"You Can't Track the Token. But You Can Track the Mistakes."

In 2017, global investigators quietly launched a case that would unravel one of the darkest corners of the internet. Buried behind layers of Tor routing and pseudonymous Bitcoin payments, Welcome to Video was a child sexual abuse material (CSAM) marketplace operating out of South Korea. It didn't just trade illegal content; it industrialized it. Access came at the price of a few thousand satoshis, and buyers believed their transactions would disappear into the blockchain's fog.

They were wrong.

Using only open-source blockchain data and forensic techniques like clustering, investigators traced payments, linked wallets to names, and kicked down digital doors in 38 countries. In the end, 337 users were arrested (U.S. Department of Justice, 2019). Not with spyware. Not with surveillance. With math.

From Crime Scene to Pattern Recognition

The Welcome to Video case revealed that blockchain transactions, when analyzed correctly, can expose hidden criminal networks. But the question remained: how did investigators know where to look? This brings us to one of the most pivotal discoveries in blockchain analysis—a method born not in a government agency, but in academia.

The Myth of Anonymity Meets a Spreadsheet

Back in 2013, long before most of us had heard of Bitcoin, a doctoral student at UC San Diego asked a deceptively simple question: how many people are actually using this thing?

What Sarah Meiklejohn found was chaos: 12 million addresses, nearly 16 million transactions, and no obvious way to tell which wallets belonged to whom. But she had a hunch. If Bitcoin was pseudonymous, not anonymous, then patterns had to exist. So she started digging, transforming the entire blockchain into a massive searchable spreadsheet and running queries like a digital archaeologist brushing sand off buried bones (Greenberg, 2022).

That hunch became a breakthrough. Through behavioral patterns and transaction structures, she realized there was a way to collapse the illusion of anonymity. It started with a rule of thumb.

When Piggy Banks Talk

Investigators call it a heuristic, a pattern you can follow even when the data won't speak directly. One of the most effective is called the common input ownership heuristic. Here's how it works: if multiple Bitcoin addresses are used together to fund a transaction, odds are they're controlled by the same person. Think of it like someone paying for lunch using two different credit cards. You wouldn't assume they borrowed both from friends. You'd assume they're both his.

But Bitcoin has another quirk. Andy Greenberg calls it the "piggy bank problem" in Tracers in the Dark. Every Bitcoin address is like a sealed piggy bank. If you want to pay someone 6 BTC from an address holding 10, you can't just scoop out what you need. You smash the whole thing. The 6 goes to your recipient. The leftover 4? That goes to a change address, a brand-new piggy bank that your wallet creates just for you (Greenberg, 2022).

To anyone watching the blockchain, both outputs look the same. But with just a bit of logic, you can often tell which one is the payment and which one is the change. If one of the outputs is a brand-new address never seen before, there's a good chance it's the change address. And if it's the change address, it probably belongs to the sender too.

Link the inputs. Spot the change. Group the addresses. That's clustering.

Peeling the Onion: Heuristics That Push Attribution Further

Here's why this matters: being able to tell payment and change outputs apart is fundamental to a successful blockchain investigation. In any UTXO-based transaction like Bitcoin, identifying which output is the actual payment and which one is the change is not just a technical detail; it can determine whether an investigation moves forward or ends up chasing its own tail. If an investigator misclassifies the change address as the recipient, the trail can go cold fast, wasting hours or even days tracing the wrong cluster. On the other hand, correctly identifying the real payment address puts the investigation on solid ground, revealing downstream flows and potential real-world identities. This distinction becomes a critical skill that separates seasoned investigators from those chasing dead ends.

The common ownership heuristic gets you in the door. But once you're inside, things get murkier. Criminals aren't always sloppy, and Bitcoin doesn't hand over answers. It hides them in plain sight. That's why blockchain investigators don't just rely on one trick. They stack heuristics like tools in a forensics kit, each one sharpening the picture of who's actually behind a wallet.

Nominal Spend Heuristic

A lot of people think the smallest output in a Bitcoin transaction is the payment. But that's not always the case. Wallets are designed to find the most efficient way to spend the exact amount needed while keeping fees low. So instead of looking for the smallest number, investigators ask a better question: are all the inputs required to cover one specific output? If yes, then that output is likely the payment.

For example, if the inputs add up to 3 BTC and the outputs are 0.5 BTC and 2.49 BTC, the 0.5 is likely the payment and 2.49 the change. But if the outputs are close in value—like 1.45 BTC and 1.55 BTC—it gets tricky. Switching to USD values sometimes helps clear things up. The goal isn't just to match numbers. It's to spot the intent behind the spend.

This method isn't perfect. Wallet behavior can vary, and some transactions are crafted to mislead. But combined with other heuristics, it's a reliable starting point for figuring out who paid what, and to whom.

