Ethereum consensus clients today can’t efficiently serve small, verifiable pieces of BeaconState without shipping the entire ~271MB state or relying on ad-hoc debug endpoints. SSZ-QL, originally proposed by Etan Kissling and now prototyped by Jun and Fernando in Prysm, defines a standard query language for requesting arbitrary SSZ subtrees plus Merkle proofs, across both consensus and execution clients. The article walks through how generalized indexes and SSZ serialization shape the Merkle tree, how Prysm’s SSZ analyzer (analyzeType + PopulateVariableLengthInfo) computes offsets and chunk layouts, and how new Beacon API endpoints expose an initial SSZ-QL-powered /states/{state_id}/query and /blocks/{block_id}/query interface.Ethereum consensus clients today can’t efficiently serve small, verifiable pieces of BeaconState without shipping the entire ~271MB state or relying on ad-hoc debug endpoints. SSZ-QL, originally proposed by Etan Kissling and now prototyped by Jun and Fernando in Prysm, defines a standard query language for requesting arbitrary SSZ subtrees plus Merkle proofs, across both consensus and execution clients. The article walks through how generalized indexes and SSZ serialization shape the Merkle tree, how Prysm’s SSZ analyzer (analyzeType + PopulateVariableLengthInfo) computes offsets and chunk layouts, and how new Beacon API endpoints expose an initial SSZ-QL-powered /states/{state_id}/query and /blocks/{block_id}/query interface.

SSZ-QL: A Guide to Querying Ethereum’s BeaconState Using Offsets, Proofs, and G-Indexes

2025/11/16 21:02

Today, consensus clients cannot easily provide individual pieces of data from the BeaconState together with the proofs needed to verify them. Ethereum’s Light Client system defines some proof paths, but there is no universal or standard way for clients to generate or serve these proofs. Downloading the entire BeaconState is not realistic—the state for slot 12,145,344 is around 271 MB, which is too large to send over the network quickly and puts unnecessary load on both the node and the user. The spec even warns that the debug endpoints used for fetching full states are meant only for diagnostics, not real-world use.

A much better solution is to use Merkle proofs or multiproofs, which allow the provider to send only a very small, verifiable part of the state. This is especially useful because most of the state size comes from validators (~232 MB) and balances (~15 MB); the rest of the fields are about ~24 MB. If a user needs only one small field, it’s wasteful to download the entire 271 MB state. Instead, a Merkle proof can deliver just the requested leaf plus its authentication path—usually only a few kilobytes.

Because of this, we need a general and standardized way for clients to request only the data they need, along with the proof required to verify it. This reduces bandwidth, reduces CPU load, and replaces today’s scattered and custom implementations (for example, Nimbus’s special handling of historical_summaries).

This work is also important for the future of Ethereum. SSZ is becoming more central to the protocol: Pureth (EIP-7919) proposes replacing RLP with SSZ, and the upcoming beam chain (also called the lean chain) will leverage SSZ as its only serialization format. So building a clean, efficient, and standard method for proof-based data access is a key step toward future protocol upgrades.

Proposed Solution: Introducing the SSZ Query Language (SSZ-QL)

The idea of SSZ-QL was originally proposed by Etan Kissling. His main question was straightforward but powerful:

“What if we had a standard way to request any SSZ field — together with a Merkle proof — directly from any consensus client?”

Today, consensus clients do not offer a general or standardized method to request specific SSZ data with proofs. Some ad-hoc solutions exist (for example, Nimbus’ basic queries used by the verifying web3signer), but there is no proper, universal SSZ query language available—and certainly nothing ready at the time this idea was written.

Etan’s proposal describes what an SSZ Query Language should allow:

  • Requesting any subtree inside an SSZ object
  • Choosing whether a field should be fully expanded or returned only as a hashtreeroot
  • Filtering (for example, finding a transaction with a certain root)
  • Using back-references (e.g., retrieving the receipt at the same index as a matching transaction)
  • Specifying where the proof should be anchored
  • Supporting forward compatibility so clients can safely ignore unknown future fields

This kind of API could be used by both consensus and execution clients. With forward-compatible SSZ types (like those from EIP-7495), request and response structures can even be generated automatically.

Building on this idea, the proposed solution by Jun and Fernando, who are developing this as part of their EPF project in prysm, is to add a new Beacon API endpoint that supports SSZ Query Language (SSZ-QL). This endpoint lets users fetch exactly the SSZ data they need—no more, no less—together with a Merkle proof that verifies its correctness. The initial version will offer a minimal but practical feature set, which already covers most real use cases. (The draft API specification is available for review.)

Beyond this minimal version, also plan to create a full SSZ-QL specification. This expanded version will support advanced features such as filtering, requesting data ranges, and choosing custom anchor points, all with Merkle proofs included. They intend to propose this richer specification for inclusion in the official consensus specifications, and an early draft is already available for review.

