designed

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 to help socks, sea certs, and incident
 responders manage and coordinate

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 the response to security incidents in
 a structured and collaborative way.

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 So it gets the name, you
 know, has the word Hive.

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 That's not my mistake.

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 Hive, if you've ever seen a Beehive,
 you'll see that you have a lot of

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 bees working together, you know, all
 on the same thing or the same end

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 goal in mind. So, you know, just
 a bit of a silly tangent there.

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 But, you know, if you're in case you're
 wondering why it's called the

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 Hive, that's why, or at least that's
 my, my understanding of it.

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 In any case, the Hive acts as a centralized
 workspace for handling alerts,

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 tracking investigation tasks, managing
 evidence or observables, as they

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 are called within the Hive platform,
 and, of course, documenting incident

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 response activities.

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 It is designed to streamline and standardize
 incident response workflows,

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 especially in environments with multiple
 analysts or high alert volumes.

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 And, you know, the key features of the
 Hive pretty much mirror the actual

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 features of the, of an instant management
 platform that I listed out in

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 a previous slide.

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 So it has alert ingestion, it has excellent
 case management that converts

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 alerts into structured cases and contains
 tasks, observables, and timelines.

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 You also have task tracking.

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 So, you know, organize the response
 process by creating and assigning

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 investigation tasks.

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 And then the really cool bit of the
 Hive that I personally like is the

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 handling of observables.

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 So you have the ability to
 track IOCs individually.

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 So think of IPs, hashes, and domains.

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 And then you can use Cortex.

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 But before we get to Cortex,
 we have collaboration.

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 So, you know, you have
 multi-user support.

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 You can collaborate on the same case.

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 And you have, you know, full visibility
 into actions and notes.

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 So going back to the observables handling
 and then analysis of the observables

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 that you've identified and logged,
 that's where you have Cortex.

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 I'll actually explain what Cortex is.

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 But this is sort of an optional integration
 created by the same company

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 that, again, created the Hive.

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 It's optional integration for automated
 enrichment, analysis, and response

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 actions. So what this means with Cortex
 integrated into the Hive, it gives

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 you the ability to integrate services for
 enrichment like, or, and correlation,

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 like, for example, URL
 scan as an example.

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 So, with that functionality available,
 if I find an IOC, a URL IOC, I

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 can, you know, create, I can sort of
 create an observable at the URL there

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 or just specify then, and I can utilize
 Cortex to perform an automatic

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 scan of the observable using, again,
 a service like URL scan.

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 And it'll automatically perform
 the enrichment for me.

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 So it actually allows you to automatically
 enrich or analyze at least

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 at a very basic level, the
 observables or IOCs.

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 I'll alternate between the two.

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 They're essentially referring to the same
 thing, not always, but generally.

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 You then have audit logging
 and reporting.

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 Again, the Hive is excellent here because
 it has built-in support for

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 documentation and case reporting
 for compliance and reviews.

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 So let's talk a little this is what
 makes the Hive great, right?

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 So firstly, you know, just based on
 the features of functionality of a

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 good instant management platform, when
 we talk about ingestion, you have

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 the ability to integrate
 the Hive with seem tools.

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 So think of Splunk, Elastic or Elkh Qradar,
 and this allows you to automatically

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 forward alerts into the Hive
 as new cases or alerts.

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 So configure triggers from your seem
 to say that in the event of this

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 for them to the Hive, the Hive
 then catalogs them in a list.

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 And then analysts or responders can
 start performing the triage process

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 usually done by SOCH tier one analyst.

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 And then they sort of escalated
 to the responder.

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 So in the form of a case and subsequent
 tasks, you then have ticketing

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 systems. So you can you can, you know,
 ticketing systems like service

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 now or JIRA. So you can link instant response
 cases with ITSM or engineering

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 workflows. In the case of threat intelligence,
 examples here are missp

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 and open CTI. You can actually ingest
 the latest threat intel and IOCs

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 to enrich observables.

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 So again, this may sound cool right
 now, just wait until you try it out

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 for yourself. Again, if you haven't
 used the Hive before, you then have

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 SOCH or you know, in this particular
 case examples would be Cortex, which

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 is actually an example of security
 orchestration and response.

