November 10, 2022

Or, watch on YouTube

Mark Turnage, CEO and Co-Founder of DarkOwl, and Anusha Iyer, CTO and Co-Founder of Corsha, discuss how API Security professionals can benefit from darknet data in forming a more comprehensive understanding of malicious threat actor (TA) tactics, techniques, and procedures (TTPs) and providing effective detailed security recommendations, remediations, and product solutions. API Security related topics, like “API hacking”, “stolen API tokens”, and “API MITM attacks” are regularly discussed in detail in darknet forums, tokens sold and traded in underground digital marketplaces, and API exploitation code shared amongst threat actors.

For those that would rather read the presentation, we have transcribed it below.

NOTE: Some content has been edited for length and clarity.

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Kathy: Hi, everybody. Thank you for joining today’s webinar. 

Before we begin, I want to take a moment and introduce our speakers. Anusha Iyer, President, CTO, and Co-Founder of Corsha, and Mark Turnage, CEO and Co-Founder of DarkOwl, both of whom have many years of experience working in the cybersecurity industry. Anusha is a Carnegie Mellon alum. She started in the Washington, DC area at the Naval Research Lab. At NRL her focus was on reverse engineering and tactical edge networking. She started Corsha with a friend a few years ago and is passionate about helping organizations get API security right, and making security accessible, easy to adopt, and even self-assuring. Mark is a graduate of Yale Law School, Oxford University, and the University of Colorado, Boulder. He serves on numerous corporate and nonprofit boards, and is a private investor in technology, software, and manufacturing startup companies. He is also a senior advisor to the Colorado Impact Fund and a technology advisor to the Blackstone Entrepreneurs Network. And now I’d like to turn it over to Anusha to begin our webinar.  

Anusha: Thank you Kathy and thanks to everyone for joining. We have an exciting agenda today. We’re going to look at API security and specifically API credentials and what an API security related incident looks like. We’ll tell you a little bit about Corsha as well as DarkOwl. We’ll go into why API security is so critical, some mechanisms to combat some of the threats and the attacks that we’re seeing, how the darknet can provide insights on this problem. Then [I’ll] turn it over to Mark to talk about DarkOwl and what is the darknet, how DarkOwl can deliver darknet data and give you more insights and analytics into where information is showing up on the darknet. And particularly with respect to APIs, what are threat actors saying about APIs on the darknet? And then we look forward to your questions and final thoughts.

DarkOwl and Corsha actually met a few months ago at Black Hat and had an interesting conversation around the proliferation of API credentials and how they are increasingly being used to gain unauthorized access to systems and services.

Increasingly we are seeing these types of data showing up on the dark web and being leveraged to execute breaches against organizations, like Toyota. Recently Toyota was notified of a breach where they had an API access key for T connect system. That’s part of their connectivity app to give things like wireless access and so forth to vehicles, and apparently, they had inadvertently checked in a hard-coded API secret into a repo about five years ago. It’s been available for five years in a public repo. And then they just released that over 2,900 records were exposed since then, giving access to customer names, customer information, and so forth. This is one example of what the threat landscape looks like and what the implication can be of API credentials getting into the wrong hands.  

Similarly, recently FTX and 3Commas revealed that an API exploit was used to actually make illegitimate transactions, to FTX transactions. And this was done using API keys that were obtained from essentially users and phishing attacks actually accessing other systems. Right, so 3Commas, the platform came out and said that the API keys were obtained from outside of the platform, but certainly still pose the risk of being able to then be used off-environment, unauthorized, to then make financial transactions. These trades were basically from keys that were gained from phishing and browser information stealers. 

Kathy: We’ve had a questions come in on these first couple of slides. Someone would like to know, is the fact that APIs are being targeted – is that a relatively new phenomenon?  

Anusha: That’s a great question. It is an increasingly leveraged phenomenon. I wouldn’t say that it is new necessarily, but it is increasingly leveraged. Because APIs tend to be an underserved element with respect to cybersecurity postures of most enterprises. Increasingly organizations are relying on APIs. As they look towards digitally transforming application ecosystems into microservices, APIs end up forming the backbone of communication and application ecosystems. And further, more and more organizations are moving towards cloud, moving towards ephemeral scale, and that just creates a proliferation of environments where these credentials are potentially obtainable. 

Mark: And that’s echoed by what we’re seeing in the darknet where discussions around API exploits, API keys, stealing API keys, and selling them is a relatively new phenomenon in the darknet over the last couple of years. We’re seeing the same thing from the criminals’ perspective that Anusha is observing in real life.  

Anusha: Absolutely. I would come at it from the perspective that we see the movement of organizations using more APIs, but you’re absolutely right from an exploit perspective. It is fairly new. And it makes a lot of sense, they tend to be large types of information. With the automation it’s easy to lose track of what’s legitimate and what’s not. Great question.  

Another one, this one was actually a 2018 leak where it was the USPS API endpoint. And in this instance, it was more of an authorization vulnerability where if someone has a USPS account they could actually change search parameters and do a much more expansive search and essentially get records for an entire data set without being limited to exactly what they should be seeing. It’s both on the authentication side but also on the authorization side in terms of how these credentials are provisioned, leveraged, and so forth.  

