Crypto payment scams cost users billions annually. Address poisoning, fake recipient wallets, and social engineering attacks all exploit a fundamental gap: users can’t easily verify whether a payment is safe before sending. The Payment Risk Assessment endpoint closes that gap by analyzing 8 risk dimensions in real time - before funds leave the wallet. This guide covers the three risk factors most relevant to scam prevention and how to build them into your payment flow.Documentation Index
Fetch the complete documentation index at: https://docs.range.org/llms.txt
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Prerequisites: You need a Risk API key and familiarity with the Payment Risk Assessment endpoint.
The Three Scam-Relevant Risk Factors
Payment Risk Assessment evaluates 8 independent risk dimensions. Three are directly designed to catch common payment scams:| Risk Factor | What It Catches | Risk Level |
|---|---|---|
| Address Poisoning Detection | Scammer creates a lookalike address that matches the first/last 4 characters of a real contact | HIGH |
| New Wallet Detection | Recipient is a freshly created wallet with no history - common in advance-fee fraud and impersonation scams | MEDIUM–HIGH |
| Interaction History | Sender has never transacted with this recipient before - flags unfamiliar counterparties | HIGH |
How Address Poisoning Works
Address poisoning is one of the most common crypto scams. Here’s the attack:- The scammer monitors the victim’s transaction history
- They generate an address that matches the first and last 4 characters of a real recipient the victim has sent to before
- They send a small “dust” transaction from the poisoned address to the victim
- The victim later copies the address from their transaction history, unknowingly selecting the scammer’s lookalike address
- Funds are sent to the scammer instead of the intended recipient
How Payment Risk Assessment Detects It
Theaddress_poisoning_attack factor compares the recipient address against known poison address patterns associated with the sender. If the recipient’s prefix and suffix match a poisoning pattern, it returns HIGH risk.
How New Wallet Scams Work
Many scams involve directing victims to send funds to newly created wallets:- Impersonation scams - “Send funds to this new wallet for verification”
- Fake investment schemes - Scammer provides a brand-new deposit address
- Romance scams - Victim is given a fresh wallet address to “help” with
- Phishing - Fake dApp or site provides a newly generated receiving address
How Payment Risk Assessment Detects It
Thenew_wallet_recipient factor analyzes the recipient’s onchain transaction history:
| Recipient History | Risk Level | Factor |
|---|---|---|
| 0 transactions | HIGH | new_wallet_recipient |
| <3 transactions OR <7 days old | MEDIUM | new_wallet_recipient |
| ≥3 transactions AND >7 days old | LOW | established_wallet_recipient |
How First-Interaction Risk Works
Even without address poisoning or a new wallet, sending to someone you’ve never transacted with before carries inherent risk. Scams overwhelmingly involve first-time interactions - the victim has no prior relationship with the scammer’s address.How Payment Risk Assessment Detects It
Thefirst_interaction factor examines the transaction history between sender and recipient across both same-network and cross-chain indices:
| Prior Interactions | Risk Level | Factor |
|---|---|---|
| 0 (first time) | HIGH | first_interaction |
| 1–2 interactions | MEDIUM | limited_interaction_history |
| 3+ interactions | LOW | established_interaction_history |
A first interaction is not inherently malicious - everyone has a first transaction. The value is in combining it with other factors. A first interaction with an established wallet is normal. A first interaction with a brand-new wallet that matches a poisoning pattern is almost certainly a scam.
Building a Scam Prevention Flow
Step 1: Check Payment Risk Before Sending
Step 2: Extract Scam-Relevant Factors
Step 3: Display Warnings to Users
Scam Pattern Reference
| Scam Type | Triggered Factors | Combined Risk |
|---|---|---|
| Address poisoning | address_poisoning_attack | Critical |
| Impersonation / phishing | new_wallet_recipient + first_interaction | High |
| Advance-fee fraud | new_wallet_recipient + first_interaction | High |
| Compromised account | first_interaction + malicious_connection_recipient_high | High |
| Fake investment | new_wallet_recipient + first_interaction | High |
| Typo / wrong address | first_interaction (no poisoning) | Medium |
| Legitimate new contact | first_interaction + established_wallet_recipient | Low–Medium |
| Regular payment | established_interaction_history + established_wallet_recipient | Low |
Integration Recommendations
For Wallets
- Run Payment Risk Assessment on every send before the user signs
- Display scam warnings inline - not as a separate step users can skip
- For address poisoning: show a full-screen blocker, not a dismissable toast
- Cache results briefly (30 seconds) to avoid re-querying if the user adjusts the amount
For Payment Processors
- Check both directions: screen the sender when receiving, screen the recipient when sending
- Log all risk assessments for dispute resolution and fraud investigation
- Set automated hold policies for first-interaction payments above a threshold amount
For Exchanges
- Run Payment Risk Assessment on withdrawal requests before processing
- Flag
address_poisoning_attackresults for manual review - these are almost never false positives - Use
first_interaction+new_wallet_recipientto trigger additional verification (email confirmation, 2FA) on withdrawals to new addresses
What’s Next
Payment Risk Assessment
Full endpoint reference with all 8 risk dimensions explained.
Wallet Integration
Add address screening and transaction simulation to your wallet.

