A (3:39)

Sam, what did you work on, video wise back at Vice, slash Motherboard?

B (3:46)

I did an episode of Cryptoland, which was. My episode was about crypto being used for sex work. So I went out to Vegas and went to like a content house basically for crypto. And it was really fun.

A (4:04)

It was cool.

B (4:05)

Yeah. Obviously video documentaries are really hard. It's a complicated process. So I'll be interested to see how it goes now that we're dipping our toe into doing our own.

D (4:17)

So.

B (4:17)

But yeah, Jason's. I mean, the neon documentary is really good. You should go watch it. It's really interesting. The main character in it, Gio, is such a character. So I want to go hang out in his shop in la.

A (4:30)

Yeah, I mean, it's great. And when we say we're doing it ourselves, it is very much that Jason took the podcast, sorry, the camera he usually uses for this podcast, and went and filmed this short film. So that's literally what we're doing. And of course, as we get further into it, I'm sure maybe we'll bring help on and outside contributors and that sort of thing. And that's all very much TBD down the line. But hey, it's just an exciting time. The couple of years after launch, as you say, we have the support where we can diversify and start to explore different stuff. And I definitely have ideas of what I want to try to do. All right, well, for this week, Emmanuel, do you want to lead us through this first story?

C (5:17)

Yeah. So our first story is from Joe. The headline is hackers Docs, Hundreds of dhs, ice, FBI and DOJ Officials. So, Joe, what is this data exactly? And what is the scale of the hack or docs or whatever you want to call it? How big of a problem is it, would you say?

A (5:41)

Yeah, so the data itself, this first story we're talking about, it's mostly DHS and of course that includes ICE as well. And then there's some FBI and DOJ as well, but there's something like nearly 700 DHS officials in total. And that includes their official email address, which, you know, helps verify that they're a government employee. Their name, a phone number. Sometimes that looks like a personal number, sometimes it looks like an office number, but there's definitely some personal ones in there, and then addresses. And again, this is also sometimes some sort of government facility. But the ones I looked at, they sure look like residential addresses when you put them into Google and a Zillow listing comes up and it's like, oh, I. I don't think that's an official DHS facility or something like that. So it's straight up docs. And obviously that is a lot of personal data that people could do various things with. And in this case, it landed in the hands of a group of hackers who are financially motivated, I would say. And I'm sure we'll get into that as well.

C (6:53)

So the first thing we do when we find out about a leak or docs like this is we try to verify that it's accurate, otherwise we wouldn't report on it. How did you do that for this story?

A (7:05)

Yeah. When a hacker reaches out and they say, I have this data, it could be absolute bs. You have no idea if they've fabricated it and they're trying to do it for clout or prestige or maybe just as troll the journalist or whatever. We've had it before where hackers targeted telemessage that signal clone the Trump administration uses. And we broke news of that hack way back then. There was a bunch of data about Customs and Border Protection officials in there, like phone numbers, that sort of thing. In that case, I just phoned them up, I asked them, hey, is that blah, blah, blah from cpp? And they say, yes. And then I say, my name is Joseph Cox, I'm a journalist, blah, blah, blah. And then usually they hang up immediately when I start actually speaking. So I did that way back when, and I could have done that for this, but I actually just felt like doing a different approach, which is that I took this docs provided by the hackers, and then I turned to data provided by a company called District 4 Labs. They have a search tool called Darkside. And I log in, and basically it brings together all of these different data breaches from all over the Internet. So back in 2016, I remember that there was a wave of breaches, LinkedIn and all of these other ones. And if you were a journalist or a cybersecurity researcher, you had to go and download that data, then search for it yourself, and maybe that was useful. I seem to remember some stories from the time where, oh, I need to verify who this person is for this story. A couple of years later, oh, let me go through the data breach of XYZ company. You don't need to do that anymore because companies like District 4 labs exist and they just bring it all together and then they allow researchers or journalists or threat intelligence analysts or I presume, government as well, it allows them to log in and you can just search all of these databases at once. So I started taking phone numbers from the DHS and the ICE docs, put them into this tool and very quickly it was apparent that, oh, yeah, these are real docs of ICE and DHS officials. There were some interesting cases where I would put in the phone number and would bring up the matching DHS email from a breach of a parking app. And that shows, oh, that DHS official must have signed up to that parking app with their official email address. The name matches, the phone number matches all of that sort of thing. Other ones where you would put in the address and get the phone number, or you put in the phone number and you get the address. So that did indicate this data is legitimate. Now, that said, there's the chance that these hackers have just repurposed all of that data that's already out there. You know what I mean? They've like, oh, they also have the parking app data and now they're repackaging it and going, oh, look at us, we doxxed ice, we doxed DHS or whatever. But when I was verifying, it was spread across so many different datasets that just didn't seem likely. And sometimes the data didn't appear in previously breached stuff at all as well. So it was basically building a mosaic and an understanding of, well, this data does appear to be legitimate. It does appear to be new in a lot of cases as well. And it really does appear to relate to specific government officials, including DHS, ICE, DOJ and FBI.