Change Address Type Heuristic

Not all Bitcoin addresses look the same. Legacy addresses start with "1," nested SegWit with "3," and native SegWit with "bc1." Most wallet software prefers consistency and sends change back to the same address type. If a transaction's outputs include one address that matches the input type and another that doesn't, there's a good chance the matching one is the change. This heuristic is documented in Meiklejohn et al.'s foundational work (Meiklejohn et al., 2013).

Multisig Heuristic

Multisig wallets require multiple keys to authorize a transaction, which adds an extra layer of security. These addresses have a distinct script type that makes them easily recognizable on-chain. When a transaction involves a multisig input or output alongside standard addresses, analysts can use that contrast to infer wallet structure or organizational control. If multiple transactions show consistent movement between a particular multisig and a standard address, it can help cluster them as being under the same entity's control.

Round Payment Heuristic

Humans are messy, but when we pay others, we like clean numbers like 0.1 BTC, 1.0 BTC, or 5.0 BTC. These round figures stick out on the blockchain. The less-precise outputs are often change. Round numbers suggest external payments, while uneven leftovers point to self-change.

Self-Change Heuristic

Despite warnings about address reuse, it still happens frequently, especially in older transactions or lazy wallets. When change is sent back to an address that's already appeared in the user's history, that's a huge clue. Meiklejohn's study identified this behavior and used it to tag massive address clusters across Silk Road, Mt. Gox, and other darknet markets (Meiklejohn et al., 2013). In forensic cases like Welcome to Video, this heuristic helped connect clusters when change addresses overlapped with previously used ones (Greenberg, 2022).

Don't Get Too Comfortable

These heuristics are sharp, but they're not gospel. They're patterns. Educated guesses. Good ones, but guesses nonetheless. All of them rely on predictable behavior, and criminals, when they're smart, stop being predictable.

That's where CoinJoin comes in. CoinJoin breaks the rules. It takes multiple users, mashes their payments together in one transaction, and jumbles the inputs and outputs so the usual tricks don't work. It's like walking into a crime scene and finding everyone's fingerprints on every surface. Wallets like Wasabi and Samurai have made CoinJoin more accessible, and forensic tools struggle to untangle the aftermath without additional context or external identifiers.

In the next post, we'll dig into CoinJoin, what it is, how it works, and why it remains the closest thing Bitcoin has to a true disappearing act—for now.

The Myth of Total Decentralization

"Decentralized." It's Bitcoin's battle cry — the promise of a system where no single entity calls the shots.

But here's the visual that bothers skeptics: five mining pools controlling over 60% of Bitcoin's hash rate. It looks like a cartel — until you look closer and understand how mining, custody, and protocol governance actually work (b10c, 2025).

Most large wallets? They don't belong to whales. They're held by exchanges on behalf of millions of users (BitInfoCharts, 2025). The power looks concentrated until you realize: Foundry's 30% hashrate serves institutional miners (Hashrate Index, 2025); AntPool's 'proxy pools' mask coordination, effectively consolidating control under a single entity (b10c, 2025). Decentralization isn't binary — it's a spectrum of checks and balances.

The bigger misunderstanding is this: decentralization isn't about who holds the coins. It's about who can change the rules. And in Bitcoin, that power is off-limits — even to billionaires.

Who Really Controls Bitcoin?

On paper, Bitcoin's ownership and mining power look centralized. As of 2025, just 100 addresses hold over 14% of all BTC. A handful of mining pools process the majority of blocks (BitInfoCharts, 2025; b10c, 2025).

But the picture is less dramatic when zoomed in. Those wallets? Mostly exchange hot and cold storage. Those pools? Made up of thousands of independent miners.

That said, things aren't perfect. Some proxy pools — like AntPool and its close affiliates — broadcast identical block templates, hinting at coordination. It's not a hostile takeover, but it does blur the line between decentralization and logistical convenience.

Still, no entity — no wallet, no miner, no company — can unilaterally rewrite Bitcoin's consensus rules. The protocol is governed by independently run nodes spread across the globe (Nakamoto, 2008; Antonopoulos, 2017). That's what makes Bitcoin resilient.

The Market Is Still a Battlefield

Bitcoin's protocol is predictable. The market around it isn't.

One tweet. One dump. One whale blinking twice. That's enough to tank the price or send it soaring.

In late 2025, wallets holding over 10,000 BTC reduced exposure as Bitcoin pushed past $111,000 (BitDegree, 2025). Coordinated sell-off? Maybe. Manipulation? Possibly.

Spoofing — placing fake orders to distort the order book — is still common in crypto. So is wash trading. Both create an illusion of demand or panic that retail traders react to. And without consistent regulation, enforcement is hit or miss. On-chain activity can reveal patterns of abuse, but spotting them reliably still requires better tooling and clear accountability.

The code runs on math. The market runs on psychology.

What Needs Guardrails — and What Doesn't

Bitcoin doesn't need a redesign. But the system around it does.

The blockchain works fine. The problem is everything built on top — exchanges, custodians, liquidity providers. That's where rules are thin and incentives are skewed.