Understanding Generalized Indexes (GI) Before Diving Into SSZ-QL

In SSZ, every object — including the entire BeaconState — is represented as a binary Merkle tree. \n A generalized index (GI) is simply a number that uniquely identifies any node inside this tree.

The rules are very simple:

  • Root node has generalized index: \n GI = 1
  • For any node with index i: \n left child = 2*i, \n right child = 2*i + 1

So the whole tree is numbered like:

GI:1 / \ GI:2 GI:3 / \ / \ GI:4 GI:5 GI:6 GI:7 ...

This numbering makes Merkle proofs easy. If you know the generalized index of a leaf, you know exactly where it sits in the tree and which sibling hashes must be included to verify it.

Example with Beacon State:

0 GenesisTime string 1 GenesisValidatorsRoot string 2 Slot string 3 Fork *Fork 4 LatestBlockHeader *BeaconBlockHeader 5 BlockRoots []string 6 StateRoots []string 7 HistoricalRoots []string 8 Eth1Data *Eth1Data 9 Eth1DataVotes []*Eth1Data 10 Eth1DepositIndex string 11 Validators []*Validator ← (p = 11) 12 Balances []string 13 RandaoMixes []string 14 Slashings []string 15 PreviousEpochAttestations []*pendingAttestation 16 CurrentEpochAttestations []*pedningAttestation 17 JustificationBits string 18 PreviousJustifiedCheckpoint *Checkpoint 19 CurrentJustifiedCheckpoint *Checkpoint 20 FinalizedCheckpoint *Checkpoint

There are 21 top-level fields (indexed 0..20). To place these into a Merkle tree, SSZ pads them up to the next power of two (32).

\n 32 leaves → depth = 5. \n Top-level leaves occupy the GI range:

32 ... 63

We compute the GI for a top-level field using:

Formula:

GI_top = 2^depth + field_index

For .validators, field index = 11

So: \n GI_validators = 2^5 + 11 = 32 + 11 = 43.

This GI (43) is the leaf commitment of the entire validator’s subtree inside the global BeaconState tree.

Multi-Level Proof: Example With validators[42].withdrawal_credentials

Now, suppose we want a proof for:

BeaconState.validators[42].withdrawal_credentials

This requires two levels of proof:

\

  1. Prove that the entire validator’s subtree is included in the BeaconState root

    We already know:

  • Top-level GI for validators = 43

    Using GI 43, the consensus client collects the sibling hashes on the path from leaf 43 up to root (e.g., GI 43 → 21 → 10 → 5 → 2 → 1).

    This gives the proof:

validators_root ---> BeaconState_root

\

  1. Prove that validator[42].withdrawal_credentials is inside the validator’s subtree

    Now treat the validators list as its own Merkle tree.

    Inside this subtree:

  • Validator 42 is the 42-nd element → it maps to some leaf index (e.g. chunk k) inside this subtree.

  • Withdrawal credentials lives inside one of the 32-byte SSZ chunks of validator #42 (for example chunk k = 128 — number doesn’t matter, just concept).

    We now generate:

    leaf (withdrawal_credentials chunk) ---> validators_root

    by collecting sibling hashes inside the local validator-subtree.

    Final Combined Proof

    You end up with:

1. Local Level Proof Proves withdrawal_credentials --> validator_root 2. Top-level branch proof Proves validator_root --> BeaconState_root

A verifier can now reconstruct the BeaconState root from only:

  • the requested leaf

  • the two lists of sibling nodes

  • the known BeaconState root

    No full state download needed.

┌───────────────────────────────┐ │ BeaconState Root │ └───────────────────────────────┘ ▲ │ (Top-level Merkle Proof) │ Sibling hashes for GI = 43 │ ┌─────────────────────────────────────────┐ │ validators_root (GI = 43) │ └─────────────────────────────────────────┘ ▲ │ (Local Subtree Proof) │ Proof inside validators list │ for index = 42 │ ┌─────────────────────────────────────────────────────────┐ │ Validator[42] Subtree (list element #42) │ └─────────────────────────────────────────────────────────┘ ▲ │ (Field-level Merkle Proof) │ Sibling hashes inside the │ validator struct │ ┌──────────────────────────────────────────┐ │ validator[42].withdrawal_credentials │ ← requested field └──────────────────────────────────────────┘

\

Understanding SSZ Serialization Before Computing Generalized Indices

To compute a correct generalized index, you must first understand how SSZ serializes and merklizes different data types. \n Generalized indices don’t exist in isolation—they are derived from the shape of the Merkle tree, and the shape of the tree depends entirely on how SSZ interprets the underlying Go struct fields.