B (10:52)

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D (12:22)

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C (14:23)

So this story was a huge traffic bomb for us. And I think the reason for that is that in a different time, the fact that there was a hack or a docs of a bunch of people who work for DHS and ICE would not be that interesting to so many people. But it's happening at a time, as we've reported over and over again this year, where there's like increased attention on DHS and on ICE because of the way that it's operating. Masked agents in the streets, picking people up, deporting them, etc. And the timing of this docs, I think if you don't read anything about the story, if you don't click through and read a single line of reporting, you might assume that like there is some sort of hacktivist activity here or motivation to the docs. That is not what is happening. If you are familiar with the group behind the docs, which I think is the most interesting part of this story and I guess to start on that, Joe, because it's so complicated, like what this group is, the names it has, the motivation, the history of other breaches that they've been involved with, all that stuff. So like, to start this, I would challenge you to like, what is the. And you use as many words as you want, you don't have to be succinct because it is complicated, but it's like, what do you think is the most accurate, fair description of this hacking group?

A (16:07)

I think this group, which is called Scattered Lapsus Hunters, which we'll get to, which is obviously a very complicated name. I'll explain what that means in a minute. But that group is a financially driven extortion gang. That is what they do. They breach companies, they steal data, they then try to extort maybe the individual customers where that data's been taken from, or the overarching technology and service provider, which in this case is Salesforce. They're a financially driven extortion gang. That's how we would categorize them.

C (16:43)

I think that's fair. But I feel like that kind of like if you were just, if you were to just say that you're missing some other important context, which is, I would argue the fact that they are primarily English speaking, it seems that they appear to be young or that many of the members are young and that they've been involved in real world violence as well. Yeah, go ahead.

A (17:16)

Yeah, so that was definitely the bullet point. But now to step back and you're absolutely right to give that context, I'm going to step several steps back. So there's this thing called the comm and it's short for community and there's a lot of different ways to describe it. I think recently I've called it like an online phenomenon. It's almost like a cultural phenomenon thing, almost an anthropological thing. And what this is is thousands of thousands of people on telegram and discord, usually English speaking, as you say, Canada, the United States and the United Kingdom. And it's gamers, it's people hanging out on these chat apps, people playing Minecraft, people playing Roblox is often how they get into this world. And it might start with cheating in those games or stealing valuable Roblox items or something like that. Until eventually people in calm are hacking, they are doing fraud, they're scamming, they're doing sim swapping. At least they did a lot of that. I'm sure they still do. But things have escalated somewhat now and it's this massive community, as I said, of thousands of people doing all sorts of things from trolling to beefing to crime, right up to, as you said, the commission of serious physical violence. I've seen, well, we've all seen videos of people having their ears chopped off, attacks with hammers, all of this stuff back when I covered com much more like a few years ago. I've just been focused on other things recently. So they come from that ecosystem now out of com again because it's not like a group or really it's again like an anthropological thing. Out of comm you get these various groups or nexuses of activity. So a really famous one is going to be Scattered Spider which was sort of the most well known one I would say. They were amazing at sim swapping, really effective at that. Started joining forces with Eastern European ransomware. Gangs have been linked to the ransomware attacks on NGM resorts, that sort of thing. So really going from stealing Twitter handles because it's a proper noun and it looks cool to have Ark or whatever on Twitter right up to hacking MGM and other companies. So you have Scatterspital, you have Lapsus, which actually came before and I covered them when they broke into Electronic Arts and stole a bunch of data from there that was involving buying login tokens for Slack, that was Also pretty novel at the time and lowered the barrier to entry for hackers again. So you have Lapsus, then you have Shiny Hunters, which almost like a forum administrator, more of a data broker slash seller, although has connections to hacks as well. And then that brings us to this latest evolution of this sort of ecosystem which is this kind of specific group called Scattered Lapsis Hunters. They are the ones that have posted these docs of DHS ICE officials. And that sounds like a bunch of names and it is just a bunch of names. But it shows that we're not just talking about Chinese state sponsored hackers breaking into OPM anymore and stealing the data of U.S. officials. We're talking about probably pretty young people who have escalated from stealing stuff in Roblox to becoming a top tier national security threat. I mean it's insane when you put it like that.

