WEBVTT

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So, hi everybody. I'm Julia. This is David. We're going to talk about backbain, simplify

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consensus on Android forensics. And we are part of an organization that's called Observatory

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on Existono. It's an Italian nonprofit that started running tournaments, mostly to our

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ex-innotes, because we had legal troubles doing that as individuals. And so, we associated

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those, have a bit more rights. And we are all volunteers at the moment. And we expanded

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our original scope. And also, helping activists was being became also surveillance and doing

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general research on surveillance tools and equipment from various users. And we started

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in our clubs and in our organized spaces and those are still our communities and the people

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we try to add and with whom we try to work with. And this is our tour data center. It's a beautiful

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basement in Italy, so it's our headquarters. And let's talk about Spieber. So, when somebody

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thinks Spieber and is not very deep into it, they generally think all the big scandals set up

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and through Europe and not only Europe, they might think of Pegasus, of an esogrup, of predator,

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and of other many Israeli companies. So, the point is that in the last five years, a lot of companies

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have started in Spain in Italy. And as exploit research hub and spyware development tabs,

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mostly because of the good climate, nice food, tax cuts, and a lot of research in Italy wanted

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to relocate somewhere that wasn't possibly cypress or Israel. And Barcelona is one of the main places

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as most people, I know. And Israel is still leading the exploit development, especially for

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insects, like cyberite and similar, and they test on Palestinians all the time. That's also why it's

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developed on their side. And mostly, your countries have had a spyware scandal at a point in time,

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Italy had it recently, but we know about Greece. We know about Spain with a cattle and gated,

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regret the Pegasus committee. We know about Serbia recently, we know about Bonan, Latvia,

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if one search, they can probably find one, and it's very likely that the places they're

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unlisted there, it's just that we don't know what they're doing. It's not like they're exempt from this.

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And generally doing attribution of was infected boom for which reason is extremely difficult,

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and the burden of the proof is almost always on the victims. And even if you can prove that there

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was a spyware, finding out what will be sent it is extremely difficult. So, you can guess it stays

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surveillance, but you just almost can never confirm it unless the other party confirm it,

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which is kind of annoying because justice should work in a way that not everything should be on the

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victims. And when we talk about spyware, I started from the leftmost column, and discussing about the

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very famous, very sophisticated, very costly ones, including NSW group, Dataflow, which is an Italian

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company. And mostly, when we think of this spyware, we think of zero click exploits or one click

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exploits plus a little bit of social engineering to a view, a lot of previews, or a document,

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or click a link. And generally, this highly sophisticated spyware have agents that run in memory,

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maybe in kernel space, are live persistence. And so, they're really difficult to catch from user space,

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unless you try to break or root your device. While there's a plethora of, let's say, less expensive,

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less sophisticated spyware that are used all the time in so many more circumstances.

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And, really, in the lack of sophistication and in the lack of the availability of very expensive

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exploit chains, they've to use different tactics. And so, for instance, we've seen spyware,

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bar, RCS, ornamental, the general use some type of social engineering for installation,

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and then maybe they use either end-day bugs or non-bugs for previous collections, or for maybe

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bypassing system prompts, or doing basic kind of basic attacks, so that they require some

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social engineering, but also they have some technical sophistication to pass through that.

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But, generally, this kind of spyware, are ready, more persistence on this, maybe they

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start an application, maybe they become device admin, so they're a bit more catchable,

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and they're still generally used, I guess, a significant amount of activities, journalists,

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and this is then depending on the case. And then we have on the right-most columns,

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the cheapest ones, where basically they just can be installed via social engineering,

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and while this seems very unlikely, because we're all taking care of people, they are

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totally very used, and they have a high degree of efficiency, because they can start,

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especially if you're in a position of power, you can start by doing the basics,

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social engineering, but then you can add extra tools. For instance, you can see the phone,

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unlock it using a forensic tool like cyber, 10 instance spyware, and they return it to the victim.

