ZK证明系统在组件化设计中的安全假设与可信计算基的治理难题

zkcustody/
├── circuits/                    # ZK 电路定义与编译
│   ├── voting.cairo            # Cairo 电路源码（核心逻辑）
│   ├── compile_circuit.py      # 电路编译脚本
│   └── trusted_setup_phase1_output.json # 可信启动阶段1产出（示例）
├── contracts/
│   └── Verifier.sol            # 链上验证合约
├── backend/
│   ├── prover_service.py       # 证明生成服务
│   ├── models.py               # 数据模型（投票、证明等）
│   └── config.yaml             # 后端配置（含安全假设声明）
├── governance/
│   ├── key_ceremony.py         # 可信启动模拟与密钥管理
│   ├── security_policy.json    # 安全策略定义（TCB治理规则）
│   └── audit_logger.py         # TCB 关键操作审计日志
├── tests/
│   ├── test_circuit_logic.py   # 电路逻辑单元测试
│   └── test_integration.py     # 组件集成测试
├── scripts/
│   └── run_demo.py             # 端到端演示脚本
├── requirements.txt            # Python 依赖
└── README.md                   # 项目说明（此处仅为示意，输出时不包含）

# 注意：此为概念性代码，模拟Cairo风格。真实Cairo语法更接近汇编。
# 核心约束系统定义
def voting_circuit(
    private salt: felt,
    private balance: felt,
    public committed_hash: felt,
    public threshold: felt
) -> (public output: felt):
    # 安全假设1: 使用 MiMC 哈希函数（在真实环境中需用电路内建函数实现）
    # 计算 hash = MiMC(salt, balance)
    let hash = mimc_hash(salt, balance)

    # 公共输入约束：计算的哈希必须等于承诺的哈希
    assert hash == committed_hash

    # 隐私逻辑约束：余额必须大于等于投票阈值
    # 通过引入一个辅助变量 `diff` (balance - threshold) 并证明其非负性来实现。
    # 非负性检查通常需要范围证明或布尔分解，此处极度简化。
    let diff = balance - threshold
    # 简化假设：我们有一个证明`diff`为非负的电路组件 `is_non_negative`
    # 这本身是一个重要的安全子假设。
    let is_valid = is_non_negative(diff)
    assert is_valid == 1

    # 输出一个成功信号（例如，1）
    return (1)

// SPDX-License-Identifier: MIT
pragma solidity ^0.8.19;

// 引入通过 snarkjs 或类似工具生成的验证库接口
// 这里简化表示为对一个预编译合约或库的调用
interface IVerifier {
    function verifyProof(
        uint256[2] memory a,
        uint256[2][2] memory b,
        uint256[2] memory c,
        uint256[] memory input
    ) external view returns (bool);
}

contract VotingVerifier {
    address public verifierContract;
    uint256 public constant VOTE_THRESHOLD = 100; // 公开的投票阈值

    // 安全假设2：验证合约地址在部署时被正确设置且不可变。
    constructor(address _verifier) {
        verifierContract = _verifier;
    }

    /**

     * @dev 验证一个投票证明。
     * @param a, b, c - Groth16 zkSNARK 证明的椭圆曲线点
     * @param committedHash - 公开输入，用户余额哈希的承诺
     * 公开输入数组 input = [committedHash, VOTE_THRESHOLD]
     * TCB治理点：此函数是链上TCB的一部分，其逻辑必须绝对正确。
     */
    function castVote(
        uint256[2] memory a,
        uint256[2][2] memory b,
        uint256[2] memory c,
        uint256 committedHash
    ) external returns (bool) {
        uint256[] memory input = new uint256[](2);
        input[0] = committedHash;
        input[1] = VOTE_THRESHOLD;

        bool success = IVerifier(verifierContract).verifyProof(a, b, c, input);
        require(success, "Invalid ZK proof");

        // 证明验证通过，执行投票逻辑（此处省略）
        // emit VoteCast(msg.sender, committedHash);
        return true;
    }
}

import json
import hashlib
from dataclasses import dataclass, asdict
from typing import List, Tuple
from cryptography.hazmat.primitives import serialization
from cryptography.hazmat.primitives.asymmetric import rsa
from cryptography.hazmat.primitives import hashes
from cryptography.hazmat.primitives.asymmetric import padding
import logging

