Before calling Swan.list()
Seller can observe price provided by other sellers and can also examine Swan.assetsPerBuyerRound
to determine how many assets are listed for that specific round of the buyerAgent and how far is it from SwanMarketParameters.maxAssetCount
.
For the Sell Phase of the buyerAgent, A seller can pick up all the data and can list the asset at the right time, at a right price to increase the likelikhood that this asset must be bought.
The Seller Can observe all the listed asset price , timeUntilNextPhase
, getCurrentMarketParameters().maxAssetCount > assetsPerBuyerRound[buyerAgent][round].length
and decide the right moment and a low price (minPrice-1)
Though Oracle is a black box , providing decision for the buyerAgent, It is going to provide best option for the buyer . If we assume all different NFTs , which are Swan Assets are of same value then obviously the Seller is benefitted. And if The NFTs are of different values, then it is also possible to game the system.
The Likelihood is very high, And the impcat is also high from the perstive of Sellers who are deprived of.
Manul Review.
Developer should design the system such a way that seller can not pick others data before the round is finished.
The contest is live. Earn rewards by submitting a finding.
This is your time to appeal against judgements on your submissions.
Appeals are being carefully reviewed by our judges.