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And clearly, that doesn't require exploits on the spyware side, and clearly still has a high degree

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of efficiency, that's what's been seen in Serbia and in other countries. And there's also

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other things that we're going to talk about, where I discuss social engineering plus infrastructure

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attacks that are very widely used in Italy to deploy spyware against activists. And there's also

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a sub-genre of all these things that are spyware that don't employ any exploit, but they're still

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widely used for gender violence, so for stocking purposes, for subvening employees, and these

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tools are generally very cheap, like you can buy them. Maybe a while ago, you could still find

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these tools on the Play Store, now you can't probably anymore unless special circumstances,

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but they're still very widely available and used. And as we see, there's been

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evidence of cyber use to unlock phones, and then it's a spyware. This is from another Italian

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collective that's been tracking spyware locus spyware infection via social engineering,

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and what they found out is that what happens in Italy at the social engineering,

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plus infrastructure level, is the victim. We'll have a service that they need cut off,

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so for instance, the data on their sim, or their phone calls don't work anymore. And then

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basically what they can do is they can only call the support number of the RSP. The RSP will have

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a social engineering agent, who knows, who that is, and then they will basically say,

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you need to install these special support app so that you can get your data traffic back.

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And that works very well, because you need the service, and like the only way to get back

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your services to start the spyware, and that will guide you through a design, the play product,

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like all the security features, like it's an alpha-nour, or social engineering support code,

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that they do, and people install the spyware, and it works. And it's also extremely cheap,

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because the cost per license of the staff can be as well as a standard per day per user.

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And so, where we've focused on consensual forensic on mobile. It's because, well, on desktop,

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we have focused for a long time on trying to do live detection of malware. Actually,

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we cannot really look system calls, or we can really, I'm privileged and caught threats, like

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data, Ily privileged level. And so, from user space, we are very limited of the things we can do,

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and obviously there's good reason for that. And so, most civil society has worked into two branches,

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to catch this kind of threats. One is the forensic methodology, which we're going to talk about,

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and the other is network-based detection from Pirog to Sweet, where basically you have

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at least a false name and some other network you see.

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Yeah, it says,

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get a signal.

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Maybe I can...

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Instagram, and I don't even published an Instagram account.

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as the painting

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let's go

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I think that's what this one is supposed to.

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It's like a cell delay in the mouse.

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It's a cell delay in the mouse.

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This is what I would like to ask you.

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Okay.

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I'll wait.

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Let's take a look.

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No.

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That's all.

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Thank you.

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Thank you.

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No.

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I don't know what's going on here.

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No.

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No.

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No.

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No.

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No.

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No.

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No.

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No.

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No.

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No.

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No.

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No.

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No.

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No.

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No.

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No.

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No.

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I don't like it.

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Okay.

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Okay.

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Sorry for the introduction.

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And so, as I was saying, we've been focused on forensic methodology

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and network-based detection,

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but they have shortcomings,

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especially at the moment,

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where basically you can almost only catch

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on the known spyware, like cause you need to have a ready-day

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OCS or not the OCS names or as some indicators,

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you know, like something has happened.

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And there's a bit of research of running,

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starting and dynamic analysis on the phone itself,

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but like that's very battery consuming, it's pretty difficult to do.

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So there's a lot of complexity if you want to have something

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that respects the privacy of the user, doesn't do data collection,

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does it do data correlation,

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but also you want to catch things,

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but then you're limited only to non-stuff.

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And as I was saying before,

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what we were going to focus is the threads that I've sorted,

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I've used it, have apps because we can't really catch

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from user space or it's extremely difficult to catch

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from user space, they're very sophisticated threads.

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And it's also not like our target users,

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just because we know that there's so many of the lower

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sophistication threads just affects a lot of people

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and generally they have also less assistance for civil society.

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And so what we're going to focus on is consensual

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forensic methodology.

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And what happens at the moment when an activist or a journalist

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is suspected to have been infected,

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is that they have to look for a civil society organization

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that's likely going to help them,

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it depends on the case and on their organization,

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and also on geography, but these are so many issues.

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Because the first thing is that if the person who has the

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infection is in contact with the nation,

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they likely either need to have somebody come to them,

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and some come online tools, do some manual analysis,

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check the results and like explain them what's happening,

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or there's to be guided to this process through a

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multiple part, which is again pretty difficult,

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or the victim has actually to ship their device,

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to one of these support organizations,

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which again is border someplace,

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you basically send somebody or your data via post,

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like there's a bunch of complexities.

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And obviously we are great for all the organization

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we've been doing this at this point at this moment.

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And we also do this in Italy for people when you don't

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have a fact, but it's something that's really difficult

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to scale just because you need a person,

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to provide the support.

