A class action lawsuit with a claim for $5 million has been filed against Bitmain in California. It claims the Chinese ASIC producer eked out hashing power from every machine sold. According to the suit, late-model ASICs were designed to mine toward Bitmain-related pools during the initiation process.
The plaintiff, Gor Gevorkian, claims that previously, ASIC had a setup mechanism with a low-energy mode that did not start mining. However, as Bitmain’s influence grew, the initiation process was changed, and for a while, the machine’s hashrate could be used.
“In the past, Bitmain ASIC devices could be configured and initialized in low-power mode that did not mine cryptocurrency for Bitmain. However, after Bitmain established itself [as] cryptocurrency miners in the last several years, Defendant redesigned its ASIC devices to mine cryptocurrency for the benefit of itself rather than its customers who purchase the Products,” reads the claim against Bitmain.
The lawsuit was filed after an extremely successful year for Bitmain, where sales of ASIC kept increasing, on growing interest in mining. Both mining farms and in-home miners with several machines may have been hurt from the hidden mining, hence the $5 million price tag for the lawsuit.
The lawsuit is yet another challenge to Bitmain’s dominance, and it arrives at a time when miners are actually abandoning the Bitcoin network. Bitmain has been seen as a powerful influence not only on the mining of Bitcoin, but also for Bitcoin Cash, which it helped sway in the recent hash wars.
The gains made from hidden mining are difficult to estimate, especially given the varying potential rewards for running an ASIC, as well as the market price, which fluctuated significantly.
After the slide in Bitcoin prices, the profitability of Antminer S9, the latest model so far, has gone underwater. Running an S9 mining rig and paying its electricity costs would actually set the miner back $813 for a year. But during boom times, a miner could bring in more than $500 per month per machine, based on rough estimates.