With that, let me hop into Corsha and tell you about our story and why we’re going after this problem space. Both myself and my co-founder come out of the DoD intelligence world. We’re focused on: how do we stop these breaches? How do we prevent unauthorized access to sensitive systems and services? And [we] decided to start course at the intersection of machine identity and API security. A lot of our early customers are out of the Department of Defense and we are working closely with Gartner to define this category and to define the space, if you will. What we’re finding increasingly is that API authentication, authorization, and security in general substantially lags behind all of the resources, effort, and human capital, put into human identity and access management. Now we need to think of these machines as entities, and as the same first-class type citizens as humans because they are accessing systems and services at a far greater rate and at a far greater impact even than just humans logging into accounts. So we started CORSHA and we’re very focused on how we can help with this API credential and API identity problem. I’m probably telling a lot of folks that are online something that they already know, which is that today API secrets are just glorified system passwords. They are largely static, often shared, rarely rotated, and don’t have a lot of good hygiene around them. They get leaked, sprayed, and sprawled across tons of environments. Mark, I’m sure you’re probably seeing this on the other end in terms of where they’re coming from, whether it’s CIC/D pipelines, whether it’s things like logs, deployment or cloud platforms, or even team collaboration sites. We already saw an instance with Toyota of GitHub. But I would venture to say that most organizations, just for the ease of sharing, probably inadvertently have leaked API keys, even internally, across systems. Because today the model of authentication is largely static, they’re ripe targets for adversaries.  

Kathy: A question based off this slide: can’t secret managers like Vault or KeePass prevent these attacks from happening?  

Anusha: It’s a great question. To some degree. They provide a secure mechanism to store the keys internally. But, oftentimes these APIs live in hybrid environments even in the control of hybrid parties. You may have an API that you expose to a partner, a vendor, or a customer. You would then have to rely on them properly leveraging a vault or a password manager or maintaining good hygiene around secrets to access your systems and services. So that’s part of the challenge here, is that vaults and password managers tend to be very environment or entity-controlled specific. 

Because we’re using these static, essentially bearer model credentials, for authentication and even authorization, they are almost acting as proxies for machine identity. And the challenge is that they’re not very strong proxies because they are static and they’re difficult to maintain hygiene around. Whether it’s a key, or a token –like an O-auth token, a JSON web token, or even a PKI certificate –because they essentially prescribed that bearer model of authentication where “as long as I hold it, I can leverage it, it doesn’t matter where I’m coming from,” they turn into ripe targets for adversaries. I’ll stop here and say that when we talk about a machine, what are we really talking about? In our terminology we like to think of it from the zero-trust approach to it where it’s a non-person entity. Anything where you’re trying to access a system or service and there isn’t a human identity to back that access is where the API authentication approach breaks down a little bit. Whether that’s a Kubernetes pod, a docker container, VMs, even physical IoT devices –those tend to all be areas where static credentials end up getting leveraged in some way, shape, or form. Increasingly we’re seeing that these are the new attack sector vector that is increasingly in vogue. 

To give you a very quick overview of what we are doing at Corsha, what we’ve done is we’ve come up with an API security platform where we can pull some lessons learned from the human identity and access management space. And we’ve come up with a way to not only do dynamic machine identity for API clients, but then leverage that to do fully automated MFA for machines. Think of a second dynamic factor where you can make sure that API calls are going with one time use MFA credentials. This gives you a lot of those nice benefits that we’ve seen on the human side with MFA where now you can pin access to only trusted machines. Even if a key inadvertently gets checked into a public GitHub repo, if MFA is enforced as a secondary factor, you’re okay there. That’s the idea: to elevate these API clients as first-class citizens, regardless of what their form factor in a way that is easy to adopt, easy to integrate, no code change, so that it doesn’t place burden on DevSecOps teams and make their day to day easier. So that they’re not having to worry about things like credential rotation as part of their workflows. 

Just very high level, the essence of what we are trying to provide is security, visibility, control, even the ability on a fine-grained level to do things like start and stop access for a client. That’s a little bit of a difference with, say, this approach and say a vault. Because if you give an API key to a third party, you don’t necessarily have control over their vault. But with machine-driven or an identity-first approach to it, you can say, okay, from a control plane I’m going to dynamically start and stop API access for this collection of machines. And in that way have the expectation of access matching your threat surface. That’s a quick overview of CORSHA and the product and the problem space. I would love to turn it over to Mark and hear more about DarkOwl and what you’re seeing on the Darknet.  

Mark: Thank you. The darknet is an interesting place and DarkOwl was set up specifically to allow organizations to monitor the darknet for threats to their core missions. As you can see in the lower right hand corner, our clients include many of the world’s largest cybersecurity companies who effectively use our platform and use our data to monitor on behalf of their clients. We also work, as does Corsha, with various agencies in the US Government. What we do is we go into the darknet at scale and we extract data at scale from tens of thousands of darknet sites on a daily basis. We index that data, we store that data, and we make that data available to our clients and make it searchable to our clients.  

The question I get is what really is the darknet or the dark web? The two terms are conflated.  

We all spend most of our time in the surface web. What you can search for off of your Google browser is effectively the search web. It represents a relatively small percentage of the data that is available by the internet, in spite of the fact that if I search for any term I’m going to find thousands, if not tens of thousands of results on my Google browser. It’s actually a relatively small percentage of the data that’s out there. Most of the data is fire-walled and it’s in what we call the deep web. My bank account information is available to me because it’s authenticated, I have the credentials, but it’s not available to Anusha and vice versa. By volume, most of the data that’s available via the internet is actually in the deep web. We specialize in the darknet, which is below the deep web. The darknet is dark for two reasons. It’s dark because you can’t get there from your Google browser. It usually requires a specialized browser or specialized access. What it does is it obfuscates user identity. Oftentimes the traffic is itself encrypted. And because of that, it is the perfect environment for criminals to operate in. Anusha and I can conduct a transaction, we can have a conversation, we can conduct a criminal transaction, buy or sell exploits with each other, drugs – there are any number of other things that we can do. A law enforcement agency could be sitting in the middle of that and see the transaction go through and see the discussion and never understand who I am and who Anusha is. And if you add in cryptocurrency on top of that, we could pay each other in an anonymous fashion. As a result, the darknet has become a haven for criminal elements.  

