Top Tweets for #AlliedSecOpsGroup
“It was very clearly [sic] that races were flipped.”
The #AlliedSecOpsGroup analyst who led the #ForensicAudit of #DominionVotingSystems in #Michigan said the information state officials pushed to redact shows that the outcomes of races were changed. https://t.co/fYVwS1fTkI
Opinião 💭 por Roger L. Simon
Os legisladores do Michigan erraram.
#AlliedSecOpsGroup e seu co-fundador não estava na audiência, nem, surpreendentemente, qualquer #InformationTechnology profissionais para fazer perguntas sobre #DominionVotingSystems CEO.
Opinion💭by Roger L. Simon
Michigan legislators blew it.
#AlliedSecOpsGroup and its co-founder was not at the hearing, nor were, astonishingly, any #InformationTechnology professionals at all to ask questions of the #DominionVotingSystems CEO. https://t.co/gkAf1Fo88m
Opinion💭by Roger L. Simon
Michigan legislators blew it.
#AlliedSecOpsGroup and its co-founder was not at the hearing, nor were, astonishingly, any #InformationTechnology professionals at all to ask questions of the #DominionVotingSystems CEO. https://t.co/gkAf1Fo88m
#DominionVotingSystems'máquinas são projetadas para criar #VoterFraud e influência #Elections , de acordo com a empresa de dados #AlliedSecOpsGroup .
Deles #ForensicAudit investigou 22 Dominion #VotingMachines dentro #AntrimCounty .
#DominionVotingSystems' machines are designed to create #VoterFraud and influence #Elections, according to data firm #AlliedSecOpsGroup.
Their #ForensicAudit investigated 22 Dominion #VotingMachines in #AntrimCounty. https://t.co/4xN4akXMUo
#DominionVotingSystems' machines are designed to create #VoterFraud and influence #Elections, according to data firm #AlliedSecOpsGroup.
Their #ForensicAudit investigated 22 Dominion #VotingMachines in #AntrimCounty. https://t.co/4xN4akXMUo
Opinion💭by Gary Miliefsky
#DominionVotingSystems proprietary algorithms were used in 28 states this year.
Based on #AlliedSecOpsGroup's #ForensicAudit, these algorithms produce such high error rates, that it can only mean one thing—#ElectionFraud. https://t.co/4YlExF1JG3
Following #AlliedSecOpsGroup's #ForensicAudit report of #VotingMachines in #Michigan, the #AmistadProject said it will file a lawsuit in swing states to call on judges to “preserve evidence” of alleged #VoterFraud. https://t.co/0dR8KTSK4H
#AlliedSecOpsGroup, which carried out a #ForensicAudit of #VotingMachines in #Michigan, claimed that more than 1,400 votes changed when they evaluated a #Dominion ImageCast Precinct machine for possible hardware problems in a small town. https://t.co/YxV8kMSizD
@Human85894078 @crt39437 @realDonaldTrump Besides hundreds of the affidavits, eye witnesses, video and audio and electronic evidence....According to MI Forensics Audit of 16 Dominion Machines, error rate was 68.5% #AlliedSecOpsGroup
MI Dems have since ordered all 83 Counties to DELETE all election and software data
@lornebrooker The FEC's allowable Error Rate is 1 in 250k, or, 0.0008%
According to MI Forensics Audit of 16 Dominion Machines, error rate was 68.5% #AlliedSecOpsGroup
MI Dems have since ordered all 83 Counties to DELETE all election and software data from Dominion machines.
FEC联邦选举委员会的允许错误率是25万分之一,即0.0008%
根据MI对16台Dominion机器进行的取证审计,错误率为68.5%#AlliedSecOpsGroup
此后,MI Dems已下令所有83个县从Dominion机器中删除所有选举和软件数据。
The FEC's allowable Error Rate is 1 in 250k, or, 0.0008%
According to MI Forensics Audit of 16 Dominion Machines, error rate was 68.5% #AlliedSecOpsGroup
MI Dems have since ordered all 83 Counties to DELETE all election and software data from Dominion machines.
@OANN
🚬HOLY SMOKES 🚬
From @OANN
FEC's allowable Error Rate is 1 in 250k or 0.0008%
MI Forensics Audit of 16 Dominion Machines, error rate was 68.5% 😳#AlliedSecOpsGroup
MI Dems have since ordered all 83 Counties to DELETE all election & software data from Dominion machines
The FEC's allowable Error Rate is 1 in 250k, or, 0.0008%
According to MI Forensics Audit of 16 Dominion Machines, error rate was 68.5% #AlliedSecOpsGroup
MI Dems have since ordered all 83 Counties to DELETE all election and software data from Dominion machines.
@OANN
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