how-toAIexchanges

Step-by-Step: Setting Up Read-Only AI Access to Your Exchange and Wallet Activity

UUnknown

2026-02-16

11 min read

Securely connect AI tools to exchanges and wallets using read-only keys, ephemeral tokens, and private compute — avoid handing over signing keys.

Stop handing over signing keys. Start extracting signals and tax summaries safely.

If you trade across exchanges and wallets, you already know the pain: you need consolidated analytics and tax-ready reporting, but giving full API keys or wallet signing access to AI tools is a liability. This guide shows, step-by-step, how to provision strict read-only access for AI analysis tools so you get high-quality trading signals and tax summaries without enabling trades, transfers, or signing operations.

Quick summary — what you’ll get in 10 minutes

Concrete steps to create read-only API keys on major exchanges (Coinbase, Binance, Kraken).
How to expose wallet activity safely via node providers and indexers (Alchemy, Infura, QuickNode, Covalent, The Graph, Etherscan).
Security hardening: scopes, IP allowlisting, expirations, monitoring and rotations.
Best practices for connecting AI tools: ephemeral tokens, local processing, and privacy-preserving flows.
Tax summarization and signal-extraction taxonomy you can implement immediately.

Why read-only AI access matters in 2026

Late 2025 and early 2026 saw rapid adoption of AI-driven portfolio and tax tools. Vendor features improved, and regulators increased scrutiny of exchanges and third-party integrators. At the same time, high-profile incidents showed how agentic AI and careless credential handling can magnify risk. That combination created demand for a clear, auditable read-only pattern that balances utility with security.

“Agentic file management shows real productivity promise. Security, scale, and trust remain major open questions.” — David Gewirtz, ZDNet, Jan 2026

Companies and traders now expect: granular API scopes, short-lived credentials, and the option to run analysis in private cloud/VPC/air-gapped environment. This guide uses those 2026 controls as a baseline.

Prerequisites — what you’ll need before starting

An account on the exchange(s) or wallet(s) you want to analyze.
Access to an AI analysis tool that supports either: (a) connecting via read-only API keys, (b) uploading CSV/JSON transaction history, or (c) running in a private cloud/VPC/air-gapped environment.
Optional: a node/indexer provider account (Alchemy, Infura, QuickNode, Covalent, The Graph, Etherscan) for on-chain reads without exposing private keys.
2FA/Hardware security device for your accounts to protect admin operations.

Step 1 — Create read-only API keys on exchanges (general rules)

Across exchanges the principle is the same: create an API key with the minimum possible permissions — typically a “view” or “read-only” scope that allows account and trade history queries but not trading or withdrawals.

Best-practice API scope checklist

Allow: account balances, order history, fills/trades, deposit/withdrawal history, margin/positions readout (if needed).
Deny: trading, withdrawals, transfers, margin-leverage changes, order placement.
Enable: IP allowlist where the AI tool’s outbound IPs are known, and expiry timestamps for keys.
Audit: enable API logs/alerts and set notification thresholds for abnormal API usage.

Examples: How major exchanges implement read-only scopes (2026)

Coinbase (Advanced/Pro API)

Go to Settings → API.
Create API key and select view permissions only. Do NOT check trade or transfer.
Set an expiration (30–90 days) and copy key + passphrase securely.
Use IP restrictions: list the AI tool provider’s IPs or your own proxy IP.

Binance

Navigate to API Management.
Create key and uncheck ‘Enable Trading’ and ‘Enable Withdrawals’ — only enable ‘Enable Reading’.
Set API restrictions to whitelist IPs and restrict endpoints where possible.

Kraken

API → Add Key.
Set permissions to only include Query Funds and Query Open Orders/Trades.
Limit by IP and record the key ID for audits.

Note: The exact UI changes over time; always verify that trade/withdraw permissions are unchecked. If an exchange does not offer a read-only scope, treat that provider as higher risk — prefer exporting CSVs or running local tooling instead.

Step 2 — Expose wallet activity safely (on-chain read patterns)

Wallets (non-custodial) don’t have “API keys” in the same way; instead, use indexers and node providers for read access to an address's activity.