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And some of these are volunteer based,

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some employees volunteer and employees,

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we are all volunteer so it's a bit complicated.

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So we have seen a consensus,

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forensic methodology, but what to do you use

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if you're at a technician and want to analyze a phone

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that you think it is infected by spyware

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and there is a spyware abuse.

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So MVT is the factors standard tool for consensus mode

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that mobile forensic, it was developed by

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Amnesty Tech Lab that is one of the civil society

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organization that performed this type of analysis.

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And it was developed in 2021

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in the context of the Pegasus project investigation.

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And if you don't know,

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the Pegasus investigation was a spyware scandal

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that targeted the Catalan government

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and all the members of the Catalan government

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were like surveilled with the Pegasus spyware

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and these sparked a lot of problems

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in all of Europe because of these.

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And the MVT tool, it is developed in Python as a command line tool

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so it is not really usable for and user.

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You need to know what you are doing.

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It's difficult to install.

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You have to do like pee,

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etc. but for the end user,

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it's not really a common thing.

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And also interpreting the results

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requires some technical expertise

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that are a lot of scary warning

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that a user like maybe don't understand.

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And so you need a technical person

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to run this type of tool.

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And it works by connecting the target phone via USB

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enabling the developer tool on the phone,

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enabling ADB, Android bug bridge.

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And then you can extract the relevant artifact

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from the phone and analyze it on the PC.

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But as I said,

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it is really difficult to use for an end user

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so Android QuF was developed

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to make the acquisition process easier for the victims.

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And Android QuF is more user-friendly than MVT

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is basically returning along and distributed

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as a single binary.

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You can download it like a victim.

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You can download it, run it on their PC

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and then get an export that is basically MVT compatible

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in a single click.

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And these exports can then be shared

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with our technical team.

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And MVT is used to analyze it by like an expert.

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This just streamline the acquisition process

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but the analysis is still, let's say, difficult.

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So we came up with an idea that is bugbing

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and our goals were to first of all create

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a friendly user-friendly tools that can be used by everyone

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because these will improve the civil society

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tracking intelligence by making analysis widespread.

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So if more people that think they had

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a spyware infection abuse,

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they can analyze their phone

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then we can catch abuse sooner.

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And this kind of position can be

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so actively scan with updated indicators of compromise

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because you can acquire now,

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keep the acquisition on the phone

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and then scan later if new indicator of compromise

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are published or released.

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And another goal is to remain

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for compatible with other open source tools

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such as MVT and Android QF.

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But mostly perform acquisition

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and analysis locally on the target device.

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It's our main goal.

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How can we do it by using wireless USB

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debugging?

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And basically it works like USB

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but the TCP via Wi-Fi.

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And basically you need to enable

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this option in the development tools

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and pair the D-Mon and the app

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with the pairing code or QR code.

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It is available since Android 11,

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these features so we are only targeting

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let's say newer devices.

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And it grants the same privileges as MVT

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and so this is a good news

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because we can do acquisition

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that are one to one the same as MVT.

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And ironically, this is the same mechanism

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that low-end spyware use to escalate their privileges.

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So they automate this part to obtain

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the pairing with the D-B process

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and then obtain higher privileges on the phone.

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So this is a little schema of bug vein

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on the left on the right.

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We can see the artifacts that gets collected.

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So SMS, it's a big thing

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because most of the entry points

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for low-end spyware are SMS.

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You get an SMS saying, yeah, please don't load this application

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to get your internet connection back

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and a lot of URLs are IOCs for infection.

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Another interesting part is that IOCs are updated.

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Let's say every day there is a check

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if there are new IOCs if you don't load it into use.

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And another thing is that the user is reported

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with some warnings and based on the warning level,

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the user can decide to encrypt their acquisition

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and share it with organization

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that can analyze it further

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and understand if there was indeed a spyware or spyware abuse.

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Or otherwise, if there are no big warnings

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they can just encrypt the acquisition

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and scan it in the next IOC update.

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And here are some screenshots

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of the beta version that we are starting to release.

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Here is an example acquisition

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that runs some modules to acquire artifacts.

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Then in the center there is an example

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of an acquisition details with some findings.

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Here are two scan of the same acquisition

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and then in the last one we have the detail

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of what are the warnings in that specific scan.

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What are the limitations of this approach?

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The first one is that can only catch known threats

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as we have saved before.

