Everything You Need To Know About Crypto Cartels: Podcast Ep. 135

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Chainalysis
11-05

Episode 135 of the Public Key podcast is here! Almost 110,000 Americans died from drug overdoses in 2023 and 80 percent of those deaths were attributed to fentanyl, which is unprecedented in American history. This week, we speak with Jim Schrant (Director of Strategy and Growth, CACI International) to discuss the emergence of crypto cartels that are fueling the drug trade and how their new solution, CluesAI is arming law enforcement with technology dives deep into the dark web drug trade.

You can listen or subscribe now on Spotify, Apple, or Audible. Keep reading for a full preview of episode 135.

Public Key Episode 135: Dark Web Dangers: Unmasking the Networks Behind Fentanyl Trafficking

Almost 110,000 Americans died from drug overdoses in 2023 and 80 percent of those deaths were attributed to fentanyl, which is unprecedented in American history.

In this episode, Ian Andrews (CMO, Chainalysis) discusses these horrific stats with respect to fentanyl trafficking and the technology-driven evolution of drug cartels with Jim Schrant (Director of Strategy and Growth, CACI International)

Jim provides a comprehensive look at his extensive career in the DEA, offering insights into the evolving landscape of drug trafficking facilitated by cryptocurrency and how their new solution, CluesAI and other technology, gives law enforcement a fighting chance against modern day drug traffickers.

He also provides in-depth analysis of the role darknet markets and precursors like Xylazine add to the fentanyl crisis and identifies the role Cartels and Chinese money launderer organizations play in moving crypto and cash around internationally.

Quote of the episode

“In 2023, we’re looking at 107,000 overdose deaths, of which about 80 percent of those are attributed specifically to fentanyl. And so you look at 110,000 Americans dying of overdoses, it’s unprecedented in American history.”  – Jim Schrant (Director, Strategy and Growth, CACI International)

Minute-by-minute episode breakdown

2 | Jim’s law enforcement journey beginning with investigation Colombian drug cartels

4 | Evolution of technology used by criminals and the emergence of sophisticated Fentanyl production and trafficking

8 | How the Darknet Market’s role in fueling the Xylazine and Fentanyl crisis

12 | Crypto becomes main way that drug cartels are moving the proceeds of Fentanyl sales

18 | Challenges and innovations in law enforcement’s technical evolution in investigating drug trafficking

22 | Revolutionizing Darkweb investigations with CluesAI for law enforcement

30 | Modernizing Federal law enforcement through technology and expertise

Related resources

Check out more resources provided by Chainalysis that perfectly complement this episode of the Public Key.

Speakers on today’s episode

  • Ian Andrews *Host* (Chief Marketing Officer, Chainalysis)
  • Jim Schrant (Director, Strategy and Growth, CACI International)

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Transcript

Ian:

Hey, everyone. Welcome to another episode of Public Key. This is your host, Ian Andrews. I’m super excited for today’s conversation. It’s actually one that we had live in person at the Chainalysis Links Conference a few months back here in Washington DC. This is with Jim Schrant, who’s the Director of Strategy and Growth at CACI International. But Jim, you spent 25 years working for the Drug Enforcement Agency. We had a fantastic conversation about the current state of fentanyl trafficking and the drug epidemic here in the United States, which I’m really looking forward to continuing on the conversation today, so thanks so much for taking the time to join us.

Jim:

Ian, thank you very much for the invitation. It’s been my pleasure getting to known work with you, and the collaboration between CACI and Chainalysis has just really been outstanding. And we’re excited for what the future holds between both companies.

Ian:

Wow, appreciate the partnership. Let’s start with maybe a little background on yourself. You were at DEA for 25 years. You must’ve done an incredible variety of things during that time. Give us a little walk through kind of your career trajectory and what you did at the agency.

Jim:

Yes. So I started with DEA, the Drug Enforcement Administration, in 1997, so I was a very young man at the time, and sort of had an almost Forrest Gump like experience because I moved around DEA. A lot of times, it was very much at the beginning or right in the heyday of a lot of different threats against the United States, beginning with Florida, so I started my career where it was really a fantastic opportunity to engage with the Colombian cartels, understand, and then ultimately work investigations against what they were doing, both in very high level money laundering and high level cocaine and heroin importation and distribution throughout the East Coast and the rest of the United States. So great way to sort of cut my teeth on that.

