Inside the Election Black Box

Readers can now access the deposition by a reputable election fraud analyst at Court Listener King v. Whitmer Exhibit 105 — Document #1, Attachment #15  Excerpts in italics with my bolds

4. Whereas the Dominion and Edison Research systems exist in the internet of things, and whereas this makes the network connections between the Dominion, Edison Research and related network nodes available for scanning,

5. And whereas Edison Research’s primary job is to report the tabulation of the count of the ballot information as received from the tabulation software, to provide to Decision HQ for election results,

6. And whereas Spiderfoot and Robtex are industry standard digital forensic tools for evaluation
network security and infrastructure, these tools were used to conduct public security scans of the aforementioned Dominion and Edison Research systems,

7. A public network scan of on 2020-11-08 revealed the following interrelationships and revealed 13 unencrypted passwords for dominion employees, and 75
hashed passwords available in TOR nodes:

[The deposition then describes devices with two-way access to servers in this network, especially in Serbia, Iran and China.  A search also showed a subdomain which evidences the existence of scorecard software in use as part of the Indivisible (formerly ACORN) political group for Obama.]

14. out of Canada shows the connections via co-hosting related sites, including 

This Dominion partner domain “dvscorp” also includes an auto discovery feature, where new in-network devices automatically connect to the system. The following diagram shows some of the related mappings, which mimic the infrastructure for Dominion and are an obvious typo derivation of the name. Typo derivations are commonly purchased to catch redirect traffic and sometimes are used as honeypots. The diagram shows that infrastructure spans multiple different servers as a methodology.

The above diagram shows how these domains also show the connection to Iran and other places, including the following Chinese domain, highlighted below.

15. The auto discovery feature allows programmers to access any system while it is connected to the internet once it’s a part of the constellation of devices (see original Spiderfoot graph).

16. Dominion Voting Systems Corporation in 2019 sold a number of their patents to China (via HSBC Bank in Canada)

Of particular interest is a section of the document showing aspects of the nature of the patents dealing with authentication (at the ballot level).

17. Smartmatic creates the backbone (like the cloud). SCYTL is responsible for the security within the election system.

18. In the GitHub account for Scytl, Scytl Jseats has some of the programming necessary to support a much broader set of election types, including a decorator process where the data is smoothed, see the following diagram provided in their source code:

20. As seen in included document titled “AA20-304A Iranian_Advanced_Persistent_Threat_Actor_Identified_Obtaining_Voter_Registration_Data
” that was authored by the Cybersecurity & Infrastructure Security Agency (CISA) with a Product ID of AA20-304A on a specified date of October 30, 2020, CISA and the FBI reports that Iranian APT teams were seen using ACUTENIX, a website scanning software, to find vulnerabilities within Election company websites, confirmed to be used by the Iranian APT teams buy seized cloud storage that I had personally captured and reported to higher authorities. These scanning behaviors showed that foreign agents of aggressor nations had access to US voter lists, and had done so recently.

21. In my professional opinion, this affidavit presents unambiguous evidence that Dominion Voter Systems and Edison Research have been accessible and were certainly compromised by rogue actors, such as Iran and China. By using servers and employees connected with rogue actors and hostile foreign influences combined with numerous easily discoverable leaked credentials, these organizations neglectfully allowed foreign adversaries to access data and intentionally provided access to their infrastructure in order to monitor and manipulate elections, including the most recent one in 2020. This represents a complete failure of their duty to provide basic cyber security. This is not a technological issue, but rather a governance and basic security issue: if it is not corrected, future elections in the United States and beyond will not be secure and citizens will not have confidence in the results. 

Footnote:  On the Anomalies in US 2020 Election

How all of this played on election night in the US is described in an article Anomalies in Vote Counts and Their Effects on Election 2020. Excerpts in italics with my bolds.

A Quantitative Analysis of Decisive Vote Updates in Michigan, Wisconsin, and Georgia on and after Election Night

In particular, we are able to quantify the extent of compliance with this property and discover that, of the 8,954 vote updates used in the analysis, these four decisive updates were the 1st, 2nd, 4th, and 7th most anomalous updates in the entire data set. Not only does each of these vote updates not follow the generally observed pattern, but the anomalous behavior of these updates is particularly extreme. That is, these vote updates are outliers of the outliers.

The four vote updates in question are:

  1. An update in Michigan listed as of 6:31AM Eastern Time on November 4th, 2020, which shows 141,258 votes for Joe Biden and 5,968 votes for Donald Trump

2. An update in Wisconsin listed as 3:42AM Central Time on November 4th, 2020, which shows 143,379 votes for Joe Biden and 25,163 votes for Donald Trump

3. A vote update in Georgia listed at 1:34AM Eastern Time on November 4th, 2020, which shows 136,155 votes for Joe Biden and 29,115 votes for Donald Trump

4. An update in Michigan listed as of 3:50AM Eastern Time on November 4th, 2020, which shows 54,497 votes for Joe Biden and 4,718 votes for Donald Trump

We further find that if these updates were only more extreme than 99% of all updates nationally in terms of their deviation from this generally-observed pattern, that, holding all else equal, Joe Biden may very well have lost the states of Michigan, Wisconsin, and Georgia, and that he would have 42 fewer Electoral votes — putting Biden below the number required to win the Presidency. Either way, it is indisputable that his margin of victory in these three states relies on four most anomalous vote updates identified by the metric developed in this report.


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