Verifying On-Chain Messages: A Technical Guide to Identifying Blockchain Phishing Attempts

On July 8, 2025, the cryptocurrency security community confronted a new breed of blockchain-native phishing attack. BitMEX Research uncovered scammers embedding fraudulent legal notices into Bitcoin transactions using the OP_RETURN opcode, targeting dormant wallets holding billions of dollars in BTC. For technically inclined users and developers, understanding exactly how to identify, analyze, and verify on-chain messages is no longer optional — it is a core security competency. This advanced tutorial walks through the technical process of examining suspicious on-chain data and distinguishing legitimate blockchain activity from phishing attempts.

The Objective

The objective of this tutorial is to equip you with the technical skills needed to independently verify any on-chain message you encounter. By the end, you will be able to decode OP_RETURN data from raw Bitcoin transactions, trace the origin and funding patterns of dust transactions, assess the legitimacy of on-chain claims, and implement automated monitoring for suspicious activity targeting your addresses. This tutorial assumes familiarity with basic Bitcoin concepts and command-line tools.

Prerequisites

Before proceeding, ensure you have the following tools and knowledge. You will need access to a Bitcoin block explorer that displays raw transaction data — mempool.space, blockstream.info, or a personal Bitcoin Core node with REST or RPC enabled. Basic command-line proficiency is required, including familiarity with curl, jq, and hex decoding. A Python 3 environment with the requests and bitcoinlib libraries will be needed for the automated monitoring section. Understanding of Bitcoin transaction structure (inputs, outputs, scripts) is assumed. For on-chain analysis, having access to a blockchain analytics platform like Glassnode or Blockchair’s API is helpful but not required.

Step-by-Step Walkthrough

Step 1: Identify the suspicious transaction. Begin by locating the dust transaction on a block explorer. In the July 8 incident, multiple dust transactions were sent to the 1Feex address (1FeexV6bAHb8ybZi5nhW1J1JgNiAhDnr5A), which holds approximately 80,000 BTC. Navigate to this address on mempool.space and examine the transaction list for unusually small incoming amounts — typically less than 1,000 satoshis. These are your candidate dust transactions.

Step 2: Decode the OP_RETURN output. Click on a dust transaction to view its details. Look for an output with scriptPubKey starting with “6a” — this is the OP_RETURN opcode in hexadecimal. The bytes following “6a” contain the embedded data. For example, the OP_RETURN output from the July 8 scam would contain the hex-encoded version of the message “NOTICE TO OWNER: see salomonbros[.]com/owner_notice.” You can decode the hex using a simple command: echo “4e4f54494345…” | xxd -r -p. Alternatively, mempool.space displays the decoded OP_RETURN text directly in the transaction details under the “Outputs” section.

Step 3: Trace the sending address. Examine the input addresses of the dust transaction. Who sent it? Follow the funds backward through previous transactions to identify the source. In most phishing campaigns, the sending addresses are freshly created with minimal transaction history, funded from a small pool that serves as the scam’s operational wallet. Use the “Transaction” tab on the block explorer to trace inputs backward through multiple hops. This process, known as “following the money,” often reveals patterns — such as multiple dust transactions sent to different high-value addresses from the same funding source — that confirm coordinated malicious activity.

Step 4: Analyze the linked content. If the OP_RETURN message contains a URL, analyze the destination with extreme caution. Use URL scanning services like VirusTotal or URLhaus to check whether the domain has been flagged. Examine the domain’s WHOIS record to determine when it was registered — newly registered domains are inherently suspicious. In the Mt. Gox case, the salomonbros[.]com domain was designed to mimic the historical investment bank Salomon Brothers, but WHOIS analysis would likely reveal recent registration and anonymized ownership details. Never visit suspicious URLs in a browser with active sessions or saved credentials; use a dedicated research environment or a sandboxed browser.

Step 5: Cross-reference with community alerts. Check whether reputable blockchain security researchers have already flagged the activity. BitMEX Research, Whale Alert, and independent security analysts frequently post real-time alerts about new scams on X and specialized forums. Searching for the sending address, the target address, or the domain name from the OP_RETURN message often reveals community analysis that can confirm or deny the legitimacy of the on-chain claim.

Step 6: Build automated monitoring. For users holding significant Bitcoin balances, manual checking is insufficient. Implement automated monitoring using a Bitcoin Core node or a blockchain API. Write a script that polls your addresses for new incoming transactions, filters for dust amounts below a configurable threshold, and checks for OP_RETURN outputs in those transactions. When a suspicious transaction is detected, the script should alert you immediately and automatically decode any OP_RETURN data for review. The bitcoin-cli getaddressinfo and getrawtransaction RPC commands provide the raw data needed, while a Python wrapper can handle the filtering and alerting logic.

Troubleshooting

Problem: The block explorer shows no OP_RETURN data. Some block explorers truncate or simplify transaction details. Try a different explorer or use the raw transaction hex. On mempool.space, click “Raw” to see the complete transaction data, then manually locate the OP_RETURN output by looking for the “6a” prefix in the scriptPubKey field.

Problem: The hex decoding produces garbled text. The OP_RETURN data may use a non-UTF-8 encoding or may contain binary data rather than plain text. Try different encodings (ASCII, UTF-16) or examine the raw bytes for patterns. Some OP_RETURN messages use protocol-specific formats like OmniLayer or Counterparty encoding rather than plain text.

Problem: The automated monitoring script produces too many false positives. Legitimate services also send dust transactions for various purposes, including payment batching and address labeling. Refine your filters by adding criteria such as: only flag transactions from addresses with fewer than 10 prior transactions, only flag transactions that contain URLs in the OP_RETURN data, and only flag transactions sent to addresses with balances above a certain threshold.

Problem: You cannot determine whether a message is legitimate. When in doubt, assume it is not. The Bitcoin blockchain provides no mechanism for authenticating the source of OP_RETURN data. Any claim made via OP_RETURN should be treated as unverified until confirmed through independent channels. Contact the purported sender through their official website or verified communication channels — never through information provided in the on-chain message itself.

Mastering the Skill

Verifying on-chain messages is a skill that improves with practice. Start by examining historical OP_RETURN transactions on well-known addresses to develop pattern recognition. The Bitcoin blockchain is full of OP_RETURN data from legitimate projects, protocol messages, and even artistic expressions — understanding what “normal” looks like makes it easier to spot anomalies. Build a personal library of known OP_RETURN patterns and their associated protocols, so you can quickly classify new transactions you encounter.

Stay current with the evolving threat landscape by following blockchain security research publications and participating in community-driven analysis forums. The techniques used in the July 8, 2025 Mt. Gox scam represent an early example of blockchain-native phishing, and more sophisticated variants are inevitable. As Bitcoin’s price continues to climb — reaching $108,950 on the day of the incident — the financial incentives for attackers will only increase. Technical literacy in on-chain analysis is not just a nice-to-have skill; it is a critical component of cryptocurrency security in 2025 and beyond.

Disclaimer: This article is for educational purposes only and does not constitute financial or security advice. Always conduct your own research and consult with qualified professionals regarding cryptocurrency security.