At the bottom of that page, you’ll see Tor, I2P, Zeronet. Everything in red is data that we at DarkOwl collect from. We also collect from certain deep websites and some surface websites which enrich our darknet data. Increasingly, especially with the Ukraine-Russia war, these direct messaging platforms, such as Telegram and IRC are becoming destination points for criminals to operate in and we collect data from those as well.  

Kathy: Mark, before you move on, an attendee would like to know, how big is the darknet?  

Mark: I wish I had an answer to that question. We don’t know how big it is. We do know that Tor was the original darknet. It is now one of many darknets. The Tor project actually publishes data on users, number of users, numbers of connections to the Tor network, and number of sites.  

Year on year, it continues to grow significantly. There are a number of sites like I2P, Zeronet, Freenet, and these other new sites that have grown. We don’t know how large it is. We have been told that DarkOwl has the largest commercially available archive of darknet data that’s available. I couldn’t prove that to you because I don’t know what the denominator is. But we know that the darknet is growing in terms of both customer usage and transactions that take place.  

Very briefly, this is the kind of data that we collect. The data that most people are familiar with is at the bottom of this slide. We hold somewhere around 9 billion email addresses that we’ve collected over the years, 1.8 billion IP addresses. Those are oftentimes IP addresses or networks that are being targeted. A range of credit cards, crypto addresses, and so on. It’s a big database that we have, and it’s updated continuously and has been since we stood the company up five years ago. Then we make our data available by a number of APIs as well as a user interface for the analyst community as well. But to give you a sense, just in the last 24 hours we’ve indexed and put into our database 1.3 million documents. That gives you a sense of the scale of the type of documents that we’re dealing with.  

More relevant to this conversation, though, is the next slide, which is, what are we seeing in the darknet that is relevant to the issue around API security? And the answer is a lot. We’re seeing that threat actors in the darknet are discussing stolen API secrets, keys, they’re trading the session tokens, and they’re openly discussed in these closed communities. This is a hot topic for the criminal elements in these communities. There are man in the middle attacks, there are injection methods being discussed and actually traded. Anusha and I would get into one of these forums, we’re both criminal actors, and we would discuss how I mounted a successful attack using this method. And she’ll say, can I buy that method from you or can I borrow it? Let me try it on a target that I’m thinking about. We see that ongoing. JWT authentication bypass methods are oftentimes discussed in detail. That’s been a real wake up call for me personally, seeing how creative criminals are being in these methods that they’re developing. Tools are shared.  

Interestingly enough, and not particularly relevant, but the DDoS services are sold. API DDoS services are sold for cheap. One of the things we’re seeing broadly in the darknet across all sorts of threat actors is the migration of threat actors to actually selling out their services and renting them out on a monthly basis. This is just an example. We’ve seen Kubernetes targeted especially. It’s a distributed environment, so there are some vulnerabilities that the threat actors are using. Then hacking courses on and on and on.  

These are some screenshots of some of the discussions that we have seen in the darknet. In the upper left you’ll see this discussion around leaking API keys. In the middle of the slide, you’ll see Russian threat actors describing API keys as well as the secret keys and making the secret keys available. I think those were stolen. In the lower right. I love this. You know, we figure out a way to withdraw funds using API keys without access to the account itself and on and on and on. If you get onto our platform and search for any of these terms, you’re going to find quite a lot of discussion among the threat actors and the criminal gangs around this. And you’ll see data brokers actually selling keys. Selling actual access to networks. The conclusion is that Darknet is rife with discussion around the very threats that Corsha is targeting and that was set up to respond to. Anytime you see this kind of activity, any time you kind of see this discussion going on in the darknet, you know you’re on to something. So your customers made some smart choices here in new shows.  

Anusha: We appreciate that, Mark. I will say it is very interesting to see all of the discussion and the activity around Kubernetes. I think that might be even a fun double click into another session to do, because it is turning into a foundational layer of most organizations transforming their application ecosystems. It would be fantastic if we could get ahead of that.  

Mark: I’d actually like to talk to the founders back at Google. It was right around 2014, if I’m correct, about Kubernetes, and ask them whether they ever had a conversation around security right at the outset. Because most people, most developers won’t. And it’s not a criticism. It’s that just most developers won’t do it. They’re thinking about how to build a scalable environment for whatever their mission is. They’re not thinking about how five or six or seven or eight years down the road, somebody’s going to be trying to attack that environment.  

Kathy: We’ve actually had a few questions come in. One of our attendees would like to know: what specifically can be done from a security perspective to prevent an API attack?  

Anusha: Some of it is obviously having good hygiene around primary credentials. Having policies in place for things like rotation. Certainly using a platform like Corsha as a layered defense so that you have a way to uniquely identify and control each API client. Is a very sound approach to a lot of this activity that we are seeing on the darknet. Other things like making sure that API access is least privileged, so having notions of authorization in there. Just like when you have a given user, you give them roles, and not all users have access to the same information and services on the system, APIs and API clients have to be dealt with the same way. And having ways to revoke secrets and revoke access are very important. It’s about drawing a lot of those parallels that we have with human identity and access management but into the world of APIs. 

Kathy: Thank you. We also have a question of: how can security or engineering teams get better visibility into how their API secrets are being used? 