Then, as I moved throughout DEA, a lot of my time was spent at our Special Operations Division, which is based in Chantilly, which is really one of the crown jewels of the Department of Justice. It’s center that we’ve got over 40 different other agencies that participate and it becomes just a tremendous center of sort of investigative and intelligence excellence, where not only is information sharing paramount, but really, the ability to target and really have very cohesive investigative and prosecution strategies against some of the world’s most notorious drug trafficking organizations comes to pass.

And there’s where I really was on the front line of both the emergence of crypto, and crypto as a capacity in international money laundering, and then the fentanyl scourge. I remember in 2015 being down meeting with the Colombian government as we really walked through evidence that we had via intercepts of some of the very early fentanyl labs that were operating in Mexico, and trying to convince them of the threat, not only to the United States, but globally, including Mexico. So from there, I moved and had the opportunity to take a leadership role in our congressional and and public affairs, and then in our intelligence division as well. So it’s been a really extraordinary career. And since then, I transitioned to the private sector with CACI in 2022.

Ian:

I’m curious. Across that incredible career, what’s changed the most? And maybe what stayed the same from your perspective when you look at the challenge of illicit narcotics trafficking, money laundering, all the things that you touched on in your career?

Jim:

Some of the most critical changes has really been one, sophistication, is the level of improvement in sophistication in a lot of these transactional organizations has just frankly changed the math. So 20 years ago, where you would have elaborate calling centers and elaborate use of phone technology, that’s really been surpassed by a level of understanding of very complex money laundering, organizations, and processes, including crypto, much greater sophistication of technologies, including encrypted apps, the dark web, a lot of these different enhanced and encrypted tools that make their lives incredibly easier. That also gets offset with some of the challenges facing law enforcement in this, is 20 years ago, there were processes by which we could really compete for intelligence and investigative standing with some of those technologies. But encryption has made it increasingly difficult, virtually impossible for federal law enforcement to really be in a situation to have the same capacity to learn and investigate what a lot of these organizations are doing.

The other big component that’s really changed is frankly, production. So 10, 20 years ago, where you had heroin and cocaine, it was really easy to be aggressive at that source of production by targeting the coca fields, by targeting the poppy fields, and then ultimately, a lot of those big conversion labs in South America with really, I don’t want to say emergence, but the domination of fentanyl in really what the global drug dynamic is. The production has completely changed, so you’re talking about relatively small packages of precursors going to labs in Mexico, being converted into synthesized fentanyl that then can be smuggled to the United States, not in 500, 600 kilogram shipments, but in packages the size of a laptop that have hundreds of thousands of dosage units in those.

Ian:

It really is incredible when we talk about fentanyl, sort of the scale of the epidemic, particularly if you measure it in terms of things like overdose deaths in the United States, which I think the excess deaths last year were tens of thousands, 40,000 to 50,000 if I’m remembering my statistics correctly, and I think projected to be larger even this year based on the year to date totals, which is really unfortunate. But this kind of decentralization of the production capacity into these smaller labs with smaller smuggling operations, it seems like it’s a real challenge for law enforcement to put a stop to the drugs coming into the United States. Is that a fair assessment?

Jim:

It is. And I think that decentralization is a perfect description of what that challenge looks like. And just to put a fine point on what that public health epidemic looks like is in 2023, we’re looking at 107,000 overdose deaths, of which about 80% of those are attributed specifically to fentanyl. So unfortunately, you’re-

Ian:

The numbers were low is what you’re telling me.

Jim:

Yeah. And so you look at 110,000 Americans dying of overdoses, it’s unprecedented in American history. And of that, 80% of those are attributed to fentanyl, and largely, the other 20% are generally tied to methamphetamine, which once again, has a very similar sort of production posture as fentanyl does. But to your point is that threat against the United States is you’re trying to track the threat coming from a number of different sources. You can have an aspiring 22 year old fentanyl trafficker sitting in Salt Lake City that’s able to order packages from China over the dark web and have those delivered from DHL to FedEx, ultimately, to his doorstop and then he’s got at entire distribution network that he’s established over the dark net, completely transacting in cryptocurrencies, largely anonymously, that law enforcement has to target that very complex system of distribution.