In SSZ, each field can only be one of two categories:

\

  1. Base Types (fixed-size values)

    uint64, Bytes32, Bytes20, uint256 etc. These are straightforward — they always serialize into a fixed number of bytes.

    \

  2. Composite Types

    Container (like BeaconState), Vector[T, N] (fixed length), List[T, N] (variable length), Bitvector[N], Bitlist[N] And each of them is serialized in a slightly different way.

    To compute a generalized index (g-index) for any field inside a state, the SSZ tree must first know how that field is serialized. This is why the generated *.pb.go files include tags such as:

\

ssz-size:"8192,32" → Vector ssz-max:"16" → List ssz-size:"?,32" → List of Vector

\ To compute a generalized index for any field, we must first understand the SSZ structure of the object:

\

  • which fields exist,
  • whether each field is a List or Vector,
  • how many chunks each field occupies,
  • and how nested types should be traversed.

This is exactly what the AnalyzeObject function does in Prysm, located at encoding/ssz/query/analyzer.go

// AnalyzeObject analyzes given object and returns its SSZ information. func AnalyzeObject(obj SSZObject) (*SszInfo, error) { value := reflect.ValueOf(obj) info, err := analyzeType(value, nil) if err != nil { return nil, fmt.Errorf("could not analyze type %s: %w", value.Type().Name(), err) } // Populate variable-length information using the actual value. err = PopulateVariableLengthInfo(info, value) if err != nil { return nil, fmt.Errorf("could not populate variable length info for type %s: %w", value.Type().Name(), err) } return info, nil }

What analyzeType Does

analyzeType is the function that examines a Go value using reflection and figures out what kind of SSZ type it is. It is a pure type-analysis step — it does not depend on the actual runtime values, only on the Go type and the struct tags.

When you give it a field or struct, it:

  • Checks the Go kind (uint, struct, slice, pointer, etc.)
  • Reads SSZ-related struct tags like ssz-size and ssz-max
  • Decides whether this field is:
  • a basic SSZ type (uint64, uint32, bool)
  • a Vector (ssz-size:"N")
  • a List (ssz-max:"N")
  • a Bitvector / Bitlist
  • a Container (struct)
  • Builds an SszInfo record that describes:
  • the SSZ type (List, Vector, Container…)
  • whether it is fixed-sized or variable-sized
  • offsets of fields (for Containers)
  • nested SSZ information for child fields

Think of analyzeType as the function that scans the type definition and produces a static SSZ layout blueprint for this type.

What PopulateVariableLengthInfo Does

While analyzeType studies the type, some SSZ objects cannot be fully described without the actual value. \n

Examples:

  • Lists ([]T) need to know their current length
  • Variable-sized container fields need their actual offset
  • Nested lists need each element’s actual size

PopulateVariableLengthInfo fills in this missing runtime information.

\ It:

  • Looks at the SszInfo blueprint created by analyzeType
  • Looks at the actual value of the object passed
  • Computes values that can only be known at runtime:
  • length of Lists
  • sizes of nested variable elements
  • offsets of variable-sized fields inside Containers
  • bitlist length from bytes

It processes everything recursively — for example, a Container with a List containing structs with Lists will all be filled in.

Think of PopulateVariableLengthInfo as the function that takes the blueprint from analyzeType and fills in the real measurements based on the actual value you pass.

Example:

