隐私层
jiayaoqijia2026-10-25查看 1989复制 1844
> 面向加密 agents 的隐私保护操作。涵盖
📘如何使用这个技能
- 1复制技能内容·点击上方「Copy SKILL.md」复制全部内容,或 Download 下载到本地
- 2打开你的 AI 客户端·支持 Claude Code、Trae、Cursor、ChatGPT、DeepSeek、Kimi 等任意 AI 助手
- 3粘贴为系统提示/知识文件·Claude Code:放入 .claude/skills/ 目录;普通对话:作为首条消息发送并说「请严格按这份技能文档执行」
- 4直接提出你的需求·AI 会按技能定义的工作流、格式和约束来处理,无需再解释背景
💡 提示:技能生效后,每次对话只需一句需求,AI 会按 SKILL.md 的流程执行。
SKILL.md3519 chars
--- name: privacy-layer description: > Privacy-preserving operations for crypto agents. Covers ZK-SNARK private transfers via Railgun Protocol, shielded balances, network egress monitoring, and confidential transaction patterns. Use when asked about private transfers, shielded transactions, or agent privacy. --- # Privacy Layer Privacy-preserving operations for AI agents handling sensitive financial data. ## ZK-SNARK Private Transfers (Railgun Protocol) Railgun enables fully private ERC-20 transfers using ZK-SNARKs on Ethereum. Three core operations: ### Shield (Public → Private) Move tokens from a public address into the Railgun privacy pool: - Tokens become shielded — balance hidden from chain observers - Agent receives a private note commitment - On-chain: only the deposit amount and token are visible ### Private Transfer (Private → Private) Transfer tokens within the privacy pool: - Sender and receiver are hidden on-chain - Amount is hidden via ZK proof - Only the proof validity is verifiable ### Unshield (Private → Public) Withdraw tokens from the privacy pool to a public address: - Converts shielded balance back to standard ERC-20 - Receiver address becomes public ## Railgun Contract Addresses | Network | Contract | Address | |---------|----------|---------| | Ethereum | Relay Adapt | `0xc3f2C8F9d5F0705De706b1302B7a039e1e11aC88` | | Arbitrum | Relay Adapt | `0x5aD95C537b002770a39dea342c4bb2b68B1497aA` | | Polygon | Relay Adapt | `0xc7FfA542736321A3dd69246d73987566a5486968` | | BSC | Relay Adapt | `0x19B620929f97b7b990801496c3b361CA5bbC8E71` | ## Network Egress Monitoring Monitor all outbound connections from the agent to detect data leaks: - Track all RPC calls, HTTP requests, and WebSocket connections - Classify targets as `external` vs `loopback` - Log destination hosts, ports, and protocols - Alert on unexpected outbound connections ## Agent Privacy Architecture ### 1. Secret Isolation - Private keys never sent to LLM — all signing handled in isolated process - Mnemonic stored with `0600` permissions (owner-only read) - Config directory `0700` permissions ### 2. LLM Security Fence - System prompt forbids revealing private keys, mnemonics, API keys - Reduced tool surface — only expose necessary operations - ClawWall DLP catches secrets before they reach the LLM ### 3. Private Inference - Use Venice AI or local Ollama for zero-retention inference - Sensitive data (portfolio values, strategies) processed without provider storage - No training on agent queries ### 4. On-Chain Privacy - Shield balances via Railgun before agent operations - Private transfers between agent sub-wallets - Unshield only when public settlement is needed ## Privacy Checklist for Agents | Risk | Mitigation | |------|------------| | LLM sees private key | ClawWall DLP + system prompt fence | | LLM provider stores queries | Venice (zero retention) or local Ollama | | On-chain activity traced | Railgun shielded transfers | | Network connections leak data | Egress monitoring + allowlist | | Config files exposed | 0600/0700 permissions, fail-loud validation | | Agent overshares in chat | Domain constraint — blockchain-only access | ## Usage Tips - Shield tokens before any sensitive agent operations - Use private transfers for inter-agent payments - Monitor network egress during development to catch unexpected leaks - Always use Venice or local models for strategy-sensitive reasoning - Never expose raw portfolio data to third-party APIs without shielding