Mark: One way to do that is to use a platform like DarkOwl’s platform to actually monitor the environment on an active basis. Oftentimes, you will see threat actors discussing targets by name or by IP range or by other things. Look in the upper left hand side of this slide, right there  is a discussion around a very specific key from a very specific 

My point is, any time you’re thinking about security more broadly, there are a number of hygiene elements that have to go into place. One of those hygiene elements is monitoring this environment where criminals are actually plotting attacks in a wide variety of different contexts, not only in the API environment. We see active threats, active exploits under way. We see targets being identified and threat actors saying, all right, that’s great, I’m going to hit them. You have to have some eyes on that environment.  

Kathy: Thank you. We did have one more question come in, and that is, what should a team do today if an API secret is compromised?  

Anusha: That is where having a good platform for observability in place is really important because you want to know where that API secret could have been leveraged right and have the ability to quickly revoke and rotate it. It’s both understanding impact of the leakage or the stolen credential and then mitigation strategy of how to revoke it, how to rotate it, with obviously a little downtime as possible. I think for observability using a platform like DarkOwl is really helpful because you can see the extent to which it may have been leaked or compromised as well.  

Mark: Thank you, Anusha. It’s a pleasure doing this. Let’s do another one in the future once we find more threats.

Anusha: Absolutely. That would be fun. Thanks so much for the time. And thanks to everyone for listening in.   

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About Corsha:
Corsha is on a mission to simplify API security and allow enterprises, developers, and DevSecOps teams to embrace modernization, complex deployments, and hybrid environments with confidence. Our core technology is dual use, designed for widespread adoption, and easy to configure and deploy to both commercial and government customers. Corsha has a strong engineering team with deep expertise in distributed ledgers, cryptography, security principles, orchestration technologies, and software design. Contact Corsha.

About DarkOwl:
DarkOwl uses machine learning to automatically, continuously, and anonymously collect, index and rank darknet, deep web, and high-risk surface net data that allows for simplicity in searching. Our platform collects and stores data in near realtime, allowing darknet sites that frequently change location and availability, be queried in a safe and secure manner without having to access the darknet itself. DarkOwl offers a variety of options to access their data. 

To get in touch with DarkOwl, contact us here.

November 08, 2022

Or watch on YouTube.

David Alley of DarkOwl FZE and Ivan Kravstov of Social Links dive into the topic of harnessing OSINT to expose illegal trade on the darknet. They outline the black-market landscape of the darknet and showcase a range of methods for fighting illegal trade and approach the topic of darknet marketplaces from different angles. In this webinar, they cover:

• The nature of the dark web and how it is accessed by users
• The functional make-up of darknet marketplaces
• User deanonymization methods
• Advanced darknet data extraction and analysis techniques

Attendees learn how to break through the perceived anonymity of the dark web and crypto transactions to identify criminal actors and track illegal trade and illicit activity.

For those that would rather read the presentation, we have transcribed it below.

NOTE: Some content has been edited for length and clarity

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Ivan: Greetings everyone, today we will be hosting a joint webinar with David Alley of DarkOwl FZE and the topic will be countering illegal trade on darknet marketplaces or more broadly dark web research in general. 

David could you tell us a bit about DarkOwl?  

David Alley: Absolutely. It’s really great to be here and thank you to everyone for joining from all around the world. I know that we always fight the various time zones to get everyone here, so a special thanks to the Social Links team for hosting this webinar. They’ve been super helpful in getting this excellent presentation together for us.  

A little bit about DarkOwl – we are American company, and our headquarters is in Denver, Colorado also known as the Mile High City. We originally started off as a cybersecurity company with a focus on penetration testing. And at that time we would do research on the darknet to see if we could find credentials to help with our pentesting work. We were really successful at that, we had a very high rate of penetrations for the pentests. We said, “why don’t we change this and actually go into being just a pure darknet company only?” That was really the birth of DarkOwl. Since then we’ve had a lot of great team members with us at DarkOwl and we’ve built a very good collection capability for us to go onto the darknet and pull out that data that is really difficult to get to.  

We have a great collections team that does all of this hard work and makes it much easier for our partners like Social Links to do the next part. Which is, that once they’ve looked at that data, to make sense of it and decide what does is it mean? And how do we use it? And how do we fight crime that is emanating from the darknet? 

We have a couple of claims to fame. The one we use the most is that we have the largest commercially available darknet data lake in the world. And that’s just because we have been doing it for longer than everyone else. We’ve had some very special team members over the years that have had a very unique access and understanding of the Tor Network. At one point we actually had the co-founder of Tor on our team and so it’s a really unique company. We are highly niche and highly skilled and that’s why great companies like Social Links and ours like to work together because we are complimentary. We work a lot with OSINT analysts as well, but we also provide APIs and Datafeeds for partners and that’s how we work with Social Links. I think you’re going to be pretty amazed at what the team has to show you today. I’m always impressed with what they’re able to come up with; they have a superior team. Leveraging great data from DarkOwl with great analysts from Social Links you’ll always be happy with the results. I’ll turn it back over to you Ivan. 

Ivan:  Thank you very much for the introduction David. A bit about us: the company was founded in 2015 we have 80 + employees at the moment with HQ in the US and EU offices in the Netherlands and the R&D office in Riga, Latvia. What we do is provide software for data-driven investigations. You can see that we have a good rating on Gartner Peer Insights and that we have received a number of 
industrial awards in the past years. 

Here we have a very brief slide about the average pricing of various goods on the dark web. Ranging from stolen credit cards to out of the box ransomware Trojans.  

