DYORSWAP Blames Fake GIWA Chain for 766 ETH Loss

DYORSWAP said the incident was caused by a fraudulent network impersonating GIWA Chain 9134, rather than a vulnerability in the DYOR smart contracts. The OP Stack-style network and bridge infrastructure were deployed on 27 September 2026. Around 1,335 addresses deposited approximately 767.65 ETH, while about 766.25 ETH was later withdrawn through the bridge. DYORSWAP recorded 1,479 on-chain operations, including 1,148 successful transactions involving 298 wallets and 104 liquidity pools. The team has distributed more than 200 ETH from its own funds to compensate affected users. DYORSWAP is investigating the bridge deployers, funding sources, batch-processing infrastructure and movement of the drained funds. It is also using on-chain data to distinguish attackers from legitimate victims. For traders, the DYORSWAP incident highlights fake-chain, cross-chain bridge and DeFi counterparty risks. Compensation may limit immediate selling pressure, but confidence in DYOR-linked services could remain under pressure.
Neutral
The incident is negative for DYOR-linked services because a fake-chain operation caused substantial ETH losses and raises concerns about bridge security, user protection and counterparty risk. In the short term, affected users could sell DYOR-linked assets or withdraw liquidity, creating volatility and temporary downward pressure. However, the losses were attributed to an impersonating network rather than a DYOR smart-contract exploit, which limits the direct technical damage to the protocol. Compensation of more than 200 ETH may also reduce panic selling and liquidity withdrawals. The drained ETH amount is significant for the affected users but unlikely to materially move the broader ETH market. In the longer term, the impact will depend on the investigation, fund recovery, transparency and whether users continue to trust DYORSWAP. These offsetting factors support a neutral classification for the mentioned cryptocurrency market, despite elevated project-specific risks.