C (20:57)

Yeah. And notably again, not hacktivists, like not looking to do good. Not anonymous. Right. It's like if you just read the headline and you assume that's what this is. It's not that. To follow up on something, you know, in your brief definition of them you said they're financially motivated which is what made them dox these people. Can you explain a little bit more how that would work? And also I believe there was like another like stated mechanism through which they thought they would like gain profit.

A (21:36)

Yeah. So I don't think the doxing of DHS and ICE is specifically linked to the extortion, but to give the context on that, this group or people affiliated with it, whatever, broke into a bunch of databases which were using tech from the tech company Salesforce, which we all know a ton of companies were using this Disney, Hulu, Toyota, ups, all of these companies. This group, again people working with them broke into those, stole all the data and now they've been trying to extort Salesforce. Maybe they've gone to individual companies as well, but they've gone more to Salesforce and said we're going to leak all of your customers data if you don't give us presumably millions of dollars or whatever Salesforce has said we're not going to do that. That's what Bloomberg reported. And then when I've spoken to a member they said, oh yeah, we're sort of done with Salesforce and now we're just posting these docs. And the reason being, and I didn't include this in the article because I don't take it as a verified fact, but I feel like I can give people just a behind the scenes thing on the podcast which is that one of the members told me they started doxxing DHS and ICE because one of their friends got deported. I don't know, man. Like I asked. Well, can you give me the name of the person who was deported? That I can verify it? And they didn't want to provide that and because presumably that could, you know, reveal their identity or something like that, which I get. They're not going to hand that over, but that's why I didn't put in the article. So they are extorting Salesforce or they were extorting Salesforce. Now they're almost just doing stuff to cause damage. And that's like a key feature of these groups as well, is that they just do stuff to starfires sometimes.

C (23:22)

I was, I was going to give my completely subjective reading of it, but it almost feels as if they haven't been in the news for a minute. And they were like, oh, you know what we could do to really get some clout right now is dox a bunch of DHS and ICE officials. Because that's what everybody's talking about. And they were right. You know, it's like it did work and they have a history of trolling and making a mess just to make a mess. So I definitely, I can't prove it, but like that. I believe that that is a motivation here. So you published the story we just talked about. Then a few days later you publish another story with the headline, hackers say they have the personal data of thousands of NSA and other government officials. So what did you learn to justify publishing this new story?

A (24:15)

Yeah, so a little while before that, almost around the time of the original DHS and ICE doxxing, these hackers also posted the apparent docs of a specific NSA official. In the Telegram chat, I mentioned that offhand behind the blog that we published on a recent Friday, I then do this one. Then again, this member reaches out and says, oh, we actually have much more data, they say, of 2,000 NSA officials, 22,000, something like in total of the U.S. government. And they start sending me the personal data of a lot of government officials. And again, it's the same thing. It's names, email addresses, phone numbers and addresses. And honestly, the number of agencies was dizzying. There's Defence Intelligence Agency, Federal Trade Commission, Federal Aviation Administration, the cdc, atf, Air Force, State Department. And what I did was I did much the same thing. I took those pieces of personal data, turned to that Darkside tool again and verified while I could. Again, it looked legitimate. So then we published that as well. And initially this story, at least in my head, was going to be more about the Salesforce connection. Because the. That was a question when they initially published the DHS and ICE one and said, well, where are they getting this data? It's probably the Salesforce stuff they stole, but I don't really know. The member reached out, that's what they said. That was going to be the headline. But then when they started sending all of this other personal data, I was like, oh, this is like a really broad, I think ATTCK is too strong, like a broad incident with the US Government. It's not just a DHS ICE thing anymore.