A concept that I’m sure everybody is familiar with is that there is a division into what is known as the clear web or the surface web, something which is indexed by conventional search engines, then there is the deep web which can include many different things that are not [indexed by conventional search engines] and that it takes a bit more effort to find and then there is a space commonly known as the dark web which include the Tor Network but also additional ones such as I2P, Freenet, and Zeronet.  

The general principal of Tor browser network is that the traffic goes from the user through several nodes and then reaches a specific server at the end. The current total Tor network bandwidth is 400 gigabytes per second.

One of the technologies that is also utilized quite often within the platforms of communication is PGP encryption. The basic concept being that the user sends an encrypted message that can only be accessed and read with the use of a private key held by the recipient.  

Now here we can see the boost of darknet marketplaces revenue from 2011 with the first precedent being the Silk Road up to 2020 [revenue] which is quite substantial.  

The products and services available on those marketplaces range from drugs to tutorials, forgery, various kinds of illicit services, malware hosting, and fraud. The majority of those being drugs. 

The general principle of how a marketplace works is that a buyer exchanges currency for any kind of specific cryptocurrency accepted by the marketplace. Which is predominantly Bitcoin at this moment but there is a shift towards alternative ones such as Monero or Z cash. The buyer then transfers the 
Bitcoin into markets account and makes a purchase. The crypto is  held in the market’s ESCROW account until the order is finalized with the market taking a commission. After the finalization of the deal the vendor is paid. Then the vendor may move the Bitcoin from the market account and potentially exchange it. 

Here we see an infographic of types of entities receiving Bitcoin from dark web sources which can be KYC and for exchanges enforcing KYC or exchanges more liberal with their KYC processes. Those can also be mixing services and other entity types.  

David, if you could tell us about DarkOwl’s differentiation?  

David: Absolutely. As we’ve seen here we’re talking a lot about the crypto piece. And I want to talk about how DarkOwl differentiates itself and helps you with this. It is because we are able to go into these markets that we’re talking about today and were able to pull that data out for you. A lot of the Blockchain tools that you’ll be familiar with will allow you to see various wallets as they’re being tumbled and where they’ve been mixed or how they’re being exploited. But what they have difficulty doing is tying wallets to a very specific illegal activity. And that’s one of the main things that makes us different for these types of investigations. We are continuously out there crawling these darknet sites and these markets that we are in. Someone asked a question: how do we differ from our competitors? It’s just a real question of scale and scope. Many of them are in about 400 sites and we’re collecting from over 95,000 sites and about another 20,000 to 30,000 mirrors every day. It’s this massive amount of unmatched darknet content discovery that we’ve got and inside of that content is where all of these cryptocurrency wallets are which can be tied to illegal activity. You want to buy your MDMA in London? Here you go – use this bitcoin wallet or this Monero wallet.

I second the comments that we’re seeing a shift from Bitcoin into some of the other coins out there. We’ll even pick up coins in our collection that are not even on the chain yet. They’re brand-new wallets that are being used. We’re seeing that shift away from the traditional way of using the same wallet over and over to now criminals will create a new wallet put it up on the site for their drugs or their CSAM material or whatever it is they’re trying sell and have the payments into the air before the Blockchain tools can even detect them. You’ll see coins get recycled and because of our unique archival capability it goes back to almost 9 year’s worth of data. You can also do those deep investigations into darknet transactions that happened years ago. All of that together gives you the content that makes investigations very strong and that combined with the ability to do leak analysis as you can see from our Social Links partners is a very powerful tool. To give you an idea of what we actually have in the collection, it’s about the numbers. 

It is a lot of Tor. Tor is the largest of the darknets. We also have a very large collection of from I2P and from ZeroNet. Those are the three major darknets that we collect on. And there’s some very technical reasons behind that. We also are having a lot of success picking up cryptocurrency transactions off of Telegram channels. As we know Telegram is very popular with a lot of different hacking groups and black hat hacking groups. It’s easier to use than a darknet channel. We see that a lot of hackers are also gamers, and they use Discord for communications. We see some in paste as well. What should really be focused on [in this slide] is the lower right-hand corner. That’s 347 million cryptocurrency wallets pulled out of our darknet collection. It’s a pretty big number, and every time I see a cryptocurrency wallet on a darknet site it’s always doing something bad. I’d say it’s a 99.9% probability that if you’re using Social Links and you pull out a cryptocurrency wallet from the darknet data, you’ve already done one of the hardest steps which is identifying some form of suspicious activity. I’ll turn it back over to our Social Links partners to take you through the rest of the demo.  

Ivan: It may make sense to note that with Telegram and Discord channels there is indeed substantial overlap. Much more substantial obviously then with the traditional mainstream social media platforms. Telegram and Discord aren’t really called social media, but they have a significant social networking element. Telegram especially in the past few years. It is about cybercrime groups but also apart from that it could just be local, regional, or even macro-regional drug vendors. It could be people engaged with child grooming, especially on Discord, or extremist groups as we previously covered in one of our webinars with a German expert on extremism research. Now we will go into the actual examples that we have. 

First we should dedicate a few minutes to talk about the method of dark web research. In this case that would mean focused on researching an individual. It makes sense to use all of this in conjunction.  