Let's test this function with a passing BeaconState struct

type BeaconState struct { state protoimpl.MessageState `protogen:"open.v1"` GenesisTime uint64 `protobuf:"varint,1001,opt,name=genesis_time,json=genesisTime,proto3" json:"genesis_time,omitempty"` GenesisValidatorsRoot []byte `protobuf:"bytes,1002,opt,name=genesis_validators_root,json=genesisValidatorsRoot,proto3" json:"genesis_validators_root,omitempty" ssz-size:"32"` Slot github_com_OffchainLabs_prysm_v7_consensus_types_primitives.Slot `protobuf:"varint,1003,opt,name=slot,proto3" json:"slot,omitempty" cast-type:"github.com/OffchainLabs/prysm/v7/consensus-types/primitives.Slot"` Fork *Fork `protobuf:"bytes,1004,opt,name=fork,proto3" json:"fork,omitempty"` LatestBlockHeader *BeaconBlockHeader `protobuf:"bytes,2001,opt,name=latest_block_header,json=latestBlockHeader,proto3" json:"latest_block_header,omitempty"` BlockRoots [][]byte `protobuf:"bytes,2002,rep,name=block_roots,json=blockRoots,proto3" json:"block_roots,omitempty" ssz-size:"8192,32"` StateRoots [][]byte `protobuf:"bytes,2003,rep,name=state_roots,json=stateRoots,proto3" json:"state_roots,omitempty" ssz-size:"8192,32"` HistoricalRoots [][]byte `protobuf:"bytes,2004,rep,name=historical_roots,json=historicalRoots,proto3" json:"historical_roots,omitempty" ssz-max:"16777216" ssz-size:"?,32"` Eth1Data *Eth1Data `protobuf:"bytes,3001,opt,name=eth1_data,json=eth1Data,proto3" json:"eth1_data,omitempty"` Eth1DataVotes []*Eth1Data `protobuf:"bytes,3002,rep,name=eth1_data_votes,json=eth1DataVotes,proto3" json:"eth1_data_votes,omitempty" ssz-max:"2048"` Eth1DepositIndex uint64 `protobuf:"varint,3003,opt,name=eth1_deposit_index,json=eth1DepositIndex,proto3" json:"eth1_deposit_index,omitempty"` Validators []*Validator `protobuf:"bytes,4001,rep,name=validators,proto3" json:"validators,omitempty" ssz-max:"1099511627776"` Balances []uint64 `protobuf:"varint,4002,rep,packed,name=balances,proto3" json:"balances,omitempty" ssz-max:"1099511627776"` RandaoMixes [][]byte `protobuf:"bytes,5001,rep,name=randao_mixes,json=randaoMixes,proto3" json:"randao_mixes,omitempty" ssz-size:"65536,32"` Slashings []uint64 `protobuf:"varint,6001,rep,packed,name=slashings,proto3" json:"slashings,omitempty" ssz-size:"8192"` PreviousEpochAttestations []*PendingAttestation `protobuf:"bytes,7001,rep,name=previous_epoch_attestations,json=previousEpochAttestations,proto3" json:"previous_epoch_attestations,omitempty" ssz-max:"4096"` CurrentEpochAttestations []*PendingAttestation `protobuf:"bytes,7002,rep,name=current_epoch_attestations,json=currentEpochAttestations,proto3" json:"current_epoch_attestations,omitempty" ssz-max:"4096"` JustificationBits github_com_OffchainLabs_go_bitfield.Bitvector4 `protobuf:"bytes,8001,opt,name=justification_bits,json=justificationBits,proto3" json:"justification_bits,omitempty" cast-type:"github.com/OffchainLabs/go-bitfield.Bitvector4" ssz-size:"1"` PreviousJustifiedCheckpoint *Checkpoint `protobuf:"bytes,8002,opt,name=previous_justified_checkpoint,json=previousJustifiedCheckpoint,proto3" json:"previous_justified_checkpoint,omitempty"` CurrentJustifiedCheckpoint *Checkpoint `protobuf:"bytes,8003,opt,name=current_justified_checkpoint,json=currentJustifiedCheckpoint,proto3" json:"current_justified_checkpoint,omitempty"` FinalizedCheckpoint *Checkpoint `protobuf:"bytes,8004,opt,name=finalized_checkpoint,json=finalizedCheckpoint,proto3" json:"finalized_checkpoint,omitempty"` unknownFields protoimpl.UnknownFields sizeCache protoimpl.SizeCache }

package main import ( "fmt" "github.com/OffchainLabs/prysm/v7/encoding/ssz/query" eth "github.com/OffchainLabs/prysm/v7/proto/prysm/v1alpha1" ) func main() { v := ð.BeaconState{} // Analyze it with Prysm’s existing SSZ analyzer info, _ := query.AnalyzeObject(v) fmt.Println(info.Print()) }

Output:

