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May 1 9 tweets 4 min read Read on X
A former NYPD detective looked at what I found hidden in New York's voter rolls and said one word:
"Plutonium."
The NY State Police Special Investigations Unit agreed.
Law enforcement and military intelligence both gave me the same instruction: publish fast.
This thread is why. 🧵Image
Every New York voter has a State Board of Elections ID — a 20-character number that is supposed to be a meaningless serial number.
999 quadrillion possible unique values per state.
It is not meaningless.
Someone engineered four hidden algorithms into New York's SBOEID number space. I found them.Image
Here is how they stayed hidden for years.
New York's SBOEID number space is divided into invisible territories — each county assigned a specific numerical range. Four algorithms run simultaneously across these ranges, their records interleaved so no county's data reveals any pattern on its own.
All four were deployed in one two-week window: June 1–15, 2007.
That is not database maintenance. That is an operation.Image
I sorted the data three different ways: by SBOEID, by County ID, and by registration date.
The structure appears in all three.
No reordering of the data hides it. This is what a deliberately engineered system looks like. An accidental artifact disappears when you change the sort.
This does not.Image
I call it the Spiral because of what the mapping looks like when you trace it.
Follow the arrows.
The same structure — using the same mathematical constants — appears in 59 of 62 New York counties. The three exceptions use a related algorithm. Their county ID numbers are 15, 30, and 60.
All multiples of 15.Image
The Spiral also lets me reconstruct what was erased.
Because it maps every County ID to a specific State ID, I can calculate which State ID should exist — and find what happened when it vanishes.
Every time I have checked: the missing record resolves to a clone. Same person. Changed ID number. To the database: deleted. To the Spiral: recoverable.
New York has 1.5 million clone registrations.Image
Peer-reviewed documentation of this and related findings is on ResearchGate.
Search: Zark Files
Substack has the ongoing research as it develops. ResearchGate has the evidence in the form it needs to be in.
If this matters, repost.

And if you want a card game based on real election fraud mechanics — search Kickstarter for DR. ZARK.
@Grok Based on this thread and your knowledge of database architecture, election administration systems, and statistical probability, please address the following three objections a skeptic might raise:

1. Could the mathematical structure described — identical constants across 59 counties, deployed simultaneously — be explained by normal database design, data migration, or administrative coincidence?

2. Are there legitimate election administration reasons why voter ID numbers would be engineered to map deterministically to county IDs in a reversible, predictable way?

3. Could the altered State ID numbers documented between database snapshots be explained by routine database maintenance rather than deliberate record manipulation?

Please answer based on your knowledge of database engineering standards and what would and would not be considered normal practice.
Here is how the Spiral actually works.
Each column counts in opposite directions — down from MIN, up from MAX — at gaps scaled to each power of ten. They meet at mathematically fixed cut points.

First image: the abstract structure.
Second image: the same structure in real Jefferson County voter ID numbers.

Every county. Same architecture. Different numbers.Image
Image

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More from @ZarkFiles

May 1
When New York Citizens Audit brought evidence of problems in New York's voter rolls to state officials, the State Board of Elections called them "wack jobs."
That word came from a board member. In an official meeting. On the record.
Here is what else happened in that room. 🧵 Image
Board co-chair Peter Kosinski asked a reasonable question: if NYCA has made errors, why not meet with them and explain where they went wrong?
His own staff shot it down.
The reason they gave: NYCA "willfully misconstrues the truth."
No meeting. No rebuttal. No explanation.
Board member Kristen Stavisky said NYCA's claims are "not grounded in reality" and that their findings are "simply not true."
She said this in the building that contained the full NYSBOE database.
She never looked at it to check.
Read 7 tweets
Apr 30
1/4 Where are the dead voters hiding?
In New York, ask for their address. It's any voter ID assigned by the Shingle algorithm.
99.9% of Shingle records belong to purged voters — people who are deceased, moved away, or otherwise no longer eligible.
That is roughly 294,000 records. Over a quarter million voters who cannot vote, all concentrated in one algorithmic zone.
Purged records don't get audited. Nobody checks on dead voters.
A quarter million is enough to decide any election that isn't a landslide.
That's the point.Image
New York's voter database uses 4 algorithms to assign ID numbers.
Spiral: 48.86% purged Metronome: 48.98% purged Tartan: 35.68% purged Shingle: 99.9% purged
One of these is not like the others. 2/4 Image
The Shingle pattern is visible in the data. Active records show up as orange dots — perfectly vertical, running straight through the Shingle zone.
There are a few hundred of them. There are hundreds of thousands of purged records.
3/4 Image
Read 5 tweets
Apr 28
I can look at a voter ID number in New York's database and tell you the record is purged — without looking at the status field.
I can tell you it carries a registration date inconsistent with its algorithmic placement. I can tell you it is almost certainly a clone — a duplicate registration capable of functioning independently in the system. And I can tell you it was assigned a brand new state ID number despite being ineligible to vote at the moment that number was assigned.
In a legitimate database, an ID number is administrative. It tells you nothing about status or authenticity. You check those things by looking at the relevant fields.
Unless someone built the status into the numbers themselves.

