平凡的蛙里奥

Thank you to the project team for giving us the opportunity to participate in this competition
100 people, 100 USD, 14 days
It sounds incredibly thrilling

Who wouldn’t want to stand out among these 100 people?

Let’s see who’s a true racehorse—run them and find out
After 14 days, you’ll go home with empty accounts and a full load of lessons learned

And I will go home with the prize, smiling, and say
"Good game"
😏

The crypto world is in astonishing sync—without discussing the market, what are they all talking about? What about the girl from 2007 and the nail clippers???

Last night I flipped through the whitepaper (@Dusk ) and reached Chapter Seven. I meant to look up the tail end of the consensus part, but I crashed straight into the sections on the execution layer. Rusk VM adds four genesis contracts.

First, what is Rusk VM?
It’s a virtual machine with a WebAssembly foundation, but the whitepaper gives it a deliberately restrained role: nearly Turing-complete. It prices every function with an internal accounting unit called gas, and the computational cost for each state transition is capped within the allocated gas limit.
Why do it this way?
You can’t guarantee that a fully Turing-complete machine will always halt.
So it sidesteps this deadlock by imposing an upper bound on computation.

This VM isn’t just running raw cryptographic primitives as standalone hosts: hashing, elliptic-curve scalar multiplication, signature verification, and zero-knowledge proof verification are all implemented as native calls. It also exposes protocol state things like contract storage read/write and the current block height and timestamp.

What really hit me is the state transition function: it lists nine global state fields, then feeds them into the VM—state tree, timestamps, block height, seed, gas limit, and so on.

What made me pause were the four genesis contracts. They’re not ordinary contracts. They’re written into the genesis block; every node running the protocol comes with them—no avoiding them.

The DUSK contract is the skeleton. I counted nine functions in total for handling native asset accounting. It supports assets moving between two forms—"transparent" and "confused"—and the entry/exit flows are all enumerated one by one, in a long list.

From a user sending to the contract, to the contract returning to the user (or to another contract), you have transparent-to-confused, confused-to-transparent, transparent-to-confused out, and every direction gets its own dedicated function. There’s no vague universal interface.

The Bid contract governs block producer bidding: three actions—submit, extend, and withdraw upon expiry.

The Stake contract governs validator staking. Again, it has the same three actions, but adds a fourth: FSlash. Anyone can report a validator that made a mistake; the reporter can receive a portion from the slashed validator’s staked funds.

The Reward contract is responsible for distributing payouts to the validators who finalized blocks and to the block producers who minted blocks. Block producers claim their own share.

Those four contracts control asset in/out flows, and if anyone wants to move DUSK, they have to go through these functions. Of course, the prerequisite stays the same: there must really be security tokens running on top of it. Even if the execution layer is precise, without the business feeding it, it’s basically a machine idling—#dusk $DUSK

I just want to ask about this Axis Robotics x Binance wallet promotion—who else is interested?

Come to the live room to learn. People with hypertension should not enter.

Axis Robotics × Binance Wallet Activity Complete Rules

I. Core Activity Information

• Total rewards: 1,500,000 Axis points

• Duration: 30 days, divided into 2 reward cycles, with 750,000 points per cycle

• Eligibility: Only for Binance users of Keyless Wallet

• Task quota: Limited to 20,000 tasks per day; first come, first served

II. Detailed Participation Steps

1. Open the Binance Wallet extension, log in, and connect to the Axis Hub platform

2. Go to the Binance Wallet exclusive activity page, find the entry point for this Axis Robotics activity

I’ve already completed 7 tasks. Hurry up!