BeaconState (Variable-size / size: 2687377) ├─ genesis_time (offset: 0) uint64 (Fixed-size / size: 8) ├─ genesis_validators_root (offset: 8) Bytes32 (Fixed-size / size: 32) ├─ slot (offset: 40) Slot (Fixed-size / size: 8) ├─ fork (offset: 48) Fork (Fixed-size / size: 16) │ ├─ previous_version (offset: 0) Bytes4 (Fixed-size / size: 4) │ ├─ current_version (offset: 4) Bytes4 (Fixed-size / size: 4) │ └─ epoch (offset: 8) Epoch (Fixed-size / size: 8) ├─ latest_block_header (offset: 64) BeaconBlockHeader (Fixed-size / size: 112) │ ├─ slot (offset: 0) Slot (Fixed-size / size: 8) │ ├─ proposer_index (offset: 8) ValidatorIndex (Fixed-size / size: 8) │ ├─ parent_root (offset: 16) Bytes32 (Fixed-size / size: 32) │ ├─ state_root (offset: 48) Bytes32 (Fixed-size / size: 32) │ └─ body_root (offset: 80) Bytes32 (Fixed-size / size: 32) ├─ block_roots (offset: 176) Vector[Bytes32, 8192] (Fixed-size / size: 262144) ├─ state_roots (offset: 262320) Vector[Bytes32, 8192] (Fixed-size / size: 262144) ├─ historical_roots (offset: 2687377) List[Bytes32, 16777216] (Variable-size / length: 0, size: 0) ├─ eth1_data (offset: 524468) Eth1Data (Fixed-size / size: 72) │ ├─ deposit_root (offset: 0) Bytes32 (Fixed-size / size: 32) │ ├─ deposit_count (offset: 32) uint64 (Fixed-size / size: 8) │ └─ block_hash (offset: 40) Bytes32 (Fixed-size / size: 32) ├─ eth1_data_votes (offset: 2687377) List[Eth1Data, 2048] (Variable-size / length: 0, size: 0) ├─ eth1_deposit_index (offset: 524544) uint64 (Fixed-size / size: 8) ├─ validators (offset: 2687377) List[Validator, 1099511627776] (Variable-size / length: 0, size: 0) ├─ balances (offset: 2687377) List[uint64, 1099511627776] (Variable-size / length: 0, size: 0) ├─ randao_mixes (offset: 524560) Vector[Bytes32, 65536] (Fixed-size / size: 2097152) ├─ slashings (offset: 2621712) Vector[uint64, 8192] (Fixed-size / size: 65536) ├─ previous_epoch_attestations (offset: 2687377) List[PendingAttestation, 4096] (Variable-size / length: 0, size: 0) ├─ current_epoch_attestations (offset: 2687377) List[PendingAttestation, 4096] (Variable-size / length: 0, size: 0) ├─ justification_bits (offset: 2687256) Bitvector[8] (Fixed-size / size: 1) ├─ previous_justified_checkpoint (offset: 2687257) Checkpoint (Fixed-size / size: 40) │ ├─ epoch (offset: 0) Epoch (Fixed-size / size: 8) │ └─ root (offset: 8) Bytes32 (Fixed-size / size: 32) ├─ current_justified_checkpoint (offset: 2687297) Checkpoint (Fixed-size / size: 40) │ ├─ epoch (offset: 0) Epoch (Fixed-size / size: 8) │ └─ root (offset: 8) Bytes32 (Fixed-size / size: 32) └─ finalized_checkpoint (offset: 2687337) Checkpoint (Fixed-size / size: 40) ├─ epoch (offset: 0) Epoch (Fixed-size / size: 8) └─ root (offset: 8) Bytes32 (Fixed-size / size: 32)

In the SSZ analyzer output, the offset shown for each field represents the exact byte position where that field begins when the entire struct is serialized according to SSZ rules. SSZ serialization lays out all fixed-size fields first, tightly packed one after another, and the offset tells you where each of these fields starts within that packed byte stream. For example, in the line root (offset: 8) Bytes32 (Fixed-size / size: 32), the field root is a 32-byte fixed-size value, and its serialized bytes begin at position 8 in the SSZ-encoded byte array. The size indicates how many bytes the field contributes to the serialized output (32 bytes in this case). For fixed-size types, the size is predetermined, while for variable-size types, the analyzer computes the size based on the actual value. Together, the offset and size show exactly how the SSZ layout is organized in memory when the struct is serialized.

Example: Finding the Merkle Leaf for a Field Using the Offset

Let’s take a real field from the SSZ Analyzer Output:

├─ fork (offset: 48) Fork (Fixed-size / size: 16) │ ├─ previous_version (offset: 0) Bytes4 (Fixed-size / size: 4) │ ├─ current_version (offset: 4) Bytes4 (Fixed-size / size: 4) │ └─ epoch (offset: 8) Epoch (Fixed-size / size: 8)

We want to prove the field:

fork.epoch

The “fork” field in BeaconState starts at offset 48 in the serialized byte stream.

Inside fork, the epoch field starts at offset 8 (relative to the start of Fork).

So:

absolute_offset = base_offset_of_fork + offset_of_epoch_inside_fork absolute_offset = 48 + 8 = 56 bytes

fork.epoch begins at byte 56 of the full serialized BeaconState.

SSZ divides serialization into 32-byte chunks:

  • Chunk 0 → bytes 0–31
  • Chunk 1 → bytes 32–63
  • Chunk 2 → bytes 64–95

Now find which chunk contains byte 56:

chunk_index = floor(56 / 32) = 1

So:

The leaf containing fork.epoch is Leaf / Chunk 1.

fork.epoch is an 8-byte integer

Within chunk 1 (bytes 32–63):

local_offset = 56 - 32 = 24

So inside the 32-byte leaf, the bytes look like:

[ 0 … 23 ] → unrelated fields [ 24 … 31 ] → fork.epoch (8 bytes)

To prove this value, you:

  1. Take chunk 1 → this is your leaf.
  2. When hashing up the tree, at each level:
  • If chunk is a left child → record the right sibling hash.
  • If chunk is a right child → record the left sibling hash.
  1. Continue until you reach the top Merkle root.

