The Multichain bridge exploit of July 5, 2023, which resulted in the theft of approximately $130 million across Fantom, Moonriver, and Dogechain networks, provides a real-world case study for understanding how on-chain forensic analysis works in practice. As Bitcoin traded near $30,514 and Ethereum hovered around $1,911, blockchain security researchers and on-chain analysts scrambled to trace the movement of stolen funds across multiple chains in real time. This advanced tutorial walks through the techniques and tools used by professional on-chain investigators to follow the money after a major exploit, providing a technical framework that experienced crypto users can apply to their own security monitoring.
The Objective
The primary objective of on-chain forensics after a bridge exploit is to trace the flow of stolen funds from the initial attack addresses through subsequent transactions, across chain hops, and into eventual liquidation endpoints such as decentralized exchanges, mixing services, or centralized exchanges. In the Multichain case, the attacker moved assets from bridge smart contracts on Fantom, Moonriver, and Dogechain into externally owned accounts under their control. The forensic challenge then becomes tracking those funds as they are swapped, bridged to other networks, and potentially laundered through privacy tools. Understanding this process requires familiarity with blockchain explorers, transaction graph analysis, and the specific mechanics of cross-chain transfers.
Prerequisites
Before conducting on-chain forensic analysis, you need several tools and capabilities. A reliable block explorer that supports multiple chains, such as Etherscan for Ethereum, Ftmscan for Fantom, and Moonscan for Moonriver, is essential. For bulk transaction analysis, platforms like Nansen, Dune Analytics, or the Arkham Intelligence dashboard provide the ability to query and visualize transaction patterns at scale. You should be comfortable reading raw transaction data, including understanding input data fields, internal transactions, and event logs. Familiarity with the Ethereum Virtual Machine and how ERC-20 token transfers are logged through Transfer events will be necessary. For the Multichain analysis specifically, understanding how bridge contracts lock and mint tokens, and how the MPC key compromise allowed unauthorized withdrawals, provides the technical context needed to interpret the on-chain evidence correctly.
Step-by-Step Walkthrough
Step one: identify the attack addresses. In the Multichain exploit, the first sign of the attack was a series of large, unauthorized withdrawals from the bridge contracts on Fantom. By examining the transaction history of the Multichain router contracts using Ftmscan, analysts identified the receiving addresses that accumulated the stolen assets. These addresses became the primary tracking targets. Step two: catalog the stolen assets. The attacker drained a variety of tokens including USDC, DAI, WETH, and WBTC from the Fantom bridge pool. Each token transfer generates a Transfer event log on-chain, which can be queried and aggregated to determine the total value stolen. Step three: monitor subsequent movements. The attacker began swapping stolen stablecoins and wrapped assets through decentralized exchanges on Fantom and other chains. By tracing each swap transaction, analysts could follow the funds as they were converted into different tokens. Step four: track cross-chain movements. The attacker used additional bridge protocols to move some of the stolen funds to other blockchains, complicating the tracing effort. This is where tools like Chainalysis KYT and TRM Labs become valuable, as they maintain heuristic models for tracking funds across chain hops. Step five: identify endpoints. The ultimate destinations of stolen funds typically fall into one of three categories: centralized exchanges where the attacker attempts to cash out, decentralized exchanges where the funds are swapped for privacy coins or stablecoins, or mixing services like Tornado Cash that attempt to sever the transaction trail.
Troubleshooting
On-chain forensics is rarely straightforward. Attackers employ countermeasures designed to frustrate tracking efforts. Chain hopping, where funds are moved rapidly through multiple bridge protocols across several blockchains, creates a complex web of transactions that is difficult to untangle manually. The Multichain attacker was observed moving funds through multiple chains, and the BlockSec team noted that the exploiter burned 1.2 million ICE tokens worth approximately $1.8 million from a specific address, a behavior that did not fit the standard theft-for-profit pattern and complicated the analysis. Another common challenge is the use of flash loan-powered transactions that create intricate transaction chains with multiple hops executed in a single block. When stolen funds reach privacy-focused tools or cross into blockchains with limited explorer support, the trail can go cold entirely. In these cases, investigators rely on behavioral analysis and timing correlations to make probabilistic connections.
Mastering the Skill
Becoming proficient in on-chain forensics requires consistent practice and a deep understanding of blockchain mechanics. Start by analyzing historical exploits using publicly available data. The Multichain hack, with its multiple chains and complex fund movements, is an excellent training case. Build custom dashboards on Dune Analytics or Flipside Crypto to monitor bridge contracts and set up alerts for unusual withdrawal patterns. Study the methodologies published by blockchain security firms like Chainalysis, TRM Labs, and Elliptic, which regularly release reports on major exploits. The emergence of AI-powered analytics platforms like Arkham Intelligence, which launched its ARKM token and on-chain intelligence marketplace in July 2023, represents the next evolution in forensic capabilities. These platforms use machine learning to automate pattern recognition across billions of transactions, capabilities that were previously available only to well-funded security firms. As the tools democratize, the skill that differentiates analysts will be the ability to combine automated intelligence with human judgment about which leads to pursue and how to interpret ambiguous evidence.
Disclaimer: This article is for informational purposes only and does not constitute financial or investment advice. Always conduct your own research before making any financial decisions.
chain hops through mixing services into CEXes is the standard laundering playbook. the interesting part is how fast the fantom-side moves happened
the fantom-side moves happened in under 45 minutes. thats faster than most incident response teams can even get paged
45 minutes from exploit to CEX deposit on fantom. the attacker had the laundering route preplanned. this wasnt opportunistic
45 minutes is the key stat. most incident response teams take longer to join the call. preplanned laundering routes are why bridges keep getting hit
45 minutes from exploit to CEX deposit means the mixer route was tested beforehand. these are professional operations not some solo hacker winging it
the chain hopping through fantom to CEX in under an hour means the attacker had withdrawal limits and KYC bypass ready. inside job vibes honestly
would love a follow-up on which forensic tools were used. the article mentions techniques but not specific platforms like TRM or Elliptic
TRM and Elliptic are mentioned in the full writeup on Rekt News. this article is more of a summary tbh
the real-time tracing across multiple chains is impressive work by the researchers. most analysis happens weeks after the fact
$130M across three chains and most of it is still gone. bridge security remains an unsolved problem
Gerhard M. $130M across 3 chains and most bridge exploits follow the same pattern. the forensics get better but the bridges dont
multichain bridge was audited and still got drained for 130M. audits are necessary but not sufficient. the real problem is bridges creating massive honeypots by design
audits catch maybe 30% of bugs and bridges keep getting drained anyway. the bridge model itself is broken