C (26:08)

Any other agencies that you want to talk about that were impacted or anything else you want to say about where they got this data?

A (26:16)

Yeah, well, I mean there's FDA in there as well, Health and Human Services and they mentioned State Department. I think the last thing I would say is that I find it really interesting that I mentioned several years ago, Chinese state hackers targeted the Office of Personnel Management, opm and they took all of this very sensitive data that could be used to identify, I think undercover officials and that sort of thing. When you attack the HR department of the US Government, you're going to get a lot of very sensitive, interesting data. That's why the Chinese hackers did that here. I'm definitely not saying they're equivalent. The OPM stuff would have been way more sensitive because there's like background checks and stuff in there as well. But what's happened here is that a bunch of English speaking, probably young hackers have managed to build dossiers on US Government officials themselves. Not by attacking the US government directly, but going to all of these other companies that happen to use Salesforce. And of course it also reminds me of the snowflake at&t breach where young hackers broke into a Snowflake database run by AT&T, which included the cool and text metadata records of nearly all of AT and T customers. Again, that is something that you would usually attribute to top level state sponsored hackers from Chinese, Iranian, Russian intelligence, something like that. And we reported they did a lot of interesting stuff with that. They looked up members of the Trump family in that data and various politicians, all of that sort of thing. Almost the same thing is happening here. It's not Snowflake this time, it's Salesforce. But they've gone and got this very sensitive data, including again personal data of NSA officials and other intelligence community officials as well. The Telegram channel is gone now people are saying it was shut down by telegram. That seems like the most likely explanation. There are rumors the members have been arrested, but I haven't seen strong enough confirmation to put that in an article or anything. But I don't know if you're starting to dox ice DHS and NSA officials. I think that the US Government is probably going to come knocking pretty quickly. All right, should we leave that there? After the break, we're going to talk about one of Emmanuel's stories, and he's going to bring us up to date on what's happening with Wikipedia and AI. We'll be right back after this.

D (29:09)

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A (32:29)

All right, we are back. Emmanuel, this is one you wrote. The headline is, Wikipedia says AI is causing a dangerous decline in human visitors. So Wikipedia is seeing this. How big are we talking? Like, what's the scale? Before we get to the specifics, is it like, I don't know, half of all traffic to Wikipedia is bots or something? Like, is this a big deal?

C (32:51)

So the hard number they gave me is 8%, 8% down compared to the same time last year, which I don't know what that sounds like to you. I would say if we were to look at Four4Media's traffic and see that we were down for October 8% year over year, we would definitely not lose our minds over that. But you have to keep in mind that Wikipedia is one of the most popular sites on the Internet. I believe that they get something like 300 billion page views a year. So when you're Talking about an 8% decline, you're talking about billions of page views, which is just like a massive shift in how traffic is rooted around the Internet.

A (33:43)

Yeah. So what does wikipedia attribute this 8% decline to? And to be clear, it's an 8% decline of human visitors.

C (33:53)

Correct.

A (33:54)

Yeah.

C (33:54)

So, you know, they kind of do an audit of their traffic, and also they have always done this, but now a lot more. They do a lot of auditing of bot traffic in particular, and they have ever evolving methods for how to designate traffic as bot traffic, as many other sites do now because of the huge problem of AI scrapers that we've talked about on the podcast many times. And what happened basically is that they noticed a lot of traffic, like an abnormal spike of traffic coming from Brazil specifically. And it was such a significant increase that it made him go back and investigate the traffic which they previously assumed was human. And upon further examination, they decided that that traffic was not human, that it was bot traffic. And then they both reconfigured their methods for detecting bot traffic because of this investigation, and then revised their traffic data, and that's when they noticed that there was an 8% decline in human traffic.

A (35:12)

Yeah, so I'm speculating and kind of putting words in the mouth a little bit, but it's almost like, wow, there's a big spike of readers from Brazil. Maybe people in Brazil just got. There was some Asian news event and wow, everybody's checking out Wikipedia and they go and look at it. It's like, oh, no, it's actually a bunch of robots, essentially.

C (35:32)

Correct.

A (35:32)

They, they, they didn't speculate or name a specific company then. It was just, there's a lot of buck traffic coming from Brazil for some reason, and left it at that.