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And techtactors can also scrape public IOCs

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and update their obfuscation

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to make it harder for this tool

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to detect such spyware.

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And also another big thing is that

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we are using artifacts on the device

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to add evidence in case of seizures.

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So maybe you have a lot of acquisition

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that you performed on your device

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that you want to keep to scan later

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but if your phone gets seized

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and then they use subbright for example

20:12.840 --> 20:14.840
to unlock it then they can get

20:14.840 --> 20:18.840
all this kind of evidence from the past.

20:18.840 --> 20:20.840
What it is currently on the developed

20:20.840 --> 20:23.840
in our application we want to secure

20:23.840 --> 20:26.840
the app by encrypting the local data

20:26.840 --> 20:30.840
so the local acquisition so it is encrypted

20:30.840 --> 20:34.840
and not available at a later time

20:34.840 --> 20:40.840
for people outside of the user itself.

20:40.840 --> 20:43.840
We are building and are reproducible builds

20:43.840 --> 20:46.840
infrastructure and we plan to release the app

20:46.840 --> 20:50.840
also on f-droid so that the source code

20:50.840 --> 20:54.840
is public and everybody can vet the source code

20:54.840 --> 21:00.840
and see that the app that is downloaded is really safe.

21:00.840 --> 21:02.840
And we want to improve all

21:02.840 --> 21:04.840
so false positive detection and prevention

21:04.840 --> 21:07.840
that is a problem with the MVT

21:07.840 --> 21:10.840
because technical people can just

21:10.840 --> 21:12.840
check out what are the false positive

21:12.840 --> 21:14.840
and exclude them.

21:14.840 --> 21:16.840
Instead if you are target

21:16.840 --> 21:19.840
the end user you need to be able to provide

21:19.840 --> 21:21.840
like less false positive

21:21.840 --> 21:24.840
as possible otherwise the user will simply just

21:24.840 --> 21:28.840
be scared by all your warnings.

21:28.840 --> 21:31.840
And finally as I said UX because it is important

21:31.840 --> 21:34.840
for the end user to ever

21:34.840 --> 21:39.840
easy to use application.

21:39.840 --> 21:41.840
So clearly everything is open source

21:41.840 --> 21:45.840
you can find a blog post on our website about this.

21:45.840 --> 21:47.840
It is not released yet we will soon

21:47.840 --> 21:49.840
we are thankful to all the people who helped

21:49.840 --> 21:52.840
to Rowan and also to all the previous projects

21:52.840 --> 21:55.840
who provided like the foundation to start building

21:55.840 --> 21:58.840
is to see the service service service organization

21:58.840 --> 22:00.840
that is an organization

22:00.840 --> 22:02.840
of organization and all the

22:02.840 --> 22:04.840
civil society groups tend to share

22:04.840 --> 22:05.840
threat intelligence.

22:05.840 --> 22:07.840
And we didn't talk about closet source

22:07.840 --> 22:08.840
source tools, there are a few

22:08.840 --> 22:10.840
and that is some purpose because most of

22:10.840 --> 22:12.840
these tools do some kind of full pack

22:12.840 --> 22:14.840
data collection and then run

22:14.840 --> 22:16.840
and maybe machine learning algorithms

22:16.840 --> 22:18.840
on their servers but the first need to collect

22:18.840 --> 22:19.840
the logs and all that kind of stuff

22:19.840 --> 22:21.840
where we are trying to focus on

22:21.840 --> 22:25.840
local clear practices to

22:25.840 --> 22:27.840
respect the user choices so nothing

22:27.840 --> 22:29.840
from the application gets shared unless

22:29.840 --> 22:30.840
the user explicitly go through

22:30.840 --> 22:32.840
a flow to share that information

22:32.840 --> 22:35.840
and to end encrypted it doesn't come to us.

22:35.840 --> 22:36.840
And so that was it.

22:36.840 --> 22:38.840
We are happy for questions.

22:38.840 --> 22:40.840
There are more pointers.

22:40.840 --> 22:50.840
Thank you.

22:50.840 --> 22:56.840
Just say that this project was only

22:56.840 --> 23:00.840
in my work that is existing

23:00.840 --> 23:03.840
all the advice as an application.

23:03.840 --> 23:06.840
So in theory, like that's the easiest to

23:06.840 --> 23:07.840
catch.

23:07.840 --> 23:08.840
Sorry.