From the username we can get the specific platform within this interface where the vendor or forum member is present. That can also give us insights into their stated or observed affiliations. Those are the payment methods, the posts and threads and the products. From the posts and threads you can examine the topics discussed in the details which can also tell you more about what exactly they are doing, what kind of merchandise they are dealing in, what kind of categories, and if they have a specific focus. As well as the speech patterns of the idioms and idiosyncrasies used by the individual and the shipping locations. And of course, the products also tell us more about the proper categories and sometimes product cards can contain contact details within them. Objects within this schema such as the speech patterns, the stated shipping locations of the products, the affiliations, and the specific platform can point us to assumptions about a certain region or macro-region.  

For example, there is a higher probability of a vendor or a forum member on an Eastern European marketplace to be from somewhere in Eastern Europe. Payment methods can be different as well as various types of e-money, but here we’ll focus more on cryptocurrency addresses. A transaction derived from an address can tell us about the interactions it has with other addresses for groups of those. And it can tell us about the services that they are using such as mixers or exchanges. A mixing service may also have theoretically some kind of interactions in some kind of partnership program for a specific marketplace. They can also be mentioned in various reports or forums. All of those can possibly lead us to digital breadcrumbs, and that in conjunction with the assessment of the presence of the user in other forums and marketplaces and the way their personality may be reflected in their online behavior and the kinds of merchandise that they are dealing in and the kind of payment methods that they’re using is all part of an attempt to create a digital profile of an individual.  

Now here we will start with the first example where we will go from an alias. We will run our first transform search for users under this alias. Here we can see some details in the properties, one of those being the side name Tochka Market. “Tochka” is a Russian word standing for point or place. We search for the products related to this vendor and we also extract their PGP open key which is quite often used by vendors. Next, we will use the products and extract the locations they are to be shipped to and from. 

We can see here that those are mostly recreational drugs shipped to the United States. From a PGP open key it is sometimes possible for us to go to the email address. Not in a hundred percent of cases, which can also be said about some of the other methods that we will be applying here. Here we see a Gmail and from that we can further try to see if there are any social media profiles and any accounts connected to that email address. There is also the possibility to get reviews if it’s a Gmail account. We can see that there are accounts within Facebook, Firefox, Gravatar, Pinterest, Samsung, and Twitter connected to the email and we see several profiles within Gravatar, LinkedIn, and Skype from which we can extract additional details. In reviews we also see a cannabis dispensary seemingly located in the United States and a bar in Cameroon which matches with the location that we see here within the LinkedIn account [redacted account name] connected to the Gmail address. There is also a post promoting the sale of marijuana on a surface web source stated by the account holder to be safe and secure. Now here we can use some of the Maltego functionality to go into more data about that specific domain. The WHOIS data gives us the name of [redacted name] as a registrant and the company name [redacted company name]. [Redacted names] are both something that we have seen within the social media footprint derived from the email address. Now of course an analyst won’t be as lucky as in this instance in 100% of cases, but this is real data related to a real individual. It is possible because people do tend to make mistakes.  

Now we will go through another alias. This [alias] gives us 4 accounts with the same username and it’s something that vendors to do to maintain a commercial reputation with the customer base. Now we can ask for specific platforms. We can see the Dread forum, the Hub forum, the Apollon market, and the Wall Street Market. Now we also see a single PGP key used by three out of four of those accounts and we will further ask for the posts and products. We can see that there is a certain focus on Europe. In this instance the goods are more likely shipped from Europe to locations worldwide. The principles of working with the posts are  similar to the way a user of Social Links Pro or a SOC tool in general can work with social graphs. The graphs of social interactions within the digital space. From each of those we go into the thread. From the thread we can go to the other posts within it, and the other users that have been participating in those conversations.  

This is just at stage of gathering data and an analyst working on a real case will of course face the necessity to analyze this communication in depth. That’s why there’s a capability here to download the content within those posts and save the text content as a text archive. Now here we see a Proton mail account- [redacted email address] so they seem to be more conscious about their digital footprint and security, but potentially we can try to search for this alias in the social media platforms available. Here we’ll try with an Eastern European platform because [redacted name] [the alias] is obviously a reference to the famous assault rifle. Here we got an account with just the cat as a picture under the name [redacted name] and while it’s not something that we will state and something that we will accuse this person of, it could be a coincidence or it could not be a coincidence. The account is not very informative, is closed, and has a profile picture of a cat. So here we are less lucky than in the first example. In some instances it’s even more obscure. Here we see an individual with the alias [redacted name] focusing on the European Union. They have two email addresses and a statement in the product description that there is a possibility to contact the vendor on Discord. We see that there is a Discord account connected to their Proton mail address, and also a Skype account which states the location as Germany. This is all on the level of analyzing people and individuals or small groups of people, because several individuals can be behind one username.  

This can also be done on a macro level. We can take several capital cities or countries within a certain macro region such as Asia-pacific or Latin America and run a search into the full spectrum of dark web sources available to us to see which products are shipped to and from those locations. Here we see that some countries have more activity within the spectrum of available sources, some countries have less, and we can potentially look for vendors that are focused on two or three specific countries at once. We can also see which marketplaces are more active within a given region. Here and in Latin America Tochka market is quite active. Additionally the Apollon and Nightmare markets and then several other ones have much less activity.  

Now of course it makes sense to talk a bit about the cryptocurrency aspect within dark web research. Several of those graphs are something that we’ve shared previously in some of our previous webinars. The methods can be split into two sets: passive intelligence and direct engagement. Passive intelligence may include open-source and social media intelligence, the traditional following the money approach, and the enrichment of the initial entered data that the analyst or potentially a victim of a crime may have. Direct engagement is something that implies using custom digital avatars for social engineering and also in the case of enterprises, or state organizations, offensive security procedures or threat intelligence. Some of those methods are more customary to certain kinds of professionals, analysts, and organizations than others but in the end as is the case with any kind of investigation it is all about connecting the dots, the seemingly not connected entities in a broad sense that word. 