Likewise, you’ve got the Chinese precursor chemical source sending shiploads full of precursor chemicals into Central America and Mexico, that then are going to a whole diversity of decentralized laboratories that are taking and synthesizing those fentanyl precursor chemicals into raw fentanyl at virtually 100% purity that then they’re able to smuggle into the United States in very small packages. So if I was able to throw up a chart, you could just imagine arrows coming from sort of all points of the world into the United States, once again, really coming to what that constant is, which is that demand, that demand inside the United States for those illegal substances. And it’s an addiction problem, if we’re being quite honest about it. It’s truly a public health emergency that’s driven by an addiction problem that just takes a heck of a lot of resources to try to just deal not only on the supply side, but on that demand side as well.

Ian:

One of the things that maybe scares me the most about this drug as a father of younger children is that it seems like a lot of the overdoses are related to people not actually knowing they’re taking fentanyl, and not attempting to, because it’s being mixed into other combinations of drugs, or it’s intentionally mislabeled, maybe as part of the smuggling operation. Is that overstated, or am I right to be worried about that?

Jim:

You’re 100% right, Ian. And so a lot of times, you’ll hear it referred to as narcotics poisoning because that’s largely what it is. You have someone who’s thinking that they’re buying an M-30 Oxycontin tablet, largely to address an addiction issue that they’re suffering from, which may come from an over-prescription issue that they encountered from an injury a year ago, so they think they’re buying an M-30 tablet, and what they’re really doing is they’re purchasing essentially fentanyl that been pressed via a pill press, either in Mexico or in the United States, and then they’re taking one of these essentially fentanyl pills that they end up dying from very quickly. And then you compound that with a very disturbing trend just in the last year that we were able to sort of track this emerging trend because the dark net oftentimes is sort of a precursor of things to come, so we were seeing a lot of activity on the dark net related to xylazine, which is essentially an animal tranquilizer. It’s an uncontrolled veterinary substance. And were increasingly seeing advertisements and solicitations for sale of xylazine on the dark net.

What was happening is a lot of criminal organizations were then mixing fentanyl, cutting it with xylazine. It’s got a couple pharmaceutical benefits. It ends up increasing the length of the high from the fentanyl, and so it just becomes a really good cutting agent. It doesn’t necessarily dilute the product, but the consequences are severe. And the two really notorious consequences of xylazine being mixed into fentanyl in a fake M-30 pill is, one, xylazine is completely nonresponsive to Narcan.

Ian:

Oh, gosh.

Jim:

So Narcan being a great tool by which first responders can go and revive a lot of these overdose subjects. Xylazine makes that nonfunctional. So as a consequence, Narcan does not work, so xylazine being an animal tranquilizer makes Narcan nonfunctional. The second impact of xylazine is sustained use of xylazine ends up causing xylazine sores. So there’s a breakdown sort of blood vessels and tissues, and almost imagine what somebody with leprosy looked like 1000 years ago, that’s what it looks like. And it can result in gangrene and amputations, and just a whole series of, this isn’t bad enough, xylazine makes everything exponentially worse. And we’re seeing that increasingly showing up in a lot of the chemical signatures in a lot of these fake Oxycontin pills that are containing both xylazine and fentanyl.

Ian:

So it seems like you mentioned earlier that the criminals are getting more sophisticated in their operations. It’s more of a technology driven process. It’s a distributed organization, multiple illicit actors participating. Right? We have manufacturing happening in the US by US citizens potentially. We also have cartels in Mexico at large scale producing the drugs, smuggling them into the US for distribution. We’ve got Chines precursor shops. And it seems like there’s a thread that runs through all of this, which is cryptocurrency, which you mentioned earlier being kind of one of the big things that’s changed over your career. Maybe take us down that track and explain where you first encountered crypto and then kind of how it ties into the current situation that we see with fentanyl.

Jim:

So crypto is such a key component to how these transactional organized organizations are working to really move the tens and hundreds of millions of dollars, once again, not just within the Western hemisphere, but really all over the world. So for me personally, one of the advantages of being on the front line on a lot of these really important trends and threat evolutions was we really saw it about 10 to 15 years ago. So there were a couple of really important sort of kick offs, so to speak, in terms of crypto and drug trafficking. So one was Silk Road. So Silk Road was one of the very first dark net marketplaces that was really serving a global population, and this is 2010, 2011. And they were a very early adopter of bitcoin as being one of the key currencies by which they could anonymously transact what they were facilitating over the Silk Road marketplace. So we saw that, but once again, that is a very sort of bespoke, highly sophisticated organization that was able to operate 10, 15 years ago on the dark net, so certainly a threat, very much an indicator of where things were going to go.