@dataclass
class CeremonyParticipant:
    """代表一个可信启动仪式的参与者。"""
    name: str
    public_key_pem: str  # RSA公钥，用于签名贡献
    contribution_signature: str = None  # 对该参与者贡献的签名

class TrustedSetupManager:
    """
    可信计算基(TCB)的关键部分：管理zkSNARK可信启动仪式。
    安全假设3：此类实例的运行环境（硬件、OS、人员访问）是高度可信的。
    """
    def __init__(self, curve_name: str = "BN254", policy_path: str = "governance/security_policy.json"):
        self.curve = curve_name
        self.participants: List[CeremonyParticipant] = []
        self.final_parameters = {}  # 模拟最终的 proving/verification key
        self.audit_logger = logging.getLogger("tcb_audit")
        self._load_policy(policy_path)

    def _load_policy(self, path: str):
        """加载安全治理策略。"""
        with open(path, 'r') as f:
            self.policy = json.load(f)
        self.audit_logger.info(f"Security policy loaded: {self.policy.get('description')}")

    def add_participant(self, participant: CeremonyParticipant):
        """按照策略添加参与者。"""
        if len(self.participants) >= self.policy.get("max_participants", 10):
            raise ValueError("Maximum participants reached as per policy.")
        self.participants.append(participant)
        # TCB关键操作审计日志
        self.audit_logger.critical(
            f"Participant added to ceremony: {participant.name}",
            extra={'action': 'add_participant', 'participant': participant.name}
        )

    def simulate_phase1_contribution(self, previous_output: dict) -> dict:
        """
        模拟单个参与者的贡献（例如，对tau幂的随机偏移）。
        在实际中，这会涉及复杂的椭圆曲线运算。
        """
        # 简化模拟：参与者生成一个随机数，并"混合"到参数中
        import secrets
        participant_random = secrets.token_hex(32)
        # 模拟对之前参数的"扰动"
        previous_output['contributions'].append(participant_random)
        previous_output['last_contributor'] = participant_random[:8]
        return previous_output

    def run_ceremony(self, initial_params: dict) -> Tuple[dict, List[str]]:
        """
        执行多参与者可信启动仪式。
        返回最终的参数和所有贡献的签名列表。
        """
        self.audit_logger.critical("Trusted Setup Ceremony STARTED")
        current_params = initial_params
        signatures = []

        for i, participant in enumerate(self.participants):
            self.audit_logger.critical(f"Participant {i+1} ({participant.name}) contributing...")
            # 1. 参与者收到当前参数
            # 2. 参与者在其隔离环境中贡献随机性
            current_params = self.simulate_phase1_contribution(current_params)
            # 3. 参与者生成贡献的签名（使用其私钥，此处模拟）
            contribution_hash = hashlib.sha256(json.dumps(current_params, sort_keys=True).encode()).hexdigest()
            # 模拟签名过程
            fake_signature = f"SIG_{participant.name}_{contribution_hash[:16]}"
            participant.contribution_signature = fake_signature
            signatures.append(fake_signature)
            # 4. 发布带签名的更新后参数

        self.final_parameters = current_params
        self.final_parameters['signatures'] = signatures
        self.audit_logger.critical(
            "Trusted Setup Ceremony COMPLETED",
            extra={'final_params_hash': hashlib.sha256(json.dumps(self.final_parameters, sort_keys=True).encode()).hexdigest()}
        )
        return self.final_parameters, signatures

    def get_proving_key(self) -> dict:
        """分发用于生成证明的密钥。访问需授权。"""
        if not self.final_parameters:
            raise ValueError("Ceremony not yet completed.")
        # 在实际中，这里会从 final_parameters 导出具体的 proving_key
        return {"type": "proving_key", "curve": self.curve, **self.final_parameters}

    def get_verification_key(self) -> dict:
        """分发用于验证的密钥。将最终被部署到智能合约。"""
        if not self.final_parameters:
            raise ValueError("Ceremony not yet completed.")
        # 生成 verification_key 的简化模拟
        vk = {
            "type": "verification_key",
            "curve": self.curve,
            "alpha_g1": "0x...",
            "beta_g2": "0x...",
            "gamma_g2": "0x...",
            "delta_g2": "0x...",
            "ic": ["0x..."] * 3,
        }
        return vk

import json
import time
from models import VoteStatement, ZKProof
from governance.audit_logger import tcb_audit_logger

class ProverService:
    """
    证明生成服务。它依赖于：

    1. 正确的电路逻辑 (circuits/)
    2. 有效的可信启动参数 (governance/)
    3. 安全的随机数生成（用于盐值）
    安全假设4：运行此服务的服务器不会泄露输入的隐私数据（盐值、余额）。
    """
    def __init__(self, proving_key_path: str):
        with open(proving_key_path, 'r') as f:
            self.proving_key = json.load(f)
        tcb_audit_logger.info(f"ProverService initialized with key from {proving_key_path}")

    def generate_proof(self, vote_statement: VoteStatement) -> ZKProof:
        """
        根据私密输入和公开承诺生成ZK证明。
        此处模拟了与`snarkjs`或类似证明库的交互。
        """
        # 模拟私密输入和公开输入的预处理
        private_inputs = {
            'salt': vote_statement.salt,
            'balance': vote_statement.balance
        }
        public_inputs = [
            vote_statement.committed_hash,
            vote_statement.threshold
        ]

        tcb_audit_logger.info(f"Generating proof for commitment {vote_statement.committed_hash[:16]}...")