@Dusk 的 whitepaper
Halfway through reading, I suddenly sat up straight

These people write code like they’re doing cryptography experiments—right down to having two sets of solutions for even a hash function. You can switch between Blake2b and Poseidon at will, while Schnorr and BLS signatures run in parallel on two tracks. I just stared blankly at the JubJub and BLS12-381 elliptic curves on the screen

What really got me hooked was Phoenix anonymous transactions. It uses a UTxO model to create stealth addresses—each transaction generates a one-time address via Diffie-Hellman key exchange. In plain terms: the deeper the pool, the harder it is to find the fish; the more users there are, the larger the anonymity set

But what made me slap my thigh was Zedger’s multi-signature consensus model. This thing is designed specifically for security tokens. It literally hardwires seven regulatory constraints into the protocol layer

Users must have unique accounts, transactions must pass a whitelist, and the counterparty must explicitly approve before funds can be credited. The best part is that it splits balances into three categories: tradable, votable, and dividend-distributable. Equity records can be reconstructed at any time. I stared at the line “the counterparty must explicitly approve before funds can be credited” for a long time, and suddenly felt that this is the compliance solution built for institutions—not some smoke-and-mirrors act to placate regulators

The consensus mechanism is just as wild. Proof-of-Blind Bid uses Pedersen commitments to obscure the staked amount, then uses a PLONK zero-knowledge proof to prove eligibility. Who proposed the block and how much was staked—everything is a black box. The attack cost becomes pure blind guessing game theory: you can’t see your opponent’s cards, so how do you attack?

Rusk VM is a WASM-based architecture and natively supports on-chain ZK verification. DuskEVM is compatible with Solidity and Hardhat, and the testnet is already running. Tokenomics is also clean: a hard cap of 1 billion, initial issuance of 500 million, and the remaining 500 million released gradually through staking rewards. The issuance curve decays geometrically—halving every four years. Block rewards are 70% to the block producer; the rest is burned, 10% goes to the development fund. When I read the words “the remainder is burned” out loud, I actually felt kind of satisfied

When I closed the document, the sky outside had already started to brighten. Honestly, this project doesn’t feel like it’s chasing trends. It doesn’t call for disruption, doesn’t talk about empowerment—it just slowly welds zero-knowledge proofs and compliance requirements into the underlying layer

I don’t know whether it will succeed, but I do know that if one day institutions really dare to move security tokens on-chain, they’ll most likely have to use this kind of ruthless setup that bakes regulation into the protocol layer. #dusk $DUSK

$TMX sold 400 lucky draw tickets and 200 scratch-offs. Feels like we can go for a run

I flipped through the @Dusk whitepaper last night, intending to look for something macro—but I ended up diving straight into Chapter 8, Concrete Protocol, the specific protocol details. This chapter doesn’t have a grand narrative; it’s all anatomy.

What exactly does a block look like, and what’s inside it?

First, how blocks link together—the whitepaper is pretty straightforward: blocks come one after another, locked down by hashes. In the header of the current block, it stores the Blake2b hash of the previous block header, and the height increments strictly by one. Block 0 is the genesis block, and its previousBlockHash is hard-coded directly to 0.

The genesis block contains four genesis contracts, a pre-set list of generators and validators, and two hard-coded seeds—used for epoch 0 and epoch 1 respectively. In other words, this chain’s “birth certificate” is written by design.

A block is split into three parts: Header, Body, and Certificate. The header has eight fields: version, height, timestamp, previous block hash, seed, block reward, transactions root, and state root. I stared at this field table for quite a while, because it’s essentially the chain’s “ID card”—change even a single byte, and the hash of the entire chain changes.

Then there’s the Certificate. It stores the block production score, the PLONK zero-knowledge proof of the block producer, and the committee’s BLS aggregated signature.

The binary mapping of validatorSeq, indicating which validators’ signatures have been aggregated into the certificate. What’s truly interesting is that the whitepaper explicitly says: the certificate is constructed locally by each consensus participant, so for the same consensus round, there is no single unified certificate. I actually paused when I read that.

Other chains can’t wait to make certificates unique across the whole network, stamp them, and store them. Dusk does the opposite: each node holds its own proof assembled locally. I think the trade-off is behind this—rather than forcing the entire network to wait for one authoritative certificate, it lets each node independently prove itself. That matches its privacy-first philosophy.