Not long after that, we at DEA really started to see that transition over to largely Mexican cartels, the Sinaloa Cartel famously, and then a lot of the Chinese money laundering organizations operating in the United States on their behalf, is money laundering has always been sort of a specialty that requires access and capabilities. So back in the days of pure cash, we would run it, one of the key target areas for us were money brokers. So these would be sort of agnostic money brokers that had the means to collect and then disseminate cash largely throughout the Western hemisphere. They could go and make money pickups all over New York City in cash and then repatriate that, oftentimes through phone companies, back down to Colombia, or Mexico, or Guatemala, or where they were hoping to get to.

So that system has always been a very effective system, so what we saw transition about 10 years ago was a lot of those money broker activities, which was just bulk cash pickups, transitioning into black market peso exchange and some of those other trends really turned into, let’s turn those into crypto transactions by which we can repatriate a lot of that cash that we’re taking in the United States, and then repatriate that in Mexico or Colombia back down to those ultimately the cartel [inaudible 00:16:37] holders that that was responsible to. And that’s grown into really almost an entirely second banking system that these Chinese money laundering organizations have set up right now, of which crypto is essential to the day to day operations.

Ian:

Tell me a little more about the Chinese money laundering organization, because I feel like this is an under-reported element in the way that profits actually accrue back. So we all have probably heard, everyone listening to this podcast I would imagine is familiar with the Sinaloa or Jalisco cartels in Mexico who have been the primary importers I think of much of marijuana, heroin, cocaine, and now fentanyl coming into the United States. Where do the Chinese fit into that? And how did they become the predominant kind of money laundering faction for those organizations?

Jim:

So that’s always been a key challenge for Mexican drug cartels was that repatriation of cash, is demand is high, the means of production exists, and the means of transportation. But the weakness was always how we get all this cash that’s accumulating in the United States. How will we gather it? And then how will we get it back? And for a very long time, sort of simplicity ruled the day. But simplicity ended up creating a lot of vulnerable vulnerabilities for the cartels and a lot of opportunity for law enforcement. So for us, being able to really target these cash stash houses was a tremendous opportunity where you would find these situations where they were aggregating $10 million, $15 million, $20 million at a time. There was one particularly notorious case where we ended up hitting a place in Mexico, just outside of Mexico City, gosh, about 10, 12, 15 years ago, where there was over $250 million in cash aggregated at this location.

So that was definitely a vulnerability for a lot of these cartels. And there’s a time component with that as well because as you’re trying to repatriate cash back to Mexico, there’s a whole time process that’s involved with that. And it’s just challenging to count and maintain what is a very diversified cash operation. So the Chinese money laundering organizations have really taken off 10 years ago, but have really hit their stride in the last five years, and I would argue domestically, are one of the biggest challenges and opportunities to federal law enforcement in the United States is taking the resources to really target those.

So essentially, a lot of that cash pickup ends up being outsourced to a lot of these Chinese money laundering organizations, where they can go and facilitate those cash pickups inside the United States. The difference is instead of having to pick it up in New York City, bundle it, get it to Tucson, it it across through Nogales and then get it back down to Jalisco, what they’re able to do is pick up $5 million in New York City and that area and then can immediately provide via crypto and other tools, they can get that back into pesos back in Mexico City virtually that same day.

And what enables that is they’re essentially acting as a mirror banking system for a lot of Chinese nationals that are looking to have cash available in the United States, so the Chinese nationals in China are able to go and essentially through the black market, go and obtain a million dollars cash in the United States, where it’s illegal for them to move a million dollars from China into the United States. So this parallel banking system facilitates that to happen with virtually automatic repatriation of cash back to Mexico to the cartels. And what’s the incentive? So each of those steps, both that step of repatriating cash back via crypto or other financial devices back into pesos into Mexico at generally a 3% to 6% fee, so it’s a great money incentive for these organizations to adhere. And that mirror banking system for the Chinese nationals to get US cash oftentimes is done on the very same fee structure.

Ian:

Wow.

Jim:

So out of a million dollar money pickup, you’re really looking at them to have an opportunity of 10% to 12% for every million dollars that they’re laundering.

Ian:

And just give us a sense of what’s the likely scale. I mean, I’m sure we don’t know it precisely, but likely scale of money moving from just on the cartel side of that equation, it’s hundreds of millions of dollars, maybe billions of dollars a year, something like that.