The fix? Rules that mirror Bitcoin's own design: transparent, automated, and resistant to capture. Like traffic laws that govern drivers but don't redesign roads:

• Require disclosure of large transactions, especially from institutional wallets.
• Enforce real-time audits of exchange reserves.
• Crack down on spoofing, wash trading, and fake volume.
• Push adoption of Stratum V2, which lets individual miners, not pools, decide which transactions to include.
• Encourage MiCA-like standards for transparency — a regulatory framework originating in the European Union that focuses on crypto-asset service provider accountability.
• Align with frameworks like the U.S. SEC's 2025 crypto-market guidelines to standardize market conduct.

Even good regulation has limits. Cross-border enforcement is hard. Jurisdictions clash. But saying "it's hard" isn't a defense. The alternative is letting markets rot from the inside.

Bitcoin maximalists will disagree — and that's fine. But decentralization without accountability is just chaos in disguise.

Fix the Market, Not the Code

Bitcoin's rules are clear. The network doesn't blink. The ledger doesn't lie.

But markets are murkier. They reward the loudest, the fastest, the best capitalized. And sometimes, the most manipulative.

If we want Bitcoin to stand for more than just uncensorable code, we need to fix the playing field around it. That means building market rules with the same rigor that built the protocol.

The next evolution isn't technical — it's cultural.

Let's make the markets as resilient as the blockchain that backs them.

Academia loves to believe it is the gatekeeper of innovation. It wasn't.

In 2008, an anonymous figure named Satoshi Nakamoto dropped a nine-page PDF into an obscure cryptography mailing list—Bitcoin: A Peer-to-Peer Electronic Cash System (Nakamoto, 2008). No peer review. No journal. No prestigious institution. Just raw code and an idea. The world changed forever.

While Satoshi stood on the shoulders of cryptographic giants like Diffie, Hellman, and Merkle, he didn't wait for their blessing to leap (Narayanan, Bonneau, Felten, Miller, & Goldfeder, 2016).

In 2015, Ethereum launched the same way: no formal academic blessing, just a white paper, a GitHub repo, and a vision for unstoppable smart contracts (de Filippi & Wright, 2018). Both Bitcoin and Ethereum became multibillion-dollar ecosystems while academia debated whether they should exist at all.

The brutal truth? Both Bitcoin and Ethereum thrived precisely because they bypassed academia's slow, cautious validation rituals. Academic journals and researchers only rushed in years later, after the real work was already done (Catalini & Gans, 2016; Narayanan et al., 2016; Xu, Weber, & Staples, 2019).

Academia's Blind Spot

When Bitcoin first appeared, it wasn't published in Nature or Science, and traditional scholars largely brushed it off as a niche idea for anarchists or tech enthusiasts (Catalini & Gans, 2016). Many questioned whether a decentralized system with no government or central entity could even work (Chen, 2018). An early mainstream critique of cryptocurrency white papers highlighted the lack of formal vetting (Chen, 2018).

Ethereum, on the other hand, dared to promise decentralized apps, DAOs, and smart contracts—concepts that sounded too utopian for serious academic circles (de Filippi & Wright, 2018). Yet here we are today, with entire industries being reimagined because of it.

Why did it happen this way? Traditional academic research operates on peer review cycles that can take months or years, while open-source builders release code and iterate in days or weeks. Without institutional constraints or gatekeepers, these communities moved fast, responding directly to user feedback and market demands.

This practice-before-theory pattern isn't unique—like Wikipedia and open-source software, crypto flourished outside institutional walls.

The Inevitable Catch-Up

As Bitcoin and Ethereum survived relentless attacks, price cycles, and network growth, academia had no choice but to pay attention.

In 2015, the University of Pittsburgh launched Ledger, the first peer-reviewed journal focused exclusively on blockchain technologies (Ledger, n.d.). By 2017–2018, blockchain research exploded across disciplines—finance, law, computer science, public policy (Xu, Weber, & Staples, 2019).

Bitcoin and Ethereum weren't the first to challenge academic norms. Innovations like Wikipedia and open-source software demonstrated how decentralized communities could develop sophisticated systems outside traditional research frameworks.

Today, there's a tidal wave of studies on everything from Bitcoin's monetary policy to Ethereum's smart contract security models. But make no mistake: the builders came first. The researchers arrived later.

The Final Word: Academia Didn't Lead. It Followed.

Let's be honest: Satoshi and Vitalik didn't wait for peer reviewers. They built. They shipped. They changed everything.

The academics? They scrambled to catch up, launching Ledger in 2015—seven years late (Ledger, n.d.). By the time the papers were being published, Bitcoin had already survived multiple market cycles, hacks, forks, and global adoption.

This is not a condemnation of academia, but a recognition of evolving innovation patterns. Research remains essential for analyzing and improving technologies. The rise of pre-print servers like arXiv shows glimpses of a faster, more open future for scholarship. Yet today, these remain exceptions, not norms.