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 And you also have the Hive
 for Pi right over here.

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 So what this allows you to do is to automate
 enrichment scanning and containment

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 actions. And then you have EDRAV.

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 So examples, CrowdStrike Sentinel 1.

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 So you can again perform the same ingestion
 of alerts or response actions

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 via the Cortex analyzes and then email
 and phishing analysis examples

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 here, iMap, email, passes, scripts, etc.

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 So you can actually create automatically
 create alerts from phishing reports

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 sent to a particular inbox,
 which is really cool.

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 I've done this myself.

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 And then chat operations or chat ops.

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 So in this case, you can actually
 integrate Slack via webbooks.

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 Fantastic. That's typically what you see.


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 But now you'll also see the use of Matamost,
 especially if it's on-prem

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 or self hosted. So this allows you to
 easily notify IR teams of new alerts

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 or case status changes.

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 So you'll typically have a Slack channel
 or the responders will have access

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 to a Slack channel.

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 And these cases or alerts into the
 Hive will automatically, when they

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 get ingested into the Hive, the Hive
 will automatically trigger the alerts

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 on Slack or Matamost.

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 And the responders actually get
 notified wherever they are.

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 So really, really cool stuff there.

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 We then have Cortex, which is again,
 just think of it as an integration,

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 sort of a different component of the
 Hive that is not required to run

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 the Hive, but is absolutely fantastic.

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 And it's always recommended to sort
 of have them paired together.

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 And you'll see why.

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 So what is Cortex, as said, made by
 the same company that develops or

0:15:58.460000 --> 0:15:59.840000
 develop the Hive?

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 Cortex is the Hive's official analysis
 and automation engine.

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 It's a companion application or service,
 I should say, that is used to

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 automate the enrichment of observables,
 also known as IOCs, and perform

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 response actions directly
 from within the Hive.

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 So Cortex acts like the,
 quote unquote, brains.

0:16:20.580000 --> 0:16:24.520000
 And it really is, you'll see why
 behind the Hive's automation.

0:16:24.520000 --> 0:16:28.940000
 What this means is that it gives responders
 instant context without leaving

0:16:28.940000 --> 0:16:31.740000
 the platform, which I already
 alluded to earlier.

0:16:31.740000 --> 0:16:37.380000
 So the fact that I can take a malware,
 you know, a hash or a URL, or any

0:16:37.380000 --> 0:16:43.500000
 type of IOC, and automatically use Cortex
 to analyze, to perform analysis

0:16:43.500000 --> 0:16:47.000000
 and enrichment, you know, I already
 know what I'm dealing with, like,

0:16:47.000000 --> 0:16:48.480000
 relatively quickly.

0:16:48.480000 --> 0:16:53.200000
 And then you can perform additional
 prioritization and triage there.

0:16:53.200000 --> 0:16:57.720000
 But, you know, absolutely
 fantastic service.

0:16:57.720000 --> 0:17:01.800000
 So what are some of the
 capabilities of Cortex?

0:17:01.800000 --> 0:17:04.820000
 Well, you have the ability
 to run analyzes.

0:17:04.820000 --> 0:17:09.500000
 Analyzes are these functionalities
 that allow you to analyze specific

0:17:09.500000 --> 0:17:12.640000
 IOCs, like IPs, URLs, or hashes.

0:17:12.640000 --> 0:17:16.280000
 That's why the word is pluralized here.

0:17:16.280000 --> 0:17:21.580000
 So there are multiple analyzes, one
 for scanning or enriching IPs, the

0:17:21.580000 --> 0:17:26.520000
 other for URLs, the others for hashes,
 and all different types of IOCs

0:17:26.520000 --> 0:17:28.600000
 that you typically encounter.

0:17:28.600000 --> 0:17:32.560000
 So it, you know, allows you to run analyzes
 on observables like, you know,

0:17:32.560000 --> 0:17:36.640000
 scan IPs, URLs, hashes, etc.