Crossover’s special field—it’s the bridge between DUSK’s transaction layer and its general computation layer.

My takeaway after reading is: the first few chapters were all about the “why,” while this one is entirely about the “what it looks like.” Privacy, consensus, compliance—everything ultimately has to be packed into a concrete sequence of bytes before it’s truly realized.#dusk $DUSK @Dusk

My real-life best friend has some extra money to invest in financial management. I told him, you’re really better off just doing spot DCA $ETH $BTC . He said I was trying to scam him, that I’ve only been playing for 3 years and still haven’t figured it out. Brothers, what should I say to persuade him? Drag him into the crypto world.

Last night I flipped through the consensus-proof section of the whitepaper of @Dusk . I originally planned to skim it and close it, but I got stuck on page 15. The whole page is one tidy-looking binomial distribution formula: summation notation, combinations, powers of h and (1-h)—all arranged so neatly. I stared at it for a few seconds, briefly thinking I’d opened an undergraduate probability theory homework question.

It’s basically that formula that controls whether this chain will fork or not.

First, a quick rundown: the SBA phase flow was written about before. This time it’s about that layer underneath the phases—statistical finality. The whitepaper’s definition is very straightforward: the probability that a fork occurs in a single execution round is negligible. Pay attention to the wording: it’s not “never forks,” it’s “forking probability is so small you don’t need to worry about it.” Honestly, I really buy into that. It’s more convincing than someone just promising “absolutely safe” offhand.

So how do they drive the probability down to negligible? The whitepaper nails down the only way to fork: double voting. In the same voting step, a node votes for two different candidate blocks. The key point is that honest nodes can’t do this—so double voting can only come from Byzantine nodes. And one double vote isn’t enough. To actually split the chain, you need to secure an absolute majority in all three consecutive voting steps.

That’s where the formula comes in. The failure rate—this binomial distribution—calculates the probability that the adversary achieves an absolute majority within a single committee. N is the number of committee members, τ is the vote threshold for passing, and h is the honest share. To fork you have to win three steps in a row; it’s basically multiplying small probability by small probability, and the more factors you multiply, the smaller it gets.

There’s also a detail I really like: consensus is organized into three layers—epoch, round, and step. A round is block height. Each round runs through a fixed cycle of four steps. Within an epoch, the lists of proposers and validators stay unchanged, and they’re generated using the same epoch seed. Combined with the assumption that the “corruption” must wait for one epoch, it means once someone is in this committee list, nobody can swap them out midstream.

After reading it, my takeaway is this: what protects the chain isn’t some kind of mysticism—it’s an honest-to-goodness probability exam question. Of course, all of this is built on the assumption that “the bad guys are less than one-third.” If a few whale-stakers end up dominating the stake, no matter how pretty the formula is, it’s all for nothing. #dusk $DUSK @Dusk

So what if you’re a genius—can you make money for me nonstop?

Can a privacy chain be positioned like this?

It says @Dusk can serve as a privacy-preserving sidechain for any L1

The whitepaper is very direct: Dusk was never designed to be a one-size-fits-all public chain. It’s targeting “regulated security tokenization and end-to-end lifecycle management.”

Two standards are what prop up the show.

One is XSC. The privacy-preserving security contract standard’s whitepaper even writes very modestly that the details are outside the scope of this paper. If you want to learn more, look for another document [Mah21].

I was stunned at the time—this was the first whitepaper I’d seen that effectively handed over its most important application-layer standard to external references, and then I traced through it. This set of standards covers the whole sequence for tokenized securities: from issuance, to voting, to dividends.

The other is the privacy token standard. This one is even more clever: it allows regulated and unregulated assets to interact on the same chain without sacrificing participants’ privacy. My understanding is that this is the privacy bridge built between DUSK (which operates with unregulated assets) and security tokens.

They don’t need to know each other on either side to safely work together.