For anyone building something audacious today: ignore the gatekeepers.

You don't need their permission slip.

History belongs to the doers. The citations will come later.

"Academia does not certify revolutions. It documents them after the fact."

The address looked ordinary.

No label. No history I could rely on. No flashy breadcrumbs. Just a quiet string of characters on the blockchain — the kind you've scrolled past a thousand times on Etherscan.

But something didn't add up.

It had just received a few large inbound transactions. Within seconds, the balance dropped. Then it did it again — and again. Over the next few hours, it processed more than a dozen transactions, moving assets in and out in patterns that felt… mechanical.

This wasn't a whale.
This wasn't a scammer trying to launder funds.

This was infrastructure.
Most likely, an exchange.

The Unlabeled Wallet Problem

In the world of blockchain forensics, labels are gold. They turn a hash into context. When a wallet is tagged as "Binance Hot Wallet" or "FTX Cold Storage," it gives you a foothold in your investigation. You can anchor movement to purpose. But most wallets aren't labeled — and exchanges don't exactly hand out maps to their internal architecture.

So you're left with patterns. And that's where real attribution begins.

What Exchange Wallets Actually Look Like

Here's a secret: most exchange-controlled wallets don't behave like people. They behave like systems. And once you've seen enough of them, the patterns become loud — even when the wallet itself is silent.

1. Transaction Frequency

These wallets are busy.
They receive deposits around the clock, often in regular intervals. You might see inbound transactions every few minutes, and corresponding outflows shortly after. It's not someone moving funds manually. It's automated, structured.

2. Volume Fluctuations

Balances spike, then vanish.
One minute the wallet holds a few million in USDT. Next, it's emptied. Then filled again. There's no "HODLing." It's not savings. It's throughput. Like a valve in a machine — pressure builds, it releases.

3. Clustering and Consistency

Exchange wallets often form clusters — groups of addresses that interact heavily with each other but rarely outside their orbit. If you find one, you often find ten more by association. Their connections aren't obvious, but they're tight.

4. Common Spending Behavior

Known multi-input heuristic: if two addresses spend from the same input in a single transaction, they're likely controlled by the same entity. In UTXO-based chains like Bitcoin, this is a dead giveaway.

How Investigators Confirm Suspicions

Once you suspect a wallet might be exchange-controlled, how do you prove it? You bring together three lenses: behavioral analysis, on-chain heuristics, and OSINT (open-source intelligence).

A. Cluster Analysis

Most serious investigators use graphing tools that analyze address behavior across thousands of transactions. These tools spot shared characteristics — like gas patterns, token flow, or common counterparties — that suggest wallet clusters. If your mystery wallet is deeply entwined with known exchange infrastructure, odds are it belongs to the same system.

B. OSINT Correlation

Google can be a surprisingly powerful tool. Public breach dumps, GitHub gists, Reddit threads, and even stray comments on block explorers can sometimes link an address to a platform. Add tools like Arkham or LookOnCHain, and suddenly your unlabeled wallet might not be so anonymous.

C. Behavioral Fingerprinting

Every blockchain actor leaves a signature. Exchanges optimize for speed, liquidity, and security. Their wallets reflect that: rapid inflows, controlled outflows, no randomness. When a wallet does the same thing 500 times in a row, it's not human. It's scripted.

Labels Are a Working Theory

In this line of work, labeling a wallet is like building a legal case — you don't need a confession, but you do need strong evidence. That's why many firms use terms like "provisional label" or "high-confidence attribution." Because the blockchain never lies, but it also never explains itself.

A label isn't a claim. It's a hypothesis — one built on pattern recognition, corroborating data, and the occasional lucky break. And that hypothesis helps steer investigations: Was this a withdrawal to a new user? Or just another cog in the machine?

The Takeaway

A blockchain address isn't an identity—it's camouflage. The only way to see who's underneath is to watch how the pattern repeats.

So when an unlabeled wallet flashes across your screen, don't swipe past. Track the cadence, follow the hand-offs, and ask what job the address is quietly doing.

Because intent always bleeds into the chain. It's never hidden—just waiting for someone who can read the patterns.

Recently, ZachXBT shared a great list of tools he uses for blockchain investigations and open source intelligence (OSINT) work. I've been following Zach's work for a long time and have huge respect for what he's built—setting the bar for independent, credible crypto investigations.

When I looked at his list, I realized I use many of the same tools (if not the majority), plus a few more that I've added based on the types of cases I handle. So I thought I'd share my own working toolkit—both for those just starting out and for those already digging deeper into hacks, scams, laundering ops, and wallet attribution.