Providers and their roles

Etherscan/Polygonscan/Bscscan: address transaction lists and token transfers.
Alchemy / Infura / QuickNode: RPC endpoints for JSON-RPC read operations (eth_getLogs, getTransactionReceipt, balanceOf).
Covalent / Bitquery / Flipside / Dune: indexed, normalized datasets and SQL interfaces for faster queries across chains.

Step 3 — Configure the AI connection: safe patterns

How you connect your read-only keys to the AI matters. Below are secure integration patterns prioritized from most to least secure.

Pattern A — Private compute (most secure)

Run the AI analysis tool in your cloud VPC (or on-prem) and provide keys that only work from that VPC IP range; pair this with robust distributed file systems for hybrid cloud when you need long-term storage.
Use short-lived tokens created by your central secrets manager (AWS Secrets Manager, HashiCorp Vault) and rotate them automatically.
Data never leaves your environment unless you opt in — best for sensitive tax/reporting workflows.

Pattern B — Ephemeral service account tokens

Use OAuth or an exchange-provided OAuth-like delegation flow where available, granting read-only permission and an expiration.
Prefer tools that support granular OAuth/consent screens rather than raw static API keys.

Pattern C — Upload sanitized export files (least risky)

Export trade/wallet CSVs or JSON from the exchange or indexer, sanitize sensitive fields, and upload to the AI tool.
This avoids any API key sharing but requires manual or scheduled exports.

Practical controls to demand from AI vendors

Support for read-only OAuth or ephemeral API tokens.
IP allowlisting and proof of possession for tokens.
Data residency options and the ability to run in your private cloud.
Audit logs and access transparency (who queried what and when).

Step 4 — Data hygiene: normalize, label, and preserve audit trails

An AI tool can only produce good signals and tax summaries if the input is clean and well-labeled. Implement these steps to make outputs reliable and defensible for tax filing.

Normalization pipeline

Ingest raw trade and transfer data from each source.
Map exchange-specific event types to a canonical taxonomy: BUY, SELL, SWAP/DEX, TRANSFER-IN, TRANSFER-OUT, FEE, STAKING-REWARD.
Enrich records with price at timestamp (use CryptoCompare, CoinGecko, or an exchange price API) and with chain-specific metadata (token decimals, pair symbols).
Tag internal transfers between your own wallets/accounts to avoid double-counting.
Retain a full raw data copy and store transformed records separately for audits.

Tax-specific operations

Implement cost-basis methods explicitly (FIFO, LIFO, HIFO) and allow auditors to recompute with alternate methods.
Detect taxable events: disposals, trades, swaps, and spent tokens. Not all transfers are disposals.
Special-case NFTs, staking rewards, airdrops, and bridging events — document assumptions and provide traceability.

Step 5 — Signal extraction: what AI should see and infer

When configuring the AI, choose the minimal dataset required to extract the signals you want. Typical analytic outputs include momentum indicators, position-level P&L, realistic execution slippage estimates, and pattern-detection for suspicious activity.

Data to expose to the AI

Time-series: per-trade timestamp, side, price, size, fee, exchange pair.
Balance snapshots: daily or hourly balance per asset.
Order-level metadata (only if read-only): order type, filled amount, partial fills.
Normalized trade history from wallets (on-chain transfers, contract interactions labeled by type).

Signal types to derive

Portfolio risk signals: concentration, unilateral exposure to token/chain.
Behavioral signals: consistency of execution, frequent rebalancing, stop-loss patterns.
On-chain alpha signals: large-level liquidity changes, whale transfers, contract approvals spikes.
Tax signals: realized gains/losses buckets, wash sale flags (where applicable by jurisdiction), short-term vs long-term holdings.

Step 6 — Test and validate without risk

Before you give any keys to a vendor or connect a private compute node, run these tests.

Create a “canary” read-only key limited to a test account or a subset of addresses.
Run the AI integration in a dry-run mode that does not make outbound calls beyond the provider.
Verify that the AI performs only GET/READ RPC and REST calls. A quick log inspection should show no POST/PUT actions to trading endpoints.
Confirm the results match a local reconciliation script for balances and trades.

Monitoring, alerts and incident playbook

Assume keys will be misused someday. Prepare detection and response now.