0:17:36.640000 --> 0:17:40.060000
 It allows you to perform automated
 actions like checking an IP against

0:17:40.060000 --> 0:17:45.080000
 virus total or querying MISP if you
 have integrated MISP into the Hive,

0:17:45.080000 --> 0:17:48.420000
 which is makes it an absolute powerhouse.


0:17:48.420000 --> 0:18:01.660000
 So you can actually query
 MISP for set it up right.

0:18:01.660000 --> 0:18:05.800000
 I mean, you're, you're, you're shedding
 or cutting down, you're, you're

0:18:05.800000 --> 0:18:08.740000
 making the operation so
 much more efficient.

0:18:08.740000 --> 0:18:12.500000
 And, you know, as we'll progress not
 just with this course, but other

0:18:12.500000 --> 0:18:16.820000
 courses within this learning path,
 you'll actually see what this ends

0:18:16.820000 --> 0:18:22.320000
 up looking like, in any case, continuing
 on, it also allows it also uses

0:18:22.320000 --> 0:18:24.940000
 responders to take real world actions.

0:18:24.940000 --> 0:18:31.440000
 So think of it as something similar
 to Wazoo, Wazoo was, depending on

0:18:31.440000 --> 0:18:36.000000
 what you want to call it, the Wazoo seem
 or Wazoo seem, there's something

0:18:36.000000 --> 0:18:39.140000
 called active response or feature called
 active response that allows you

0:18:39.140000 --> 0:18:45.160000
 to define rules, you know, to allow
 you to define rules for response.

0:18:45.160000 --> 0:18:50.620000
 So if a particular condition is met,
 then there's an automated action

0:18:50.620000 --> 0:18:52.520000
 that's taking. So active response.

0:18:52.520000 --> 0:18:58.240000
 So let's say you configure rule that
 if there's 10 failed attempts to

0:18:58.240000 --> 0:19:03.560000
 authenticate, you know, via SSH on a particular
 system, then do the following.

0:19:03.560000 --> 0:19:08.280000
 But in any case, you know, users use
 responders to take real world actions

0:19:08.280000 --> 0:19:13.800000
 like block an IP on a particular
 firewall or notify a system.

0:19:13.800000 --> 0:19:19.000000
 So some of the common cortex analyzes
 our virus total, the standard stuff

0:19:19.000000 --> 0:19:23.640000
 you'd expect when we talk about our
 IOCs or analyzing IOCs, right?

0:19:23.640000 --> 0:19:31.320000
 So virus total URL house abuse IPDP
 sorry, show Dan, MISP, who is our

0:19:31.320000 --> 0:19:35.100000
 DAP and senses, these are just, you
 know, some of the more popular ones.

0:19:35.100000 --> 0:19:39.340000
 Obviously, virus total is a game changer,
 especially if you have a license

0:19:39.340000 --> 0:19:42.200000
 and you integrate it, great stuff.

0:19:42.200000 --> 0:19:47.100000
 So before we actually end this video
 and we'll get into using the Hive

0:19:47.100000 --> 0:19:51.180000
 in the next video, there's some very
 important terminology that you need

0:19:51.180000 --> 0:19:54.580000
 to be aware of. I've sort of mentioned
 them, you know, throughout this

0:19:54.580000 --> 0:19:59.420000
 video. But firstly, we have an alert
 now this is the same alert that you

0:19:59.420000 --> 0:20:05.940000
 know, this is alert means the same
 thing within the Hive as it does in

0:20:05.940000 --> 0:20:11.440000
 a seem. So in this case, an alert is
 a security relevant notification

0:20:11.440000 --> 0:20:16.760000
 from a seem or an analyst or a tool
 that you've integrated that may be

0:20:16.760000 --> 0:20:20.080000
 escalated into an incident case.

0:20:20.080000 --> 0:20:22.620000
 So that begs the question,
 what is a case?

0:20:22.620000 --> 0:20:27.480000
 A case is a formal incident investigation
 that contains tasks, observables

0:20:27.480000 --> 0:20:33.380000
 or IOCs, tags for categorization, severity
 levels and, you know, analyst

0:20:33.380000 --> 0:20:35.760000
 comments or documentation.