Here is a small reflection of the situation within the Bitcoin ecosystem. There are a number of addresses here, some of those belonging to militant extremist groups such as the Palestinian Al-Qassam Brigades or Hay’at Tahrir al-Sham the fellowship operating in Syria. Some of those belong to dark web vendors such as Ross Ulbricht of the founder of Silk Road. Alexandre Cazes founder of Alphabay, or the administration of the Wall Street Market that exit scammed in 2019. Some of those were because of law enforcement, some of those were ransomware groups, and some of those were to legitimate exchanges. 

A way to perform this attribution to be 100% certain that a specific address belongs to a specific individual or a group is to run searches into the social media and dark web space and also into data that is provided by vendors such as DarkOwl And I must say that DarkOwl provides fascinating amounts of information of fascinating depth, and a number of these were done with the help of DarkOwl as well. Social Links is focused specifically on the Tor Network while DarkOwl, as David has mentioned, also pulls data from other sources such as I2P and Zeronet. Once you get this kind of entity you can further run the transform to get to the details and then examine the contents of those entities. The source of the networks and the date and time are also stated within the properties. 

Here we have another simple example of building a timeline with the timestamps from within the transactions related to a specific address and the timestamps of the mentions of that address on a dark web forum. 

All of this above is related to the situation around the exit scam performed by the Wall Street Market administration. You can see that all of the transactions and all of posts take place in the second half of April 2019.  

If we talk about profiling, there been there are a number of quite famous cases that have been solved by law enforcement and by analysts within those types of organizations related to de-anonymizing an owner or a senior administrator of a dark web marketplace. There is the famous Ross Ulbricht who was using the alias Dread Pirate Roberts and a clear web alias Altoid which was the key thing that led the American law enforcement towards then. We can gather the different data from the full spectrum of sources or potentially we could very carefully try to profile the individual based on the way they interact with the customers, the way they interact with vendors, the way they behave online within the platform. Or we can try to profile those people in retrospect to see what is common between the individuals who have been involved in such activities that have been uncovered historically. We can see that the portrait of the criminal has changed over time to this day in 2022. All of those –Mr. Ross Ulbricht, Mr. Gal Vallerius and Mr. Alexandre Cazes are educated individuals in different fields. For instance, Mr. Cazes has a degree in computer science. They tend to share certain views such as being Libertarian. Libertarianism was something very much associated with the motives of the founder of Silk Road, but similar motives can be speculated about other members of that community. In the case of Mr. Alexandre Cazes, the key input was an email address that was a source of messages to newcomers within the Alphabay Marketplace which was 10 times the size of Silk Road at its peak. The support emails were to new vendors and new members.  

Here we can try an example of enriching that identifier to build this graph from scratch. This can be done with the help of something called a machine within Maltego which can automate those queries under a specific logic.  

Here at this moment it gives us an IP address from a leaked database, it gives us an account on Gravatar –[redacted account name] an account on Skype, and a number of email addresses with similar passwords. And also a number of additional database records that contain the email in the string. The IP address is further resolved into a Canadian netblock and that is resolved to an autonomous system number. Now we can try to do the same with the second email that we have here. This is giving us two Skype accounts and two additional IP addresses. Of course, we can run a search into the data lake of DarkOwl. From which we will try to extract additional details. Here this gives us the family name, it gives us the name of another individual, and a number of IP addresses and phone numbers. The IP address issue may be just a minor technical problem on the side of Social Links with integrating this, but you get the point. This gathering and structuring process is something that is done in retrospect, so this person has already been uncovered, already been arrested, and already committed suicide while in jail. But I think it’s  obvious how beneficial industrial automated tools such as DarkOwl and Social Links can be in researching such individuals and investigating and doing criminal intelligence within those types of sources.  

With Oxymonster, the alias that belonged to Mr. Gal Vallerius an Israeli-French individual, the initial input point that investigators had was this vanity Bitcoin address for which they traced output, a number of outgoing transactions to a number of addresses all leading to an account on a peer-to-peer platform [redacted address][.]com under the username Vallerius. That is exactly what we were talking about when we said speech patterns and idioms and idiosyncrasies. The investigators further compared the speech of Mr. Gal Vallerius on Instagram and Twitter accounts that are no longer in existence but we do have a Foursquare profile here with that of the user Oxymonster and there was a certain match in the patterns. Now here we can extract additional things from the DarkOwl entities that we have as well.  

In another example with an email of Mr. Ross Ulbricht which was found from one of the posts on the Bitcointalk forum which was initially found a by matching the username Altoid with the first-ever mention of the Silk Road marketplace on [redacted address].org. We can also try to use those transforms to see what is connected to those identifiers.  

Here we go to what is more commonly associated with Social Links. Social Media intelligence is our strongest side so far even though we’ve diversified the sources that we have and the methods available for them in the standard procedure of mapping out the digital footprint of an individual. If we return to the initial logical schema of those processes it is a necessity not just to focus on the user account or on the group or on the marketplace within the Tor Network or any of the other darknets. The process of investigation and analysis will take the analyst, if they’re lucky of course, into other kinds of domains which may include conventional social media. 