C (35:41)

They did not name a specific company. I think, as you probably know from reporting on hacking or even like video game hacking and cheating, they're kind of in a bind here. Obviously, as a reporter, I want to get as as much specific information as possible, and I pushed for that. However, they are reluctant to share technical details about how this bot traffic works and how they detected it, because once they make that information public, it makes it easier for people who build scrapers to work around their protection and detection methods. So they didn't explain exactly how it worked, only that they were confident that it was bot traffic. Who that can be, your guess, is as good as mine. All I can say about that is that every single major AI company scrapes the Internet for traffic. There's varying degree of openness about that practice, but everybody does it. And that is before we get into AI companies from China and other countries that are less open about how they collect their data, and a bunch of really small projects that nobody knows exist. But they are also scraping the Internet to build AI products. So that can be anyone, however kind of like related. And in addition to this bot scraping problem, when they talk about a decline in traffic, they also say that search engines presenting their own summaries of Wikipedia articles is diverting a lot of traffic away from Wikipedia. And they don't say Google, but it's Google.

A (37:33)

It's obviously the AI summaries at the top of Google.

C (37:35)

Right? Not even AI summaries. Yes, and I recently wrote about a study from Pew that shows that only 1% of people who are presented in the AI summary click through to the article, which makes that problem even worse. But that is building upon Google's years long practice of presenting the Google snippet or knowledge panel which basically does the same thing. It just shows you a summary of something instead of throwing you a link to that website. And Wikipedia is saying that obviously that is diverting traffic away from them.

A (38:12)

Yeah, so there's two things. There's a spike in bot traffic in that just case it was from Brazil, but of course it happens all over as well. And then people just not going to Wikipedia because they're seeing some sort of summary from a search engine, that sort of thing.

C (38:26)

And the bot traffic is building chat bots that are also diverting traffic. Right. So it's like there's also an increase of people who are not going to Google, they're going to ChatGPT. Asking, asking a question. The answer that is provided many, many times is just a summary of a Wikipedia article. But you get, when you do that you don't, you don't go to Wikipedia. You get Wikipedia information but you're not going to Wikipedia.

A (38:55)

Right. So the Wikimedia foundation, which is a non profit that hosts Wikipedia, their senior director of product Marshall Miller wrote this blog post announcing it. I think you actually got a under embargo if I remember correctly. And then you also spoke to Miller via email. What did they tell you? Did they elaborate on this at all?

C (39:20)

Again, this is them being nice and like entertaining my, my questions. But the gist was like we can't tell you exactly how we did this, only that we're very confident that this was bot traffic and that our bot detection methods evolve all the time and that this most recent spike was like very severe and something that we're confident is bot traffic, but we can't tell you the gory details for the reasons I mentioned earlier.

A (39:49)

Yeah, so you mentioned the Pew research about only 1% of people clicking through when they're presented with a Google summary. Does this line up with any other research you've seen recently? Because it just seems to be. It almost seems like we've covered this a bunch. Where you specifically cover this a bunch. And now Wikipedia is like coming out of a blog post basically saying, yep, here's another example of it.

C (40:13)

Yeah, so there's a pew research where they tracked. I forget what the sample size was, but they just like tracked the user behavior of people who were presented AI summaries on Google and saw that only 1% of those users clicked on through. That is building on top of a bunch of anecdotal reporting from and about media, that they're seeing a decline in traffic because of Google summaries, because of chatbots. And that is also building on top of previous self reporting from Wikipedia saying like, hey, we are dealing with like a massive spike in bot scrapers that is making it more difficult for our site to operate. And we've heard the same thing. I reported about this quite a bit where it's not just Wikipedia, it's like any store of information online, online libraries, museums, online archives, they're all getting slammed by these, by these bot scrapers that is making it more difficult for their fights to operate.

A (41:23)

Yeah. So what is the actual impact on Wikipedia with all this? Is it what you just alluded to, which is like it's kind of getting overloaded and there's all of these bots. I feel like it's probably not that because I think Wikipedia can handle that. Or is it more, you know, fewer people are going through and they're not going to donate as much money. Like, do you, do you know what the actual tangible impact is?