Jim:

Yeah. I think the reasonable sum is easily in the billions. A really good example of it right when I was leaving, we were doing some crypto analysis, particularly CJNG. And we looked at one particular $40 million crypto transaction, so the scale of this is … And once again, you sit there and you think about $40 million in cash and what that would look like inside a tractor trailer versus a $40 million crypto transaction, it’s a completely different animal. Then you look at the other side, which is something that I think Chainalysis does a really extraordinary job with is that delta of technical sophistication by law enforcement to understand what those transactions look like, how to properly investigate them, how to not only see what’s happened in the past, but where there are opportunities to proactively investigate and then facilitate seizures and things that really have substantial impact on cartel operations, which is really targeting the money.

Ian:

And that was actually exactly where I wanted to go with my next question. It seems like the role of the typical agent at DEA or other parts of law enforcement almost by definition, it has to have become much more technical over time. As the technical sophistication of the criminals has gone up, it puts a burden on law enforcement to keep pace. I would imagine that’s a lot of the work that you’re now doing at CACI, is helping our friends still in the government keep up with all this technical innovation.

Jim:

As we talked about how the cartels have evolved, law enforcement has evolved and really needs to deliberately evolve very quickly. And you’re absolutely right, Ian, I think technical proficiency and really the ability to drive a lot of these tools that the industry is developing for law enforcement to really enhance their capabilities, but the barrier to entry is very high. And if you look 10 years ago, a really successful federal agent was one that was very capable in terms of running human sources, informants, then being able to do wiretaps, and then being able to really facilitate putting all of those data points together. But we’re talking about two data points, full intercepts and a source.

So difficult, challenging, requires a lot of expertise, but now, in order to sort of do those same things, you have to be proficient in exploring and exploiting the dark web. You have to be proficient at really understanding crypto, being able to run complex undercover operations involving crypto, and really being able to understand what that terrain looks like. Then on the communications side, that becomes extraordinarily more challenging, so instead of sending AT&T a T3 warrant to go and have them turn on and start listening to the target’s phone, now you’re talking about them running encrypted apps very WhatsApp, where we’re not able to get content. So what you’re having to do is sort of recreate a lot of this data that would’ve come across to us via court order eight years ago, you’re having to go and recreate what that investigative pizza looks like, and it’s just really hard and challenging.

Ian:

Yeah. So I know that you all just released a new tool called CluesAI. Maybe we can talk a little bit about that because I think it goes to the heart of at least this information collection and analysis problem as I understand it, if you want to give the group kind of some insight into that new product.

Jim:

So with the dark web especially, the threat that we see on the dark web is it’s a global threat. So once again, you’re talking about Chinese fentanyl or precursor suppliers that are able to provide container loads to CJNG operating in Mexico, or is able to send a half a kilo to that aspiring fentanyl trafficker in Salt Lake City. All of those advertisements, engagements, are happening over the dark net. And that becomes really challenging to understand what is inherently an anonymous environment to operate and look and understand what is happening in that, and then coincide that with what those investigative strategies that you have are, whether it’s going after CJNG in Mexico or in the United States, going after Chinese traffickers, or going after that aspiring fentanyl trafficker in Salt Lake City.

So much like crypto, it’s a complex environment. Barrier to entry is really high. So for us, that day one challenge of running a tool, it’s going to really be able to exploit that dark web environment, becomes really challenging. And DarkBlue is a tremendous tool for us and what we’re able to capture and exploit on the dark web. A lot of people are saying, “I’m sitting here and I’m trying to figure out what to run first.” So one of the things that we’ve really intentionally done with AWS is developing a very unique gen AI tool that we call CluesAI. And what that does is it absolutely shatters that barrier to entry because now on day one, an analyst or an agent can sit down with a selector or an identifying piece of information, run that. And then they’re going to get back a sort of de-anonymized report saying, “Ian is connected to this WhatsApp address. This is connected to this IP. And we also have linked in this cryptocurrency wallet. And then we believe all of these are connected back to Jim and Amanda and Steven, and this is how.”