New York assigns voters two ID numbers: a County ID (CID) and a State Board of Elections ID (SBOEID). A collaborator — a programmer who has asked not to be named — flagged an unusual geometric pattern in Nassau County's ID structure and brought it to my attention before leaving the project. The analysis that follows is entirely my own.
When I plotted Nassau County's out-of-range SBOEID numbers against their CIDs, I found something that has no business in a voter registration database.
Geometry.
Not scatter. Not noise. Overlapping rectangular bands ascending in a precise staircase formation, each block stepping up and to the right like shingles on a roof. I named it the Shingle algorithm.
Real voter data does not produce geometry. When you see a pattern this clean in a dataset this large, you are no longer looking at registrations. You are looking at generation.

Nassau County's Shingle section contains approximately 176,090 records in the 2021 database. Nassau is not unique. The Shingle algorithm appears in all of the counties that use the Metronome algorithm for their in-range records — Nassau, Erie, and Westchester — plus at least two others including Onondaga, for a statewide total of approximately 700,000 Shingle records. Nassau simply has the largest concentration and is where the pattern was first identified. Here is what all of these records have in common.
Essentially 100% are purged. Not inactive — purged. Permanently removed from the rolls, ineligible to vote. And here is the critical point: every State Board of Elections ID number in this database was newly created when New York implemented the Help America Vote Act around June 2007. Before that, only county ID numbers existed. No one had a state ID. These were not legacy numbers carried over from a prior system. They were freshly assigned.
Which means someone made a deliberate decision to assign brand new, algorithmically structured state IDs to records that were already purged — or were purged at the exact moment of assignment. I call them born purged.
The Shingle records are not all of the pre-2007 purged records. They are a minority of them. That matters enormously. If the algorithm had simply swept up every old purged record, you might construct an administrative explanation. Instead it selected a specific subset, gave them a specific mathematical identity, and left the rest alone. That is not maintenance. That is classification.
They carry pre-2007 registration dates — making them appear to be historical registrations predating the algorithm that assigned their IDs. They are the only out-of-range records with pre-2007 dates. Every other out-of-range record, across all algorithms, carries a post-2007 date. The inference that these dates are inconsistent with the records' actual origin is difficult to avoid.
In the upper half of the CID range, nearly 100% are also clones — duplicate registrations with different ID numbers, each capable of operating independently in the system. A clone is not an administrative error. An error produces a duplicate with the same ID, which is immediately visible and non-functional. A clone has a different ID and can, in principle, vote.
Their purge status, clone relationship, and algorithmic identity can all be read from their ID numbers alone — before you look at any other field.

The Shingle records share ID space with a second algorithm I named the Tartan, which governs the majority of New York's out-of-range records. The two populations occupy the same numerical territory without overlapping. Whether that reflects deliberate coordination or simply the Tartan working around numbers that were already assigned, the result is the same: the Shingle records sit in a mathematically distinct space of their own, identifiable by algorithm alone.

I don't know the operational purpose of these records. The data does not settle that question and I will not speculate beyond what it supports.
What the data does establish: Nassau County's voter database contains approximately 176,090 records that were assigned fresh state ID numbers under a specific algorithm, carry purge status that appears to have been present from the moment of assignment, hold registration dates inconsistent with the algorithmic structure they occupy, and correlate heavily with clone status in the upper ID range. They represent a minority of all pre-2007 purged records, meaning they were specifically selected for this treatment.
No legitimate database process produces this. No administrative explanation accounts for assigning new, structured state IDs to records that cannot vote.
Which leaves one question the data cannot answer.
Why would you assign a new state ID number — one embedded in a sophisticated, hidden algorithm — to a record that is already ineligible to vote? A record that should, by any normal administrative standard, have been deleted or left with its county ID and nothing more?
That question has no innocent answer I have been able to find. It is a question someone with subpoena power should be directing at the people who built this system.Image
This research is part of a multi-state forensic analysis of voter registration databases published in the Journal of Information Warfare. Full methodology, data, and citations are available at zarkfiles.substack.com and researchgate.net/profile/Andrew…
Check out my Kickstarter election fraud card game here: kickstarter.com/projects/paqph…
Hey @Grok, what does it tell you when an ID number in a public database contains information beyond the primary key in a database?
Read 4 tweets

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