The collected sibling hashes form your:

SSZ Merkle proof branch for fork.epoch

Anyone can verify this by recomputing:

hash_tree_root(leaf + all_siblings) == state_root

This introduces two new endpoints that expose the initial version of SSZ Query Language (SSZ-QL) in Prysm:

/prysm/v1/beacon/states/{state_id}/query /prysm/v1/beacon/blocks/{block_id}/query

\ Both endpoints follow the SSZ-QL endpoint specification and allow clients to request specific fields inside a BeaconState or BeaconBlock using a query string. The server returns the requested SSZ field encoded as raw SSZ bytes. For now, at the time of writing this, the feature supports only a single query per request, and the include_proof flag is ignored — the PR always returns responses without Merkle proofs.

The request structure is:

type SSZQueryRequest struct { Query string `json:"query"` IncludeProof bool `json:"include_proof,omitempty"` }

And both endpoints return an SSZ-encoded response of this form:

type SSZQueryResponse struct { state protoimpl.MessageState `protogen:"open.v1"` Root []byte `protobuf:"bytes,1,opt,name=root,proto3" json:"root,omitempty" ssz-size:"32"` Result []byte `protobuf:"bytes,2,opt,name=result,proto3" json:"result,omitempty" ssz-max:"1073741824"` unknownFields protoimpl.UnknownFields sizeCache protoimpl.SizeCache }

For the full specification and examples, you can refer to this link

For now, the implementation locates the requested field using the computed offset and size information from the SSZ analyzer, rather than using a generalized index.

:::tip For more information, you can check out Jun Song’s work — implemented together with Fernando as part of their EPF project in prysm.

:::