This isn't a sponsored list or just theory. These are the tools I personally use in real investigations. Over the past few years, I also made sure to formally train myself to navigate them better:

• Advanced Blockchain Investigations (AnChain.AI)
  Skills developed: Digital Forensics · Blockchain Analysis · Open Source Intelligence
• Advanced Smart Contract Investigations (AnChain.AI)
  Skills developed: Smart Contract Investigation · Fraud Investigations · Anti-Money Laundering · Data Analysis · Blockchain Forensics
• Cryptocurrency for Law Enforcement (Public Version) (U.S. Department of Homeland Security)

Getting trained wasn't about collecting certificates—it sharpened the way I think, ask questions, connect subtle clues, and move beyond surface-level analysis.

If you want a solid resource to deepen your knowledge, I highly recommend reading "Investigating Cryptocurrencies: Understanding, Extracting, and Analyzing Blockchain Evidence" by Nick Furneaux.

It's one of the best foundational books out there if you're serious about blockchain investigations.

At the end of the day, blockchain forensics and crypto OSINT aren't just about tracing wallets or making graphs—it's about the mission of uncovering the truth in spaces where bad actors believe they can operate unnoticed.

I hope that by sharing these tools and experiences, more people get inspired to step into this kind of work. Because the more investigators we have, the stronger and safer the blockchain ecosystem becomes.

🛠️ Tools I Actually Use (and Recommend)

🔍 Blockchain Tracking & Labeling

• SCREEN (AnChain.AI) – Real-time risk screening on incoming addresses and transactions.
• CISO (AnChain.AI) – Full forensic case management: deep dives, clustering, attribution.
• Arkham – Multi-chain explorer with labeled entities, alert systems, and custom graphs.
• MetaSleuth – Creates transaction graphs easily.
• Phalcon – A tool that empowers you to decipher complex transactions, track fund flows, and uncover hidden patterns.
• Mistrack Dashboard – Advanced custom dashboard for spotting suspicious flows across chains.

🕵️ OSINT & Dark-web Lookups

• darkwebinformer – Darknet threat alerts and leak monitoring.
• OSINT Industries – Lookup tool for emails, usernames, and phone numbers across breaches.
• IntelX – Global archive for breaches, WHOIS, DNS records, and pastes.

🔧 Chrome Extensions & Browser-Helpers

• MetaSuites – Enhances block explorers (like Etherscan) by adding extra information.

🔗 Bridges & Explorer Aggregators

• Tor – For anonymous browsing, especially when exploring darknet forums.

📊 Analytics & Dashboards

• Dune – Custom SQL dashboards for blockchain data queries and visualizations.
• Mistrack Dashboard – (again, because pattern analysis often needs layering different views).

🌐 Archiving & Historical Data

• Wayback Machine – Snapshot archives of websites for proof and references.
• Archive Today – Instant webpage archiving for preserving evidence.

💬 Social Media and OSINT Tools

• Mugetsu – Twitter/X username history tracking and meme coin wallet monitoring.
• TelegramDB Search Bot – Look up basic Telegram account info and group membership.

Final Thoughts

This field is growing — and so are the threats.

The need for serious blockchain investigators, analysts, and forensic specialists has never been greater. Every new investigator strengthens the defenses of the Web3 ecosystem and makes it harder for malicious actors to hide.

Learning the tools, sharpening your skills, and committing to the mission of uncovering the truth is no longer optional — it's necessary.

The next wave of blockchain investigations is already starting. Those who prepare today will be the ones leading it tomorrow.

Explanatory journalism—nothing here is legal or financial advice.

When Tornado Cash Walked Free

On 21 March 2025 a U.S. appeals court scrapped Treasury's 2022 sanctions against Tornado Cash. Overnight, a tool once branded a national-security threat slid back into semi-legality and reignited an old argument: How private can programmable money really be?

Cypherpunks, Bitcoin and the Transparency Bug

Back in 1992, the cypherpunks—Eric Hughes, Tim May and John Gilmore—argued that code, not courts, would defend privacy. Satoshi Nakamoto's 2008 white paper promised money with no banks, borders or permission. Yet the very feature that made Bitcoin trustworthy—its public ledger—also created a forensic treasure trove. By 2013 the paper A Fistful of Bitcoins showed researchers could link "anonymous" addresses to real people. The dream of anonymity already had cracks.

Everything Evolved—Except Privacy

Ethereum super-charged crypto with DeFi, NFTs and DAOs, but it kept Bitcoin's weakness: every swap, stake or mint is etched forever on-chain. High-speed networks like Solana and BNB Chain followed the same blueprint. Most users shrugged—until exchanges froze funds and compliance engines flagged wallets, prompting a new question: Can blockchains still feel like freedom if every move is public and permanent?

Privacy Coins: Different Code, Different Trade-offs

Projects that put privacy first did appear. Monero hides every transaction by default, which is why blockchain-analytics firms still struggle to trace it. Zcash lets users switch to a shielded mode, yet fewer than one in ten transfers touch that feature. Dash added an opt-in mixer called PrivateSend, but private transfers now account for well under one percent of its traffic. In short, strong privacy exists—just not on the chains where most liquidity sits.