C (41:47)

I think that's a great question. And to be honest, when they first told me about this, that was the question that came to mind as well. Because Wikipedia is free, right? It's free, it doesn't have ads. What does it matter if you get the information from wikipedia.org or if you get it from a summary from ChatGPT? And there are two reasons that Miller gave me, and one is pretty obvious when you think about it, which is Wikimedia foundation relies on donations the way they collect donations. If you go to Wikipedia and there's a big banner which people love to complain about on Wikipedia, which is like, hey, we're supported by donations, Please give us money. And it's like that is an important way for them to raise money, just as it's a way for us to raise money. Right. It's like you go to our website, you read our article, and there are various what we what we call calls to action to support us financially and that's how we run our business. So that makes perfect sense. The other reason I thought was way more interesting, which is Wikipedia, there's a Wikimedia foundation which kind of operates at a very high level and does this traffic analysis, writes these blog posts. But like, the governance and production of Wikipedia articles is not them. Like, the reason Wikipedia is such an amazing and still functional store of information is that it's community and volunteer run and it's just a bunch of people writing articles, debating them, editing them, coming up with the governance for how to moderate articles and all of that. And if you don't have some sort of mechanism to feed more users into that ecosystem and have them graduate into being Wikipedia editors and volunteers, then the system dies. Right. It's just like Wikipedia has been around for a very long time now. And at this point I talked to Wikipedia editors sometimes, they're younger than me. And the reason they get into Wikipedia is like, there are students at school, they research something, they start using Wikipedia and they're like, oh, this is a really cool project. How do I get involved? And that's how Wikipedia works. That's what makes it valuable. And if that process stops at a Google AI generated answer or a ChatGPT generated answer, the whole system breaks down. And that seems to me the more serious concern for the Wikimedia foundation is you have to let people into Wikipedia's actual site in order to keep that ecosystem of volunteering alive.

A (44:45)

Yeah. And just lastly, well, what is the solution here? If one exists, is it just Wikipedia continues this cat and mouse game with bots, or like, there's no, oh, if only we did this, the problem would be solved? I mean, that's just not realistic. It's an ongoing dynamic. Right.

C (45:03)

Yeah. I thought this was also really interesting. Part of their announcement, there was like a two pronged approach to the problem, it seems, and one is Wikimedia has official relationships with Google, with YouTube, with these generative AI companies. And they don't give specifics here, but it sounds like at this point, sometimes when you go to YouTube and you watch a video and YouTube itself will like fact check a video and what it will do is, you know, like it gives you a little banner at the bottom that says something like, oh, well, people dispute the argument in this video, or this video was produced by so and so government and it sends you to a Wikipedia page for that topic. And that obviously is good for Wikipedia because it funnels people that way. So it sounds like they want to build on those relationships and they want to build in those relationships with AI companies in particular, because it looks like that funnel, obviously, as we can see from the data, that funnel is not working to their advantage or not working fairly given what they contribute, like the traffic they get back. So that's a piece of it that makes a lot of sense. The other one I think was kind of more interesting because it was an appeal to personal responsibility. It was sort of telling people, it's like, hey, it's like, do you like getting information online? You probably get that information from Wikipedia. You should consider visiting our website and you should consider becoming a volunteer and you should consider how this really, this whole system makes the Internet a much healthier, more productive, positive place. And like, please get involved. Which I don't know. I'm not a huge fan of like personal responsibility arguments when it comes to like climate change or something like that. But given that this is a community run thing, I find that to be a compelling argument. How many people hear it and how many people actually respond to it, I think remains to be seen. But that, that was kind of his plea.

A (47:19)

Yeah, bring in more humans to counter the increase in bots, essentially in various forms. All right, we'll leave that there. If you're listening to the free version of the podcast, I'll now play us out. But if you are a paying 404Media subscriber, we're going to talk about OpenAI's pivot to sex chatbot service. I mean, it was always going to happen. The writing was on the wall. It took them long enough. You can subscribe and gain access to that content at 404 Media co. As a reminder, 404 Media is journalist founded and supported by subscribers. If you do wish to subscribe to 404 Media and directly support our work, please go to 404 Media co. You'll get unlimited access to our articles and an ad free version of this podcast. You'll also get to listen to the subscribers only section where we talk about the bonus of story each week. This podcast is made in partnership with Kaleidoscope. Another way to support us is by leaving a five star rating and review for the podcast. That stuff really helps us out. I'll read some more out soon. This has been 404 Media. We'll see you again next week.