As long as you pair it with a trustworthy or trust-minimized interoperability solution, projects on other L1s don’t need to migrate their chains. They can simply use Dusk as a privacy execution layer. This idea is something I haven’t seen in other privacy-chain documents: privacy is no longer a single-chain island—it becomes a capability that others can borrow.

Put simply: if another chain’s assets want to keep things private, they don’t need to move home. Just drive the asset to Dusk’s privacy workshop, process it there, and drive it back. I think this positioning is much lighter than “issuing another privacy chain.”

One more small detail: in the architecture, the protocol is split into two non-overlapping layers—an native asset layer and a general computation layer. They share the same state space, but DUSK retains several exclusive privileges: only it can be used for staking; only it can pay execution fees; and DUSK contracts are the only entry point into state transitions. The boundary between the asset layer and computation layer is drawn very clearly. It means that no matter how big the on-chain ecosystem grows, the demand to “consume DUSK” can’t be avoided.

Of course, all of this narrative only holds if the upper-layer standards are actually being used. If XSC never takes off, or if security-tokenization projects don’t arrive for a long time, then “a privacy sidechain” is just a pretty empty promise.

My suggestion: first check whether real security token contracts show up on the testnet, and then consider whether to get on the train. #dusk $DUSK

In our little circle, everyone thinks they’re a trading genius.

Do you know someone like—where everyone says he’s a genius, but he ends up being so oppressive that other traders can’t hold their heads up?

Please recommend one to me—I want to go learn from him.

I've been thinking about how to play @TermMax lately, and I find its design of splitting debt into FT and XT pretty interesting. The lender buys FT to lock in fixed returns, while the borrower tosses out XT to swap for liquidity—effectively slicing and pricing interest-rate risk directly. That’s much clearer than the usual game-theory mixing in traditional lending pools.

That said, for this mechanism to work, it really depends on the Range Order AMM’s market-making logic. It uses a target APR range instead of a price range, and the curve can automatically recalculate based on the maturity date. It sounds more aligned with how interest-rate markets behave than V3, but whether the slippage and depth can withstand extreme conditions is something I still need to observe.

I also think the GT NFT leverage wrapper is a highlight. With a single transaction, you can move directly to a target leverage level, saving gas from repeated loop collateralization and reducing liquidation risk. But on the flip side, leverage amplifies both gains and losses. Combined with oracle dependency, if on-chain data sources malfunction, the chain reaction could be even more severe than in traditional lending.

The curator mechanism actually makes me feel a bit more comfortable. Professional teams like Keyrock manage liquidity, and idle funds can be automatically deployed into Aave or Morpho to earn yield—so capital isn’t just sitting idle. However, this also means the protocol becomes more reliant on third parties; if a curator strategy misfires, the impact could directly propagate to users.

From the data: TVL is 64 million, peak daily active users reach 170,000, and it’s deployed across 7 chains—showing the ecosystem is indeed expanding. But I think the real test after the TGE is whether it can retain TVL. TMX’s total supply is 1 billion and won’t be increased. Ecosystem tokens are locked for 48 months; the team and investors’ allocations are linearly released after 12 months. The overall pace is fairly restrained. The protocol stakes sTMX to earn trading fees, borrowing fees, and liquidation fees—its revenue sources feel fairly solid rather than purely propped up by inflation.

However, if after the token listing in 2026 Q3 the TVL doesn’t keep up, or if bad-debt controls don’t work out, then my assessment may have to be overturned.

In practice, I think it’s best not to rush. First, watch the rollout of the Q2 options expansion and the strategy vaults. Pay special attention to how GT performs liquidation under extreme volatility, and to the real returns of curators’ deployed capital. If those two hold up, then consider building positions in batches. After all, the interest-rate sector has low tolerance for mistakes—leaving room for error matters more than just reciting slogans.
#termmax

This is the highest-traffic post I’ve had since Binance

I really didn’t expect
that my first time would go to a cow

Speaking of cows—in my view, the most powerful privacy project I have is @Dusk
not the kind of self-hype where “I used some consensus so I’m so great”

It’s that it actually did something that everyone thought was impossible.