Mixers and the Rise of On-Chain Obfuscation

For users who stay on Ethereum or Bitcoin, mixers emerged. Tornado Cash breaks the link between a deposit and a withdrawal with zero-knowledge proofs. It worked so well that it attracted both legitimate users and hackers—and a temporary OFAC ban.

A newer protocol, Railgun, went live on main-net in January 2022. Instead of sending funds elsewhere, it cloaks balances inside smart contracts, letting users lend, stake or swap without broadcasting their histories. Think privacy wall, not escape tunnel.

How People Actually Hide Their Tracks

Here's what shows up again and again in case files—and why it works:

• Break the money into crumbs. Big, single transfers shout "track me." Smaller amounts look like normal traffic and slip past basic filters.
• Let the crumbs sit. Wallets may go silent for days or weeks. Waiting throws off timing tools that match a deposit on one chain to a withdrawal on another.
• Jump from chain to chain. Funds can start on Ethereum, hop to BNB Chain, land on Avalanche, then loop back. Each detour forces investigators to stitch together a new set of records.
• Wash through Monero. Once value passes through Monero, it leaves the public dashboard world. Coming back out, it looks like fresh money with no past.
• Cash out off-the-grid. Instead of an exchange, sellers meet buyers in Telegram chats or in person—no KYC forms, no exchange logs.
• Layer tricks on top of tricks. A single trail might run Tornado → Railgun → DEX swap → stablecoins → Monero → cash. Each step erases a little more of what came before.

Put together, these moves don't make someone untouchable, but they can blur the trail enough that even well-funded investigators lose the scent.

And that's why courts are paying attention. Alexey Pertsev was convicted in the Netherlands (he's appealing). Roman Storm, out on a $2 million bond, goes to trial in July 2025. Prosecutors aren't charging them for moving dirty money—they're testing whether writing privacy code can be a crime.

Why It Matters

When you pay with cash, no one can pull up a public ledger to see what you bought. With most blockchains, every tip, salary, donation or late-night purchase lives forever in plain sight.

• Privacy advocates argue that this swaps banks for an even nosier record-keeper: a global spreadsheet that never forgets.
• Regulators worry about the flip side: if money can vanish without a trace, it's easier for ransomware crews or sanctions-breakers to get paid.

Both sides are really debating the same thing—how much daylight is healthy.

Privacy tools don't hand law-breakers a free pass; they let ordinary users keep personal spending personal: the books you read, the causes you back, the paycheck you bring home. Using those tools adds steps and can raise eyebrows, but for many, the trade-off is worth the peace of mind.

Who gets to mind your business—you, or the whole world?

They've stolen over $2 billion in crypto, yet no one can say with certainty who's really behind them. The Lazarus Group is the boogeyman of the crypto world — North Korea's elite cyber unit blamed for history's boldest digital heists. From the Ronin Bridge attack, which netted $625 million, to the recent Bybit hack involving $1.5 billion, these operations have been linked to the funding of Pyongyang's nuclear program.

However, given North Korea's restricted access to advanced technology and global cybersecurity developments, it is worth examining whether Lazarus operates independently or if external forces play a role in their operations.

The Technical Limitations of North Korea

North Korea is one of the most isolated nations in the world. Strict government control over the internet and limited access to cutting-edge research present a significant challenge. How does a nation with such constraints consistently execute highly sophisticated, multi-billion-dollar cyber heists?

North Korea faces several obstacles in running advanced cyber operations. While its general population has restricted internet access, reports indicate that the regime has developed a formidable cyber program. North Korea reportedly trains between 3,000 and 6,000 cyber operatives, but only a fraction are believed to work on elite blockchain-related financial operations. Many are stationed abroad in China, Russia, and Southeast Asia, where they may interact with, or even be influenced by, external cybercriminal networks (CRS, 2024). This external positioning enables them to conduct sophisticated cyber operations despite domestic limitations.

The "Too Convenient" Rogue State Narrative

North Korea is frequently attributed as the primary actor in these cyber heists, often linked to the funding of Pyongyang's nuclear program. But attributing every large-scale crypto hack to this group raises important questions. Could another major power be using North Korea as a proxy to conduct cyber operations while avoiding direct blame?

Alternative Suspects: Who Else Could Be Behind These Attacks?

China

China possesses some of the world's most advanced cyberwarfare capabilities, with groups like APT41 and Unit 61398 operating with high levels of sophistication. Despite its ban on cryptocurrency, Chinese nationals remain deeply embedded in blockchain firms and exchanges.

Russia

Russian cybercriminal groups, including REvil, Conti, and Sandworm, have demonstrated expertise in laundering stolen funds. With deep government ties to cybercrime, many state-sponsored hackers operate freely under unofficial government protection.

The United States

The U.S. is known for its advanced cyber capabilities through agencies such as the NSA, CIA, and Cyber Command. The U.S. intelligence community has played a key role in shaping narratives around state-backed cybercrime.