0:20:35.760000 --> 0:20:37.560000
 You then have a tasks.

0:20:37.560000 --> 0:20:40.900000
 So I've actually organized
 this list hierarchically.

0:20:40.900000 --> 0:20:45.960000
 So you have an alert, the alert goes
 and can become a case if it merits

0:20:45.960000 --> 0:20:49.940000
 it. When you have a case, you can
 create a task under that case.

0:20:49.940000 --> 0:20:53.540000
 So a task is a step or action required
 during the handling of a case.

0:20:53.540000 --> 0:20:58.300000
 For example, collect logs or analyze
 malware or analyze this IOC.

0:20:58.300000 --> 0:20:59.700000
 What is an observable?

0:20:59.700000 --> 0:21:04.660000
 An observable is any indicator that
 can be analyzed or enriched.

0:21:04.660000 --> 0:21:09.880000
 So think of this, you know, file ash,
 IP domain, email address, just an

0:21:09.880000 --> 0:21:15.340000
 IOC. But it's a bit wider than that or
 broader than that because not every

0:21:15.340000 --> 0:21:18.740000
 observable would be an indicator
 of compromise.

0:21:18.740000 --> 0:21:23.140000
 So, you know, depending on where you're
 at, you may just want to know

0:21:23.140000 --> 0:21:28.240000
 to add or track specific observables
 that you think might be related to

0:21:28.240000 --> 0:21:33.140000
 the compromise or might be an indicator
 of compromise, but not yet.

0:21:33.140000 --> 0:21:34.040000
 Or you're not too sure.

0:21:34.040000 --> 0:21:37.140000
 So it actually allows for you to specify
 that, you know, you've confirmed

0:21:37.140000 --> 0:21:40.720000
 this observable as an IOC.

0:21:40.720000 --> 0:21:44.740000
 In any case, you then have the tag,
 which is just a custom label applied

0:21:44.740000 --> 0:21:48.360000
 to cases or observables for
 grouping and filtering.

0:21:48.360000 --> 0:21:51.420000
 So you can actually, this is very important
 because if you have good tag

0:21:51.420000 --> 0:21:56.620000
 set up, you can easily find stuff, especially
 ones that, you know, tasks,

0:21:56.620000 --> 0:22:06.120000
 sorry, cases that from the get go, you
 sort of define the tags that will

0:22:06.120000 --> 0:22:11.880000
 be used. But then we have some other
 terminology that is quite unique

0:22:11.880000 --> 0:22:18.900000
 to the Hive, the first of which is
 has to do with creating cases, but

0:22:18.900000 --> 0:22:22.420000
 more specifically tasks and observables.

0:22:22.420000 --> 0:22:26.660000
 So when you're creating a task or observable
 within the Hive, you'll typically

0:22:26.660000 --> 0:22:30.160000
 see a field called TLP.

0:22:30.160000 --> 0:22:35.400000
 All right. This is an abbreviation
 of traffic light protocol.

0:22:35.400000 --> 0:22:36.920000
 So what is this?

0:22:36.920000 --> 0:22:40.680000
 Well, TLP is a standard classification
 scheme that's used to identify

0:22:40.680000 --> 0:22:44.760000
 that's used to indicate how sensitive
 information is and how it can be

0:22:44.760000 --> 0:22:49.940000
 shared. So, because of the collaborative
 share shared nature of an instant

0:22:49.940000 --> 0:22:52.700000
 management platform, the fact that,
 you know, you're going to be sharing

0:22:52.700000 --> 0:22:57.300000
 info with different analysts and among
 yourselves and all of this, TLP

0:22:57.300000 --> 0:23:01.980000
 is very important because as the description
 here suggests, it allows

0:23:01.980000 --> 0:23:07.340000
 you to indicate how sensitive information
 within a case task or observable

0:23:07.340000 --> 0:23:10.440000
 is and how it can be shared.

0:23:10.440000 --> 0:23:14.960000
 So, if you set the TLP level for a
 task, let's say to read, then that

0:23:14.960000 --> 0:23:20.300000
 means it's highly sensitive and it's
 for named recipients only, no further

0:23:20.300000 --> 0:23:22.520000
 sharing, very important.