Privacy and compliance—these two are supposed to be sworn enemies. The deeper you hide, the more nervous regulators get. But Dusk took a third path.

The most mind-boggling design is called Proof-of-Blind Bid.
On other chains, everyone can see who produces blocks and how much is staked—basically laying the validator’s cards on the table. Dusk doesn’t play that game.

The staking amount is wrapped with Pedersen commitments, and then a zero-knowledge proof is used to tell the network, “I’m eligible to produce blocks,”
but it doesn’t reveal who you are or how much you staked.

A group of people wear masks and vote in the dark in a dim room.
If an attacker wants to cause trouble?

They can’t even find the target.

For the trading side, Phoenix handles anonymity. Each transaction generates a one-time address. The anonymous set is the total of all cumulative outputs from the genesis block to now— the more people use it, the deeper your privacy. Not something propped up by a mixing pool.

Another one: Zedger
Specially designed for security tokenization—regulatory requirements like whitelists, recipient approval, and equity snapshots are written one by one into the protocol layer, not the contract layer, into the protocol itself.

The chain itself was built like this.
While others are still debating how to put assets on-chain,
Dusk is already answering how to meet regulatory requirements after assets are on-chain.

The technical foundation is solid too.

Rusk VM is built on the WASM architecture, with native support for on-chain ZK verification.
The cryptography components hash uses both Blake2b and Poseidon. Signatures use both Schnorr and BLS.
Most whitepapers stop at this level with a line like “uses industry-standard mainstream solutions,” but Dusk specifies every screw’s exact model.

Tokenomics are not exaggerated either.
Total supply capped at 1 billion. Halves every four years. Any block rewards that aren’t distributed are directly burned. The more active the network, the more it burns: #dusk $DUSK

Recently, there’s some outrageous chatter going around in the local circles—rumors that say TermMax’s range-order lending/borrowing model “stole” the method used by Xu Qihang (Evergrande’s) back then.

However, when I open the @TermMax whitepaper and break down its on-chain logic, I find that this is just too...
It didn’t borrow from Evergrande at all. Instead, it uses code to build a mechanism that is completely the opposite of Evergrande.

#termmax splits every dollar into two tokens: FT (the principal coin) represents the principal that is rigidly settled at maturity, while XT (the interest coin) represents floating interest yield.

Your principal safety doesn’t depend on any platform’s promises. It’s protected by real assets locked in smart contracts. There’s no Ponzi-style structure of “borrowing new to repay old.”

Interest rates can be “targeted at specific points” by borrowing Uniswap V3’s concentrated liquidity mechanism. TermMax lets you define your own rate range for limit orders.

If you think 8%–10% is reasonable, you only place orders within that range. If the rate goes off target, your order won’t get filled—avoiding the passive “all-or-nothing” situation typical of traditional lending pools.

It also supports multi-range orders. For example, 80% of the funds are placed for stable rates, and 20% is used to chase higher interest—flexible like placing batches of limit orders.

The fundamental difference from Evergrande:
Evergrande manufactures “guaranteed returns” through paper guarantees and capital-pool shuffling, with unclear accounting—leading to the eventual blow-up.

With TermMax, all orders, interest rates, and reserve quantities are fully verifiable on-chain. Interest rates are market-matched based on supply and demand within a predefined range. Risk control is handled by automatic execution through smart contracts.

In one sentence: Evergrande is run by people. TermMax is “run by code.”

So why is there a rumor that confuses DeFi fixed-rate lending with Evergrande wealth management?

Because both of them promise “guaranteed returns.”
But the essential difference is: Evergrande’s “guarantee” relies on paper guarantees and capital-pool maneuvering, whereas TermMax’s “guarantee” comes from the smart contract’s atomic splitting of principal and interest plus real-time on-chain settlement.

The former is trust in people; the latter is trust in mathematics. They have a fundamental difference.