Enable exchange API logging and alert for unusual patterns like high-frequency order requests (indicative of attempted trading).
Set up balance-change alerts directly on your exchange (email/SMS/hardware notification) for transfers or withdrawals.
Keep a response runbook: revoke the key, rotate secrets, and audit vendor logs and your own cloud logs — practice with a simulated agent compromise to validate processes.

Advanced strategies for privacy and security (2026 best practices)

For professional investors and fund managers, adopt these 2026-forward techniques.

On-device or local LLM inference

Where possible, run signal extraction models locally. This minimizes data exfiltration risk and keeps proprietary strategies private — see guidance on edge AI reliability.

Private embeddings + vector DB in VPC

Store embeddings derived from your transaction history in a VPC-hosted vector database (Pinecone, Milvus, or self-hosted). Let the AI perform retrieval over this private index rather than sending raw transaction streams to a third-party model endpoint. Consider auto-sharding and scaling blueprints when you manage a large private index.

Differential privacy and data minimization

Apply minimalization: redact wallet labels, truncate precise timestamps to windows when not needed, and add small noise to on-chain amounts if you are sharing with external teams — but retain raw data for auditors. Keep an eye on evolving laws and consumer protections; recent coverage of crypto compliance and consumer rights is a helpful lens.

Case study: end-to-end example (Alice, active trader, 2026)

Alice runs across Binance, Coinbase Advanced, and several self-custodial wallets. She wants weekly AI-driven signals and quarterly tax summaries without exposing signing keys.

She creates read-only keys on Coinbase and Binance with view-only scopes, 30-day expiry, and IP allowlist locked to her cloud proxy.
She deploys a private AI instance in her cloud VPC and uses ephemeral tokens from Vault to grant temporary analysis access for 2 hours a week.
For her wallets, she connects Alchemy read-only RPC keys and uses Covalent to bulk-query token transfer histories; she never shares private keys.
She implements a normalization pipeline that tags internal transfers and computes FIFO cost basis while the AI generates signals in a scheduled job.
Audit logs capture every request; an alert triggers if any non-read API call is attempted. Key rotation policies force all read-only keys to be rotated every 60 days.

Common pitfalls and how to avoid them

Giving away master API keys: Create dedicated keys per vendor or per use-case and never reuse master account credentials.
Assuming read-only is safe forever: Read-only keys can still leak sensitive information. Use VPCs and ephemeral tokens.
Not validating vendor behavior: Require vendors to provide logs and proof they only executed read calls.
Over-sharing wallet metadata: Public addresses can reveal strategy; redact or aggregate when sharing externally.

Regulatory context — what changed in 2025–2026

Recent policy and market trends matter for how you design integrations:

Exchanges are offering more granular API scopes and OAuth-style flows after pressure for consented data access increased in late 2025.
Auditors and tax authorities expect traceable, auditable cost basis calculations — tools that cannot produce audit trails risk disputes. See work on automating compliance checks for a sense of tooling maturity.
Privacy requirements in some jurisdictions encourage data minimization; choose in-scope data exports carefully.

Actionable checklist — before you connect an AI

Create dedicated read-only keys per exchange and per AI vendor.
Enable IP allowlisting and set short expiration windows.
Run a dry test verifying only GET/RPC read calls occur.
Normalize and retain raw copies for auditability.
Record your cost-basis method and make it exportable for tax professionals.
Rotate or revoke keys after any suspicious activity immediately.

Closing takeaways

In 2026, the ability to safely extract trading signals and produce tax-ready summaries without exposing signing keys is table stakes. Follow the least-privilege principle: use read-only scopes, ephemeral tokens, private compute where feasible, and a strict audit and rotation policy. Insist vendors support granular consent and transparency — your security and regulatory compliance depend on it.

Remember: never hand over private keys or master credentials. Use dedicated read-only credentials, keep full audit trails, and test integrations in dry-run mode before going live.

Next steps — try this now

Use the checklist above to harden one exchange and one wallet today. If you want a template for read-only API key naming, rotation schedules, and a sample normalization schema (CSV + JSON), download our free configuration pack at crypts.site/tools (or sign up below for the 2026 security checklist PDF).

Call to action: Harden your pipeline now — sign up for our newsletter to get the 2026 Read-Only AI Integration Checklist and a sample Vault script to issue ephemeral tokens for AI vendors.

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