        # --- 模拟核心证明生成算法（Groth16） ---
        # 在现实中，这里会调用`snarkjs groth16 prove`或类似库的API
        # 涉及椭圆曲线配对、域上运算等。
        # 我们模拟一个延迟并返回结构化数据。
        time.sleep(0.5)  # 模拟计算耗时

        # 模拟生成的证明数据（Groth16 的 A, B, C 点）
        simulated_proof = {
            "pi_a": ["0x123abc...", "0x456def..."],
            "pi_b": [["0x789ghi...", "0x0jklmno..."], ["0x0pqrst...", "0xuvwxyz..."]],
            "pi_c": ["0x141592...", "0x653589..."],
            "protocol": "groth16",
            "curve": self.proving_key.get("curve")
        }

        proof = ZKProof(
            proof_data=simulated_proof,
            public_inputs=public_inputs,
            verification_key_id=self.proving_key.get("final_params_hash", "unknown")
        )

        tcb_audit_logger.info(f"Proof generated successfully. VK ID: {proof.verification_key_id}")
        return proof

{
  "description": "ZKCustody 系统可信计算基(TCB)安全策略",
  "version": "1.0",
  "trusted_setup": {
    "curve": "BN254",
    "required_participants": 3,
    "max_participants": 10,
    "participant_approval_process": "multi-signature by governance council",
    "contribution_environment": "air-gapped machine, audited OS image"
  },
  "key_management": {
    "proving_key_access": "restricted to authorized prover services only",
    "verification_key_deployment": "requires governance proposal and 7-day timelock",
    "key_rotation_policy": "triggered upon suspicion or annually, requires new ceremony"
  },
  "audit": {
    "immutable_logging": true,
    "log_public_endpoint": "/tcb-audit",
    "regular_third_party_audit": "quarterly"
  },
  "security_assumptions": [
    "BN254 curve is secure against all known attacks.",
    "MiMC hash function is collision-resistant in the circuit context.",
    "All ceremony participants destroyed their toxic waste (randomness).",
    "The underlying zkSNARK library (e.g., snarkjs) is implemented correctly."
  ]
}

# 在项目根目录 `zkcustody/` 下执行
pip install -r requirements.txt

cryptography>=41.0.0
pyyaml>=6.0
loguru>=0.7.0  # 用于更友好的日志，审计部分可用
pytest>=7.4.0  # 用于运行测试

python scripts/run_demo.py

# 运行电路逻辑测试（模拟）
python -m pytest tests/test_circuit_logic.py -v

# 运行集成测试，模拟证明生成与验证流程
python -m pytest tests/test_integration.py -v

import sys
sys.path.append('.')
from backend.models import VoteStatement
from backend.prover_service import ProverService
from governance.key_ceremony import TrustedSetupManager, CeremonyParticipant

def test_end_to_end_flow():
    """模拟从可信启动到证明验证的流程。"""
    # 1. 初始化TCB（可信启动管理器）
    tsm = TrustedSetupManager(policy_path="governance/security_policy.json")

    # 2. 模拟添加参与者
    participant1 = CeremonyParticipant(name="Alice", public_key_pem="fake_pem_alice")
    participant2 = CeremonyParticipant(name="Bob", public_key_pem="fake_pem_bob")
    participant3 = CeremonyParticipant(name="Charlie", public_key_pem="fake_pem_charlie")
    tsm.add_participant(participant1)
    tsm.add_participant(participant2)
    tsm.add_participant(participant3)

    # 3. 运行可信启动仪式
    initial_params = {"phase": 1, "contributions": []}
    final_params, sigs = tsm.run_ceremony(initial_params)
    assert len(sigs) == 3
    print(f"Ceremony completed with {len(sigs)} signatures.")

    # 4. 获取证明密钥（模拟）
    proving_key = tsm.get_proving_key()
    assert proving_key["type"] == "proving_key"

    # 5. 初始化证明服务
    prover = ProverService(proving_key_path=None)  # 简化，直接使用对象
    prover.proving_key = proving_key

    # 6. 创建一个有效的投票声明
    # 假设用户余额为150，阈值为100。盐值为随机数。
    import secrets
    salt = secrets.randbits(256)
    balance = 150
    threshold = 100
    # 模拟计算 committed_hash (实际应与电路中使用的哈希一致)
    # 此处仅做演示
    committed_hash = hash((salt, balance)) % (2**128)  # 简化哈希

    statement = VoteStatement(
        salt=salt,
        balance=balance,
        committed_hash=committed_hash,
        threshold=threshold
    )

    # 7. 生成证明
    proof = prover.generate_proof(statement)
    assert proof.verification_key_id is not None
    assert len(proof.proof_data["pi_a"]) == 2
    print("Proof generated successfully.")
    print(f"Public Inputs: {proof.public_inputs}")

    # 8. 验证步骤（此处模拟，实际应调用合约或验证库）
    # 假设验证成功
    verification_success = True
    assert verification_success, "Proof should be valid"
    print("Integration test passed!")