• Ethereum Foundation announced an increase in the reward for bug bounty from $250,000 to $500,000 ahead of the Shapella upgrade.
• Bug bounty programs offer rewards to individuals or groups who identify security flaws and vulnerabilities in an organization’s systems.
• The OWASP risk rating model is used to calculate the severity of the vulnerability based on impact and likelihood.
Ethereum Shapella Upgrade
The much-anticipated Shapella upgrade is just around the corner and with it comes a bug bounty reward that has been doubled by the Ethereum Foundation. The maximum reward for identifying any vulnerabilities in this upgrade has been increased from $250,000 to $500,000.
Bug Bounty Program
The bug bounty program provides financial compensation to those who can find security flaws or vulnerabilities in an organization’s system. In Ethereum’s case, the rewards depend on severity which can be calculated using the OWASP risk rating model based on factors such as impact and likelihood. The program covers soundness of protocols (blockchain consensus model, wire and peer-to-peer protocols, proof of stake etc.) as well as protocol/implementation security issues related to Shanghai/Capella upgrades.
Increased Reward
This isn’t the first time that Ethereum Foundation has increased its bug bounty payouts – they quadrupled ahead of ETH’s transition to proof-of-stake for all “Merge related bounties for vulnerabilities” testing network stability prior to launch. This most recent reward increase was mentioned during the 105th All Core Developers Consensus call as part of last minute testing efforts prior to deployment on mainnet.
Shapella Upgrade Effects
With Shapella upgrade rolling out soon, staked ETH withdrawals will be enabled for the first time ever on Ethereum blockchain network once it goes live on mainnet.
Conclusion
Ethereum Foundation’s bug bounty program encourages outside developers and researchers to help identify potential security risks before they become big problems down the line – offering huge rewards as motivation for identifying them quickly so they can be fixed promptly too!