\

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The meeting pointed out that due to various factors, virtual currency speculation has recently resurfaced, and related illegal and criminal activities have occurred frequently, posing new challenges to risk prevention and control. It emphasized that all units should deepen coordination and cooperation, continue to adhere to the prohibitive policy on virtual currencies, and persistently crack down on illegal financial activities related to virtual currencies. It clarified that stablecoins are a form of virtual currency , and their issuance and trading activities are also illegal and subject to crackdown. This has greatly disappointed those who believed that China would promote the development of RMB stablecoins and correspondingly relax the ban on virtual currency (crypto asset) trading. Therefore, China's policy orientation of accelerating the development of the digital yuan and resolutely curbing virtual currencies, including stablecoins, is now fully clear . Of course, this policy orientation remains highly debated both domestically and internationally, and there is no consensus among the public. So, how should we view this major policy direction of China? This article will first answer why China resolutely halted stablecoins; how to accelerate the innovative development of the digital yuan will be discussed in another article . There is little room or opportunity for the development of non-USD stablecoins. Since Tether launched USDT, a stablecoin pegged to the US dollar, in 2014 , USD stablecoins have been operating for over a decade and have formed a complete international operating system. They have basically dominated the entire crypto asset trading market, accounting for over 99% of the global fiat stablecoin market capitalization and trading volume . This situation arises from two main factors. First, the US dollar is the most liquid and has the most comprehensive supporting system of international central currencies, making stablecoins pegged to the dollar the easiest to accept globally. Second, it is also a result of the US's long-standing tolerant policy towards crypto assets like Bitcoin and dollar-denominated stablecoins, rather than leading the international community to strengthen necessary regulation and safeguard the fundamental interests of all humanity. Even this year, when the US pushed for legislation on stablecoins and crypto assets, it was largely driven by the belief that dollar-denominated stablecoins would increase global demand for the dollar and dollar-denominated assets such as US Treasury bonds, reduce the financing costs for the US government and society, and strengthen the dollar's international dominance. This was a choice made to enhance US support for dollar-denominated stablecoins and control their potential impact on the US, prioritizing the maximization of national interests while giving little consideration to mitigating the international risks of stablecoins. With the US strongly promoting dollar-denominated stablecoins, other countries or regions launching non-dollar fiat currency stablecoins will find it difficult to compete with dollar-denominated stablecoins on an international level, except perhaps within their own sovereign territory or on the issuing institution's own e-commerce platform. Their development potential and practical significance are limited . Lacking a strong ecosystem and application scenarios, and lacking distinct characteristics compared to dollar-denominated stablecoins, as well as the advantage of attracting traders and transaction volume, the return on investment for issuing non-dollar fiat currency stablecoins is unlikely to meet expectations, and they will struggle to survive in an environment of increasingly stringent legislation and regulation in various countries. The legislation on stablecoins in the United States still faces many problems and challenges. Following President Trump's second election victory, his strong advocacy for crypto assets such as Bitcoin fueled a new international frenzy in cryptocurrency trading, driving the rapid development of dollar-denominated stablecoin trading and a surge in stablecoin market capitalization. This not only increased demand for the US dollar and US Treasury bonds, strengthening the dollar's international status, but also brought huge profits to the Trump family and their cryptocurrency associates. However, this also posed new challenges to the global monitoring of the dollar's circulation and the stability of the traditional US financial system. Furthermore, the trading and transfer of crypto assets backed by dollar-denominated stablecoins has become a new and more difficult-to-prevent tool for the US to harvest global wealth, posing a serious threat to the monetary sovereignty and wealth security of other countries . This is why the United States has accelerated legislation on stablecoins, but its legislation is more about prioritizing America and maximizing American and even group interests, at the expense of the interests of other countries and the common interests of the world. After the legislation on US dollar stablecoins came into effect, institutions that have not obtained approval and operating licenses from US regulators will find it difficult to issue and operate US dollar stablecoins in the United States (for this reason, Tether has announced that it will apply for US-issued USDT). Stablecoin issuers subject to US regulation must meet regulatory requirements such as Know Your Customer (KYC), Anti-Money Laundering (AML), and Counter-Terrorist Financing (FTC). They must be able to screen customers against government watchlists and report suspicious activities to regulators. Their systems must have the ability to freeze or intercept specific stablecoins when ordered by law enforcement agencies. Stablecoin issuers must have reserves of no less than 100% US dollar assets (including currency assets, short-term Treasury bonds, and repurchase agreements backed by Treasury bonds) approved by regulators, and must keep US customer funds in US banks and not transfer them overseas. They are prohibited from paying interest or returns on stablecoins, and strict control must be exercised over-issuance and self-operation. Reserve assets must be held in custody by an independent institution approved by regulators and must be audited by an auditing firm at least monthly and an audit report must be issued. This will greatly enhance the value stability of stablecoins relative to the US dollar, strengthen their payment function and compliance, while weakening their investment attributes and illegal use; it will also significantly increase the regulatory costs of stablecoins, thereby reducing their potential for exorbitant profits in an unregulated environment. The US stablecoin legislation officially took effect on July 18, but it still faces numerous challenges : While it stipulates the scope of reserve assets for stablecoin issuance (bank deposits, short-term Treasury bonds, repurchase agreements backed by Treasury bonds, etc.), since it primarily includes Treasury bonds with fluctuating trading prices, even if reserve assets are sufficient at the time of issuance, a subsequent decline in Treasury bond prices could lead to insufficient reserves; if the reserve asset structures of different issuing institutions are not entirely consistent, and there is no central bank guarantee, it means that the issued dollar stablecoins will not be the same, creating arbitrage opportunities and posing challenges to relevant regulation and market stability; even if there is no over-issuance of stablecoins at the time of issuance, allowing decentralized finance (DeFi) to engage in stablecoin lending could still lead to stablecoin derivation and over-issuance, unless it is entirely a matchmaking between lenders and borrowers rather than proprietary trading; getting stablecoin issuers outside of financial institutions to meet regulatory requirements is not easy, and regulation also presents significant challenges. More importantly, the earliest and most fundamental requirement for stablecoins