Conclusion: Is Lazarus the Mastermind, or Just a Convenient Cover?

While the Lazarus Group is widely recognized, the extent of its independence in these operations remains a subject of debate. Their ability to evade global cybersecurity defenses, launder billions in crypto, and continuously adapt suggests that they are either supported by a more powerful entity or serving as a convenient scapegoat.

In an age where software can challenge governance systems, we need to rethink the way we view code. Lawrence Lessig's famous phrase "Code is Law" clearly captured an idea that software architecture has the power to regulate human behavior just as powerfully as any legal framework.

But what happens when code is weaponized? Stuxnet, a high level cyberattack that ignored boundaries of digital space, has proven that code could disable physical infrastructure, and make our leaders rethink international security dynamics (Hathaway, 2012). Stuxnet's emergence offered a powerful lens to examine the intersection of cybersecurity, and governance. Adding to this narrative, Kingdon's Multiple Streams Framework (MSF) provides us with a tool to understand how these issues come to the forefront of policy agendas.

Code as Law: Lessig's Vision and Today's Reality

In Lessig's work, code is described as a form of regulation in the digital age—one that shapes our actions, controls access, and determines our freedoms online (Lessig, 1999). Just as laws create rules and constraints in society, code defines the rules in cyberspace. This is evident when we consider how software and algorithms dictate who can access what data, how digital interactions are governed, and how privacy can be protected—or violated.

At the heart of Lessig's vision is the idea that those who write the code effectively make the laws in cyberspace. This concept is even more relevant today, where everything from social media algorithms to smart contracts on the blockchain are creating new forms of governance.

However, this governance can be used for both constructive and destructive purposes. Stuxnet serves as a reminder that code can be crafted to control, deceive, and disrupt as much as it can to enable innovation and transparency.

Stuxnet: When Code Becomes a Weapon

Stuxnet was discovered in 2010 and quickly became the turning point of how the governments and its people viewed cyber threats. This malware was meticulously designed to sabotage Iran's nuclear program by infecting industrial control systems, specifically targeting centrifuges. Stuxnet worked by changing the programs and modes of these centrifuges while feeding incorrect data back to the operators. It was the very first known cyberweapon capable of causing physical damage.

Stuxnet demonstrated that code could directly impact real-world infrastructures—blurring the line between cyberspace and physical reality. It revealed the extent to which code could be weaponized to achieve political and military objectives, and effectively sidestepping traditional warfare.

But beyond this malicious technical ingenuity of Stuxnet, its real significance lies in what it represents: a new frontier of governance through code. The malware was not just a tool of sabotage; it was a manifestation of how nations can use code to enforce their will in the digital space.

Kingdon's Multiple Streams Framework: How Stuxnet Opened a Policy Window

To understand how Stuxnet and the broader issues of cybersecurity come onto the global policy agenda, we can turn to John Kingdon's Multiple Streams Framework (MSF). This model suggests that for significant policy changes to occur, three streams—Problem, Policy, and Politics—must converge, creating a "policy window" where reform is possible (Kingdon, 1995).

• Problem Stream: After Stuxnet, the problem became clear: critical infrastructure and industrial systems were vulnerable to cyberattacks. Suddenly, the potential of cyberwarfare was no longer theoretical. Stuxnet exposed the weaknesses in global cybersecurity frameworks and showed that code could cripple nations.
• Policy Stream: In response to the problem, experts and policymakers began to propose cybersecurity frameworks. Solutions included new regulatory standards for industrial control systems, international cybersecurity cooperation, and more robust defense mechanisms for critical infrastructure. In this stream, the emphasis was on how to protect both digital and physical systems from future attacks.
• Politics Stream: The political will to address cybersecurity threats grew rapidly. Governments, recognizing the magnitude of the Stuxnet attack, began prioritizing cyber defense in their national security strategies. The public fear of a future, more destructive attack, combined with the political imperative to protect national infrastructure, created a fertile ground for policy change.

When these three streams—problem, policy, and politics—aligned, a policy window opened. Governments across the globe began to act, drafting cybersecurity regulations, creating cyber defense agencies, and increasing their focus on cyberwarfare capabilities.

What We've Learned: The Policy Response and Beyond

The response to Stuxnet wasn't just a rush to improve cybersecurity. It was also a wake-up call about the nature of code as a regulator. In Lessig's view, code doesn't just execute commands—it creates rules. Stuxnet was a reminder that code can be crafted to achieve specific goals, whether those goals are state-sponsored sabotage or the enforcement of privacy protections.

The challenge now is ensuring that the regulation of code keeps pace with its power. As we enter the age of blockchain, AI, and decentralized systems, we must confront the reality that code can both empower and undermine. Smart contracts are a form of code-as-law, where rules are enforced by software, not courts. But just as Stuxnet exploited vulnerabilities in code to cause physical damage, vulnerabilities in blockchain systems could be exploited for fraud, theft, or worse.