And then they’re providing that back in a really sort of connected and tailored summary report back to the analyst or the agent. What’s really spectacular with that too is we designed it with that investigative process in mind because just connecting dots with no basis does you no good. So what’s really critical is having something whereby you can look and understand what that source material is. How are we saying that WhatsApp number X is really attributed back to Ian? So those original source documents, those original data points off the dark web from an advertisement that Ian operating as Wuhan Winner just hosted, that’s how it’s connecting that data back, and then we’re giving that back in terms of sort of a source attribution to help really facilitate not only good intelligence and investigative steps, but making sure that we’re facilitating prosecutable cases.

Ian:

I can’t believe you guys figured out my WhatsApp [inaudible 00:28:32]. It’s Wuhan Winner, Jim. I’m so embarrassed.

Jim:

We’re all about de-anonymization, Ian.

Ian:

You’ve lifted the veil of secrecy here on the podcast. It’s terrible.

Jim:

I will say that an orange sweatshirt does not necessarily coincide with an anonymous nature either.

Ian:

It really is a pretty incredible product though. I got an early demo of it at the Trace DC conference this summer and spent some time with your CTO, who was kind enough to take me through a pretty extensive demo. I thought two things stood out for me. One was how easy it was to use. I’m not a dark web analyst, certainly don’t have the training that the experts do, but it was incredibly easy to put myself in their shoes and say, “Oh, great. I’ve got one piece of evidence, that phone number. Let me discover everything else that it’s connected to across all the sources that the platform has collected information across.” And then that summary you talked about was human readable, which I think is where using a large language model, that capacity of artificial intelligence is so powerful because computers are pretty good at doing that link analysis, but at the end of the day, humans like you and I have to actually look at it and understand what information’s really being presented back to us, and so that summary of all the data elements and how they’re actually connected was really powerful.

The final thing that I thought was also really neat was anticipating that the tool was going to be used in a law enforcement context. And so it wasn’t good enough just to have the information, you had to have traceability back to the underlying records and data because ultimately, you’re building a case that probably ends up going into a court of law, and so there’s all sorts of evidentiary standards there that are important. And so I just thought the product was fantastic. How’s the reception been from customers? Do you actually have it in the field yet? Because I know when I saw it, it had just really started coming to light almost as a beta program.

Jim:

Well, one, much appreciated your feedback on it and your insights because we totally agree, and that was the design. We do have it in production and deployment out in the field, and it’s doing exactly what we had hoped, is a lot of those day one users that we want them using the tool and finding immediate success in the tool are having that, where they’re able to go and they’re able to make these network discoveries right off the bat. One of the things that being on industry now that I’m very cognizant of is it’s really easy to take a gen AI sticker and slap it on something. And in many cases, where people are using ChatGPT or a version of ChatGPT, and then just using that as essentially a summary agent.

And what we needed to do was … Those are important steps, but that’s not what the primary challenge is. The primary challenge where we’re really in massive data understanding and exploitation, it’s being able to take all of these different selectors and being able to use gen AI to link these selectors together. And then ultimately, those selectors represent individuals, or they represent entities. Those make up networks. And then now you’re able to really go in and de-anonymize the link and discover these networks because at the end of the day, whether it’s in drug trafficking, or money laundering, or human trafficking, or even in counter-terror investigations, you’re really trying to figure out who’s who in the zoo, who they know, and what they’re up to. And the faster you can get to those answers, that’s what defines whether a technology’s successful or not.

Ian:

Yeah. One question that came up earlier in the summer when I saw the demo was, I would imagine customers, as soon as they see this and kind of analysts start to experience using it, they’re immediately going to want to throw data that’s proprietary to the organization, or at least comes from outside of CACI. Is that possible yet? Can a customer say, “Hey, here’s a bunch of other evidence I’ve collected through other means,” not dark web data necessarily? But I want to be able to fuse these two data sets together. Is that possible, or maybe on the roadmap?

Jim:

So [inaudible 00:33:13] really, maybe the most critical step in sort of not only data collection, but that sort of data analysis, which is being able to take these very bespoke data points and then use them in additional pools, and whether it’s the dark web exploitation or cryptocurrency investigations, being able to take these pieces of data that you’re able to extract, which oftentimes is very heavy selector based, and then run those in an adjacent platform or tool is really important. And that’s one of the things too that’s sort of that barrier to entry is being able to derive those key bits of intelligence right off the bat that you can use.