0:23:22.520000 --> 0:23:26.060000
 You then have TLP Amber, which means limited
 sharing within the organization

0:23:26.060000 --> 0:23:30.840000
 or community. TLP green can be shared
 within the cybersecurity community

0:23:30.840000 --> 0:23:33.060000
 and then TLP white public.

0:23:33.060000 --> 0:23:34.840000
 So no restrictions on distribution.

0:23:34.840000 --> 0:23:46.340000
 This is very important because it tells
 you, you know, whether or not

0:23:46.340000 --> 0:23:49.680000
 you can share stuff, that you'll see
 when creating a task, a case task

0:23:49.680000 --> 0:23:55.340000
 or observable. And that is PAP or PAP, which
 is an abbreviation for permissible

0:23:55.340000 --> 0:23:57.560000
 actions protocol.

0:23:57.560000 --> 0:24:02.440000
 So PAP is a classification system used
 to define how information may be

0:24:02.440000 --> 0:24:06.960000
 used rather than how it may be shared,
 which is what TLP governs.

0:24:06.960000 --> 0:24:10.980000
 So you have the following PAP level,
 so white, green, amber, red.

0:24:10.980000 --> 0:24:15.320000
 So white means the information can be used
 freely, including for attribution,

0:24:15.320000 --> 0:24:17.500000
 enforcement or public disclosure.

0:24:17.500000 --> 0:24:21.700000
 Green means the information may be used
 within the organization or community,

0:24:21.700000 --> 0:24:26.320000
 including for protective actions,
 but not publicly amber.

0:24:26.320000 --> 0:24:31.480000
 The information is more sensitive and
 may be used internally, but not

0:24:31.480000 --> 0:24:35.040000
 disclosed externally or used for
 attribution without permission.

0:24:35.040000 --> 0:24:38.540000
 And then PAP read, the information
 is highly sensitive and should not

0:24:38.540000 --> 0:24:42.420000
 be used for enforcement, attribution
 or public exposure typically used

0:24:42.420000 --> 0:24:44.120000
 for situational awareness only.

0:24:44.120000 --> 0:24:48.360000
 Now, what you'll typically see, because
 this may be confusing to you as

0:24:48.360000 --> 0:24:52.240000
 to why would you want to
 make it freely available.

0:24:52.240000 --> 0:24:58.540000
 Generally speaking, the other labels
 sort of come into play after your

0:24:58.540000 --> 0:25:00.480000
 sort of performed analysis.

0:25:00.480000 --> 0:25:06.620000
 So whenever you'll be interacting with
 a case within the hive, and let's

0:25:06.620000 --> 0:25:12.680000
 say an analyst has assigned a particular
 task within a case to you to

0:25:12.680000 --> 0:25:20.000000
 perform, let's say, initial analysis
 of an incident, the PAP and let's

0:25:20.000000 --> 0:25:24.780000
 start off with the TLP level, that
 will typically be labeled as red or

0:25:24.780000 --> 0:25:32.340000
 amber. But generally, red, especially
 during the actual investigation

0:25:32.340000 --> 0:25:37.200000
 process, or when the task
 is still in progress.

0:25:37.200000 --> 0:25:40.160000
 And in the case of PAP, that
 will again be set to red.

0:25:40.160000 --> 0:25:44.880000
 So that again, that's not always the
 case, but it generally means that,

0:25:44.880000 --> 0:25:50.180000
 hey, don't share this with anyone
 yet for your eyes only.

0:25:50.180000 --> 0:25:56.360000
 Of course, some organizations have defined
 their own scheme for both PAP

0:25:56.360000 --> 0:26:01.540000
 and TLP. So I'll just be
 following what I know.

0:26:01.540000 --> 0:26:04.440000
 And of course, you can
 research this more.

0:26:04.440000 --> 0:26:07.580000
 But with that being said, that's
 going to be it for this video.

0:26:07.580000 --> 0:26:10.020000
 And I'll be seeing you in the next video.


