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Detail Analysis

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Date:

Status:

Count:

Contributor:

February 5, 2021

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Verified

1

zerofriction.io

Loss Amount:

-

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Recovered Amount:

-

Currency:

Dollars

KYC By:

Audit By:

None

None

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Website:

Twitter:

No data

Discord:

No data

Telegram:

No data

Medium:

No data

Github:

No data

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Key Indicators

Platform:

Type:

Category:

Method:

Insurance

Exchange

Assets

Contract Vulnerabilities

Extended Method:

Contract vulnerabilities

Data Sources:

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ArmorFi, a decentralized finance (DeFi) insurance brokerage, is paying a hefty bug bounty of $1.5 million in tokens to a white-hat hacker who found a "critical bug" that could have seen all the firm’s underwriting funds drained. Submitted by Alexander Schlindwein via bug bounty platform Immunefi, the submission was awarded the largest bounty ever paid out in the DeFi community, Immunefi said. Schlindwein submitted the bug just a day after ArmorFi offered 1 million "mostly vested" Armor tokens (currently worth nearly $1.5 million) to anyone who could spot a critical exploit in its smart contracts. As an amusing addition, ArmorFi's CTO Robert Forster had offered to get a tattoo of the name or handle of any hacker who found a critical bug. That's now an option for Schlindwein. “It’s a real privilege to have made possible the largest ever bug bounty payout. We’re going to keep rewarding the developers who make DeFi safe, and this is just the beginning,” said Immunefi CEO Mitchell Loureiro.

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DISCLAIMER: While Zero Friction LLC has used the best efforts in aggregating and maintaining this database, Zero Friction LLC makes no representations or warranties with respect to the accuracy or completeness, and specifically disclaim any implied warranties of merchantability or fitness for any particular purpose. 

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.