There is another instance for a potential use of OSINT tools in a similar scenario, but it would make sense to use in the case of the Berlusconi Market and their administrator John Kohler Racino . The way that they were uncovered was something far more in line with the traditional work of law enforcement. They were eventually closed down as a result of the operation by the Italian Guardia de Finanza, but it was the result of operatives having ordered number of goods from the marketplace as part of an experiment and having noted that they all came from the same post station from within a small town in Italy. Here we see an example of what can potentially be found from the usernames and the accounts under the usernames that were operated by Mr. Lucino. There are two of them: one that had presence in the Dread forum and was involved in discussions around the Berlusconi Marketplace and another one on several marketplaces including Berlusconi, two of those sharing a single PGP open key with the pattern of the goods being shipped from Italy worldwide. There is some output from the Social Links identity search engine that also gives us a number of email addresses and IP addresses. Operations such as this can be advanced with the use of DarkOwl. 

That is all of my part so far with the functional demonstration of the capabilities.

Another topic which we haven’t really focused on today but which is quite relevant here is the usage of those kinds of tools and the exploration and the research by professionals in the field of corporate security. The cases that we’ve shown now –they’re somewhat more in the domain of law enforcement work and criminal intelligence analysts, but the monitoring of sources, aggregating leaked databases, data breaches, are also a topic relevant to the practice within the corporate sector.  

How we use those tools to detect human trafficking is a very good question and there is an organization that we have done a webinar with previously called the Anti-Human Trafficking Intelligence Initiative with very brilliant people working in that area. They have a solution of their own that works by a slightly different principal than Social Links and DarkOwl, but yes such solutions do exist and such practices do exist and they have been successful uncovering numerous instances of human trafficking and the distribution of CSAM.  

David: Absolutely. Ivan, I just want to jump in and congratulate you on a really excellent presentation. As far as the human trafficking pieces, we are seeing a growth in the kind of communications and coordination that happens on the darknet for human trafficking and even more broadly for the CSAM types of materials. I would like to talk about one of the other questions that has been brought up, and it talks about the companies that have been involved in ransomware incident response. The amount of chatter that we see happening on the darknet for the different ransomware gangs has increased exponentially over the last two years, and we’ve tried to focus on it for quite some time. We’ve really seen how well they have taken their software to market. You can see that ransomware as a service programs have been proliferating widely through  markets on the darknet. As far as identifying specific ransomware families, I think we have about 30 or 40 of them that we’ve already curated. Including what cipher they are using, when we first saw them appear on the darknet, and you can use it to gather some of the pricing data that you need.  

Ivan: Thank you for that David. One thing that is easy to see even from this simple graph which is just a reflection of the current state of affairs in the cryptocurrency industry and specifically in the Bitcoin ecosystem is that it is very Wild West-esque at the moment. [There is] the obvious pattern of large a number of interactions with people involved in terrorism and ransomware and the trades in illicit goods in the dark web space and human trafficking and CSAM as well, although those two categories are not reflected here. The people at the Anti-human Trafficking Intelligence Initiative know much more about that topic. Interacting with legitimate exchanges such as Binance, Gemini, and Coinbase.  

David: There’s a question from Andrew and it says: do DarkOwl and Social Links have the tech to crawl the deep and dark web? Almost all of our collection is technical-automated. There is a combination of techniques that you use to gain access, but then you cannot collect at scale just using human beings so it’s a combination of both. We use both for this kind of collection. Then there was one question about risk management targeted profiling and Customs control. Absolutely, specifically for the for the drugs portion…most of drug shipments that we see happening on the darknet are international transactions. The largest shipper of drugs worldwide is the United States Postal Service because it takes a federal warrant to get into a box being shipped. We see some law enforcement agencies do controlled buys. They use these tools to identify who the vendors are, how do you enter and interact with them, and it’s about the speed – how do you get ahead of this and then do controlled buys. When it comes into your country you will figure out which one of your Customs agents is taking bribes from people to let those packages in. It’s both useful for looking at criminal activity and also from an internal counter-intelligence perspective. 

Ivan: Thank you David and thank you for visiting we are always glad to see you here.

David:  Andrew we don’t leave you hanging out there I see your question, you’ve asked how they might go seize the ransomware payments. I don’t have any direct knowledge of how that happened, but most of these payments have to go through some form of exchange to move the money around and they likely had access to one of those exchanges that could tell them. Because remember there are some exchanges that are working with and cooperating with law enforcement and international law enforcement agencies and if they get a valid warrant from a law enforcement agency to block the transaction, they can do that. Just like it would work in the international Swift system for blocking bank transactions through the Federal Reserve Bank of New York. I would imagine that probably something like that is how it was done.  

Ivan: Yes, I actually think there was an Eastern European mixing service there.  

This is it on our part for today thank you everybody very much for participating and we hope that you will contact us to talk with us further about how our solutions can be implemented into your business processes. We will be very glad to see you and will be expecting you on our further webinars that are to come. David thank you for co-hosting.  

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About Social Links

Corsha is on a mission to simplify API security and allow enterprises, developers, and DevSecOps teams to embrace modernization, complex deployments, and hybrid environments with confidence. Our core technology is dual use, designed for widespread adoption, and easy to configure and deploy to both commercial and government customers. Corsha has a strong engineering team with deep expertise in distributed ledgers, cryptography, security principles, orchestration technologies, and software design.

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About DarkOwl

DarkOwl uses machine learning to collect automatically, continuously, and anonymously, index and rank darknet, deep web, and high-risk surface net data that allows for simplicity in searching. Our platform collects and stores data in near real-time, allowing darknet sites that frequently change location and availability, be queried in a safe and secure manner without having to access the darknet itself. DarkOwl is unique not only in the depth and breadth of its darknet data, but also in the relevance and searchability of its data, its investigation tools, and its passionate customer service. Our passion, our focus, and our expertise is the darknet.

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