So one of the things that is important to us, especially with key partners, and Chainalysis is one of those key partners, is being able for us to be able to pivot back and forth. So if you’re working on DarkBlue and extract a crypto wallet address that then you can pivot and run that in Reactor, that becomes a really powerful and seamless investigative process that doesn’t require a lot of simply cut and pasting, clicking, or writing in my notebook different selectors and then trying to use them. That ability to pivot back and forth against really linked symbiotic technologies like Reactor and DarkBlue and DarkPursuit becomes a really powerful tool.

Then you take those results into a lot of the government systems, where there’s completely different holdings. That just hydrates it even further, and then gets us to those answers that much faster. And that expertise is what we really try to sit down with and discover through training and involvement, and in many cases, where we’ve got enabled analysts that can come and either drive selector or drive taskings on behalf of the customer, or really help enable their workforce to become that much more successful.

Ian:

Yeah. It’s a really I think smart architecture that allows for flexibility across the organization. I want to shift gears a little bit and maybe zoom out. So you’ve had a super impressive career in the DEA. You’re now outside of government looking in and I think with CACI trying to drive a bit of a modernization agenda, but there’s always competing priorities. Right? The toughest thing about a big bureaucracy is you’ve got lots of responsibility, so doing new things is inevitably hard because you’re balancing against all the obligations you’ve collected over decades. If you could kind of wave a magic wand and maybe reorient some of these priorities on behalf of the government, where would you like to see new investments? And I mean, I can imagine this across focus of attention or investments into people, and kind of human capital resources or technology, but I’ll take as broad or as narrow an answer as you’d like to give.

Jim:

I think you’ve hit on something really important, Ian, which is the historical model in government I think has largely been is, let’s hire and develop our own talent, and then have that internal government talent largely be sort of all source. So whether that’s an agent that’s able to go and kick a door at 5:00 in the morning, and then go write a 100-page complex T3 affidavit 12 hours later, that was always a challenge. And now that you’re talking about these much more complicated technical processes and even some of the tactical challenges involved with that, that really becomes hard. Then you have to extrapolate that out to now we’ve got from a government standpoint, we’ve got more data than we’ve ever had in our entire lives. And our ability to really fuse and exploit and analyze what we have becomes really hard, so you’re at sort of a data management challenge. You’re at a data science challenge. Then you’re at an expertise challenges. Then you need these really unique technologies of which there’s been appetite in the government because there’s been success with this sort of, we can build it ourselves.

And that gets really hard, really expensive, and you’re competing for finite resources, so it was great when at DOJ, you can go and find really successful software developers, data scientists. But when you look at what industry can pay, competing for those resources gets really, really hard. So I think if I had the opportunity to wave the magic wand, it’s really having very direct design by government on what that aggressive buildup of technology capability looks like. And it ends up being expertise driven, where we’re going to go and we’re going to sort of diversify and specialize that expertise to come and say, “We can’t do everything ourselves. We need people to come in and help facilitate,” whether it’s an enabled crypto analyst, or it’s a really specialized data scientist to come and build and develop and connect those data pools of data. That’s where I think it becomes really important to be able to do that.

Then the second is, and it’s one of the big dichotomies, quite frankly, between the intelligence community and DOD and federal law enforcement is that level of investment, is I think DOD and the IC is much more sophisticated and successful in some of their approaches because they’ve been funded to be able to go out and facilitate that expertise and technology and experiment, where they can go in really say, “We’re going to try three or four different technologies, give them a chance to really work and operate and let us understand what it looks like.” One of the challenges that faces federal law enforcement is because budgets are so tight, every decision has to be a winning decision and it has to work immediately. So I think that funding, patience, and really precise strategy towards this is what we, as federal law enforcement, want to be able to look like from our capabilities two years from now, I think that’s what I wish I could snap my fingers and make happen tomorrow.

Ian:

Well, Jim, I think that’s a fantastic place to end the podcast. I wholly support those two things happening. I think it would have dramatic positive impact on the position of law enforcement to deal with, with all these bad guys. It’s been super informative. Thanks so much for spending time with us today.

Jim:

Thank you so much, Ian. And once again, we appreciate the partnership with Chainalysis and the ability to go and do really extraordinary work all over the federal government together.

Ian:

Thank you, Jim.

Jim:

Thank you very much, Ian.

The post Everything You Need To Know About Crypto Cartels: Podcast Ep. 135 appeared first on Chainalysis.

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Disclaimer: The content above is only the author's opinion which does not represent any position of Followin, and is not intended as, and shall not be understood or construed as, investment advice from Followin.
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