is the borderless, decentralized, 24/7 pricing and settlement of crypto assets on the blockchain. It is precisely because crypto assets like Bitcoin cannot fulfill the fundamental requirement of currency as a measure of value and a value token—that the total amount of currency must change in line with the total value of tradable wealth requiring monetary pricing and settlement—that their price relative to fiat currency fluctuates wildly (therefore, using crypto assets like Bitcoin as collateral or strategic reserves carries significant risks), making it difficult to become a true circulating currency. This has led to the development of fiat stablecoins pegged to fiat currencies. (Therefore, Bitcoin and similar crypto assets can only be considered crypto assets; calling them "cryptocurrency" or "virtual currency" is inaccurate; translating the English word "Token" as "币" or "币" is also inappropriate; it should be directly transliterated as "通证" and clearly defined as an asset, not currency.) The emergence and development of fiat-backed stablecoins have brought fiat currencies and more real-world assets (RWAs) onto the blockchain, strongly supporting on-chain cryptocurrency trading and development. They serve as a channel connecting the on-chain cryptocurrency world with the off-chain real-world, thereby strengthening the integration and influence of the cryptocurrency world on the real world. This will significantly enhance the scope, speed, scale, and volatility of global wealth financialization and financial transactions, accelerating the transfer and concentration of global wealth in a few countries or groups. In this context, failing to strengthen global joint regulation of stablecoins and cryptocurrency issuance and trading poses extremely high risks and dangers . Therefore, the surge in stablecoin and cryptocurrency development driven by the Trump administration in the United States has already revealed a huge bubble and potential risks, making it unsustainable. The international community must be highly vigilant about this! Stablecoin legislation could severely backfire on stablecoins. One unexpected outcome of stablecoin legislation is that the inclusion of fiat-backed stablecoins in legislative regulation will inevitably lead to legislative regulation of crypto asset transactions denominated and settled using fiat-backed stablecoins, including blockchain-generated assets such as Bitcoin and on-chain real-world assets (RWA). This will have a profound impact on stablecoins. Before crypto assets receive legislative regulation and compliance protection, licensed financial institutions such as banks find it difficult to directly participate in crypto asset trading, clearing, custody, and other related activities, thus ceding opportunities to private organizations outside of financial institutions. Due to the lack of regulation and the absence of regulatory costs, existing stablecoin issuers and crypto asset trading platforms have become highly profitable and attractive entities, exerting an increasing impact on banks and the financial system, forcing governments and monetary authorities in countries like the United States to accelerate legislative regulation of stablecoins. However, once crypto assets receive legislative regulation and compliance protection, banks and other financial institutions will undoubtedly participate fully. Payment institutions such as banks can directly promote the on-chain operation of fiat currency deposits (deposit tokenization), completely replacing stablecoins as a new channel and hub connecting the crypto world and the real world . Similarly, existing stock, bond, money market fund, and ETF exchanges can promote the on-chain trading of these relatively standardized financial products through RWA (Real-Time Asset Exchange). Having adequately regulated financial institutions such as banks act as the main entities connecting the crypto world and the real world on the blockchain is more conducive to implementing current legislative requirements for stablecoins, upholding the principle of "equal regulation for the same business" for all institutions, and reducing the impact and risks of crypto asset development on the existing monetary and financial system. This trend has already emerged in the United States and is rapidly intensifying, proving difficult to stop . Therefore, stablecoin legislation may seriously backfire on or subvert stablecoins ( see Wang Yongli's WeChat public account article "Stablecoin Legislation May Seriously Backfire on Stablecoins" on September 3, 2025 ). In this situation, it is not a reasonable choice for other countries to follow the US lead and vigorously promote stablecoin legislation and development. China should not follow the path of stablecoins taken by the United States. China already has a leading global advantage in mobile payments and the digital yuan. Promoting a stablecoin for the yuan has no advantage domestically, and it will have little room for development and influence internationally. It should not follow the path of the US dollar stablecoin, but should instead focus on promoting the development of stablecoins for the yuan, both domestically and offshore. More importantly, crypto assets and stablecoins like Bitcoin can achieve 24/7 global trading and clearing through borderless blockchains and crypto asset trading platforms. While this significantly improves efficiency, the highly anonymous and high-frequency global flow, lacking coordinated international oversight, makes it difficult to meet regulatory requirements such as KYC, AML, and FTC. This poses a clear risk and has been demonstrated in real-world cases of being used for money laundering, fundraising fraud, and illegal cross-border fund transfers. Given that US dollar stablecoins already dominate the crypto asset trading market, and the US has greater control or influence over major global blockchain operating systems, crypto asset trading platforms, and the exchange rate between crypto assets and the US dollar (as evidenced by the US's ability to trace, identify, freeze, and confiscate the crypto asset accounts of some institutions and individuals, and to punish or even arrest some crypto asset trading platforms and their leaders), China's development of a RMB stablecoin following the path of US dollar stablecoins not only fails to challenge the international status of US dollar stablecoins but may even turn the RMB stablecoin into a vassal of US dollar stablecoins. This could impact national tax collection, foreign exchange management, and cross-border capital flows, posing a serious threat to the sovereignty and security of the RMB and the stability of the monetary and financial system. Faced with a more acute and complex international situation, China should prioritize national security and exercise high vigilance and strict control over the trading and speculation of crypto assets, including stablecoins, rather than simply pursuing increased efficiency and reduced costs . It is necessary to accelerate the improvement of relevant regulatory policies and legal frameworks, focus on key links such as information flow and capital flow, strengthen information sharing among relevant departments, further enhance monitoring and tracking capabilities, and severely crack down on illegal and criminal activities involving crypto assets. Of course, while resolutely halting stablecoins and cracking down on virtual currency trading and speculation, we must also accelerate the innovative development and widespread application of the digital yuan at home and abroad, establish the international leading advantage of the digital yuan, forge a Chinese path for the development of digital currency, and actively explore the establishment of a fair, reasonable and secure new international monetary and financial system . Taking into account the above factors, it is not difficult to understand why China has chosen to resolutely curb virtual currencies, including stablecoins, while firmly promoting and accelerating the development of the digital yuan.
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PANews2025/12/06 15:08