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Detail Analysis

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Date:

Status:

Incident Count:

May 26, 2019

Verified

1

Contributor:

zerofriction.io

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KYC By:

KYC:

None

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Audit By:

Audits:

None

Loss Amount:

1,350,000

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Recovered Amount:

-

Currency:

Dollars, BCH

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Key Indicators

Platform:

Type:

Category:

Method:

Data Sources:

Bitcoin Cash

Network

Chain

51% Attack

Extended Method:

Chain re-organization, doublespending

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BCH May Have Sustained $1.3 Million+ Double Spend: BitMex Research - New report says after its hard fork on May 15, bitcoin cash experienced a 2-block reorganization possibly resulting in a 3,392 BCH (over $1.35 million) double spend. Following its hard fork on May 15, bitcoin cash (BCH) appears to have experienced a two-block chain reorganization resulting in a 3,392 BCH (about $1.35 million at press time) double spend. The claim was made in a report released by the research arm of cryptocurrency derivatives exchange BitMex on May 24. Per the report, the recent BCH hard fork experienced three interrelated issues. Firstly, an apparent bug evidently exploited by an attacker right after the hard fork. The attacker was able to broadcast transactions which met the mempool validity conditions but failed the consensus checks. Miners attempting to produce blocks with said transactions were not able to, instead producing empty blocks. The empty blocks reportedly resulted in concern among miners who may have tried to mine on the original non-hardfork chain, causing a consensus chainsplit. The third interrelated problem was that the consensus chainsplit reportedly prevented a system meant to recover funds accidentally sent to SegWit addresses from functioning. According to BitMex Research, “[t]his failure may have resulted in a deliberate and coordinated 2 block chain re-organisation.

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Under no circumstances, shall Zero Friction LLC be liable for any loss of profit or funds, any regulatory or governmental penalties, any legal costs, or any other commercial and non-commercial damages, including but not limited to special, incidental, consequential, or other damages from any or all usage of the dataset or information derived from our database.