Moving Forward: A Call for Discussion

As we now begin to reflect on these intersections of technology, policy, and governance, one thing is becoming very clear: code is no longer just a tool—it is a lawmaker. The events surrounding Stuxnet, and the resulting policy responses, remind us that governments, technologists, and businesses must discuss its future together to ensure that the laws embedded in code serve the common good.

Moving forward, we must ask:

• How can we ensure that the "laws" coded into our software systems align with ethical public interest?
• What role should governments play in regulating the design and deployment of code, particularly in critical infrastructure?
• How can we balance innovation with security, especially as decentralized systems and blockchain gain prominence?

We are now indeed at a critical juncture. The window for shaping cybersecurity policy and digital governance is open, but it won't stay open forever. Now is the time for industry leaders, policymakers, and technologists to engage in meaningful discussions on how code as law can be a force for good, not just a tool for control.

Let's Shape the Future Together

The Stuxnet attack and the concept of "Code is Law" present us with profound and important pressing questions about how we govern the digital world. By understanding the lessons of the past, such as those offered by Kingdon's Multiple Streams Framework, we can shape policies that protect both our digital infrastructure and our rights in the digital age.

Let's open the floor for discussion. How do you see the future of cybersecurity policy? How can we ensure that code serves as a fair and just law for all?

Cryptocurrencies, with Bitcoin leading the charge, have long been hailed as the champions of decentralization in the financial world. The promise is enticing: a system free from central authority, where transactions occur peer-to-peer without intermediaries. But as we dig deeper into the realities of how these systems operate, a paradox emerges. The very infrastructure that supports cryptocurrencies may, in fact, be introducing new forms of centralization.

To understand this paradox, we need to look beyond the blockchain and examine the physical world that makes digital currencies possible. Three key dependencies come into focus: internet connectivity, power supply, and hardware manufacturing. Each of these represents a potential point of failure and, more critically, a vector for centralized control.

The Hidden Centralization Triad

Let's start with the internet. Cryptocurrencies rely on constant connectivity to function. While the internet itself was designed as a decentralized network, in practice, it's often controlled by a handful of Internet Service Providers (ISPs) in each country. This concentration of control means that a small number of companies could potentially disrupt or manipulate cryptocurrency traffic. The physical infrastructure of the internet – undersea cables, data centers, and network nodes – is also vulnerable to both natural disasters and intentional attacks. A disruption in one key location could have cascading effects on the global cryptocurrency ecosystem.

Next, consider the power paradox. The energy-intensive nature of many cryptocurrencies, particularly those using Proof-of-Work consensus mechanisms, creates a significant dependency on electrical grids. This reliance on centralized power distribution systems introduces another layer of potential control. The concentration of mining operations in regions with cheap electricity leads to a geographic centralization of hash power. This clustering goes against the ideal of a globally distributed network and makes the system more vulnerable to localized disruptions or regulatory changes.

Finally, there's the silicon bottleneck. Cryptocurrency networks rely on specialized hardware, from ASICs for Bitcoin mining to high-performance GPUs for other coins. The manufacturing of this hardware is concentrated among a small number of companies, creating a potential bottleneck in the supply chain. This centralization in hardware production means that a handful of manufacturers have significant influence over the network's growth and evolution. It also introduces geopolitical risks, as many of these manufacturers are concentrated in specific regions.

Beyond Bitcoin: A Systemic Concern

While Bitcoin often takes the spotlight in these discussions, these centralization concerns extend across the cryptocurrency ecosystem. Even cryptocurrencies that use different consensus mechanisms or aim for different goals face similar challenges when it comes to their reliance on internet, power, and hardware.

As we observe these trends, it becomes clear that true decentralization is more complex than simply removing central banks or government oversight from the equation. It requires a holistic approach that considers all layers of the system, from the protocol level down to the physical infrastructure that supports it.

Rethinking the Future of Decentralization

The crypto community isn't blind to these challenges. Innovations like mesh networks for internet connectivity, renewable energy solutions for mining, and efforts to diversify hardware manufacturing are all steps toward addressing these issues. However, these solutions are still in their infancy and face significant hurdles.

The paradox of centralization in decentralized systems presents both a challenge and an opportunity for the cryptocurrency world. It challenges us to think more deeply about what true decentralization means and how we can achieve it. It also offers an opportunity to innovate not just in digital protocols, but in the physical infrastructure that underlies our digital world.

As the cryptocurrency ecosystem continues to evolve, these questions of centralization and decentralization will likely play an important role in shaping its future. The next phase of the crypto revolution may not be about creating new coins or faster transactions, but about reimagining the very foundations of our digital infrastructure.

In the end, the promise of decentralization remains powerful and compelling. But fulfilling that promise may require looking beyond the blockchain to the complex, interconnected systems that make our digital world possible. It's a challenge that will require innovative thinking, technological breakthroughs, and a willingness to question our assumptions about what decentralization really means in the digital age.