23:08.840 --> 23:10.840
The question is does the application only

23:10.840 --> 23:12.840
try to detect malware that is installed

23:12.840 --> 23:13.840
as an application?

23:13.840 --> 23:15.840
The answer is not necessary.

23:15.840 --> 23:17.840
In the sense that that's the easiest to catch

23:17.840 --> 23:19.840
because it leaves the most traces and then we can

23:19.840 --> 23:21.840
from the application in theory you can

23:21.840 --> 23:23.840
not extract the application and then

23:23.840 --> 23:24.840
as to share those.

23:24.840 --> 23:26.840
But with the fact that we collect the log

23:26.840 --> 23:28.840
cut and the back report,

23:28.840 --> 23:30.840
if there's wheel crashes and we have

23:30.840 --> 23:31.840
you see it for the wheel crashes,

23:31.840 --> 23:33.840
then we can basically say well there's

23:33.840 --> 23:35.840
wheel crashes on your back report that's

23:35.840 --> 23:37.840
the easiest and the same goes for SMS.

23:37.840 --> 23:39.840
Like if you received an URL,

23:39.840 --> 23:41.840
there was one of the known ones.

23:41.840 --> 23:54.840
So the question is about, for instance,

23:54.840 --> 23:55.840
Java card applets.

23:55.840 --> 23:57.840
So these are regretted as if you open

23:57.840 --> 23:59.840
us an issue, then we look if we can find

23:59.840 --> 24:02.840
this information from adb and we will add

24:02.840 --> 24:03.840
the model to do that.

24:03.840 --> 24:05.840
Because you've got this all the time.

24:05.840 --> 24:06.840
Yeah.

24:06.840 --> 24:07.840
Yeah.

24:07.840 --> 24:10.840
But all the forms are due to this,

24:10.840 --> 24:13.840
but very low integrated

24:13.840 --> 24:15.840
with the communication problems.

24:15.840 --> 24:17.840
And it's true.

24:17.840 --> 24:19.840
Yeah.

24:19.840 --> 24:20.840
Yeah.

24:20.840 --> 24:21.840
Yeah.

24:21.840 --> 24:22.840
Yeah.

24:22.840 --> 24:23.840
Yeah.

24:23.840 --> 24:24.840
Yeah.

24:24.840 --> 24:25.840
Yeah.

24:25.840 --> 24:26.840
Yeah.

24:26.840 --> 24:28.840
Yeah.

24:28.840 --> 24:29.840
Yeah.

24:29.840 --> 24:30.840
Yeah.

24:30.840 --> 24:31.840
Yeah.

24:31.840 --> 24:33.840
Yeah.

24:33.840 --> 24:35.840
Yeah.

24:35.840 --> 24:36.840
Yeah.

24:36.840 --> 24:37.840
Oh, yes.

24:37.840 --> 24:39.840
Oh.

24:39.840 --> 24:40.840
Yeah.

24:40.840 --> 24:43.840
Well, a bit to chat afterwards and we see

24:43.840 --> 24:45.840
we can build a model to do that.

24:45.840 --> 24:47.840
It really depends on what we can do from adb.

24:47.840 --> 24:50.840
We can't, like some stuff is documentited.

24:50.840 --> 24:51.840
Like you can do adb commands to finance

24:51.840 --> 24:53.840
certain things other stuff just like finding

24:53.840 --> 24:55.840
application to their device had means have

24:55.840 --> 24:56.840
commands to their know document.

24:56.840 --> 24:58.840
So if you spend some time you can find a way

24:58.840 --> 24:59.840
to detect it.

24:59.840 --> 25:00.840
So maybe there's a way to also detect it.

25:00.840 --> 25:23.840
This is the, by now, yes, the last one is up in the configuration of the operator 7, or 8, and the one that's the one that's the one that's up, and to be a vector of infection, you know the basis, you know the basis,

25:23.840 --> 25:37.840
if there are changes on the device setting, yes, that's an artifact that we gather.

25:37.840 --> 25:51.840
If, for example, malware just leaving memory and replace, for example, the X, Java class classes for another process, for example, like it's targeting WhatsApp and then changes the code for WhatsApp,

25:51.840 --> 26:13.840
then we are not going to be able to detect that with normal artifacts, but that's not like the our target, like our target is just low-end spyware that is not so sophisticated because we don't have like the privileges to dump and catch that.

