The Meme as a Weapon Under Adversary Amplification September 6, 2026
Posted by Chris Mark in Uncategorized.Tags: adversary amplification, cognitive exploitation, cognitive warfare, confirmation bias, disinformation, engagement economy, information operations, inoculation theory, meme warfare
add a comment
In Adversary Amplification, I described the mechanism by which open societies turn their own citizens into a zero-cost transmission layer for hostile narratives: an Agent seeds a story, the Engagement Economy amplifies it, sincere Nodes carry it forward, and the Impact accumulates as institutional distrust, cognitive exhaustion, and policy paralysis. That paper examined the architecture at the strategic level. The Meme as a Weapon, Part III of the Frictionless Battlefield Series, examines the delivery unit. The meme is not incidental to the mechanism. It is its most efficient tool, because it is cheap to produce, fast to share, emotionally loaded, and engineered to bypass deliberate thought entirely. The Engagement Economy did not create human cognitive vulnerabilities. It industrialized their exploitation.
The paper identifies three exploitation vectors, each grounded in documented cognitive research and illustrated with real case examples. The first is false correlation presented as evidence, which exploits statistical illiteracy by pairing two facts in a single image so that the viewer infers a causal link the image never actually claims. The second is the emotional identity trigger disguised as commerce or civic sentiment, which uses patriotic or tribal appeals to make sharing feel like an act of loyalty rather than a judgment about truth. The third is domain complexity exploitation, which targets subjects like energy infrastructure, telecommunications, or artificial intelligence where the audience lacks the baseline knowledge to evaluate the claim and so defaults to whichever version arrived first and felt right. Underneath all three sit the same vulnerabilities: heuristic processing, the truthiness effect, and confirmation bias. The 2026 anti-data-center campaign, including the August disclosure of a suspected Chinese inauthentic-account network distributing AI-generated cartoons on the subject, shows all three vectors operating at once.
The paper also examines a problem that makes correction structurally harder than propagation. Adverse-report-driven moderation on major platforms tends to suppress the factual reply while leaving the original meme in circulation, because the correction draws the complaints and the meme draws the engagement. The conclusion is that individual fact-checking cannot reach the Impact of meme-based propaganda, which operates below the level of any single claim. The only durable response is pre-emptive cognitive inoculation, and the paper closes with a practical five-question framework that individuals, platform operators, security practitioners, and educators can apply before a compelling image gets shared. The full paper is available on Zenodo at DOI 10.5281/zenodo.22539459.
Adversary Amplification in the United States September 6, 2026
Posted by Chris Mark in Uncategorized.add a comment
In August, X disclosed a network of roughly 200,000 suspected Chinese inauthentic accounts. About 200 of them were posting AI-generated cartoons about American data centers. By then, 70 percent of American voters opposed a data center in their community, New York had a moratorium, and Texas had paused grid connections for every project in the queue. Two hundred accounts did not do that. Tens of millions of Americans did, and almost none of them knew they were part of an operation.
That gap is the subject of the two papers below. Our vocabulary for influence operations describes what adversaries do. Nothing names what happens on our side: the mechanism by which sincere people become the delivery infrastructure for narratives they never knew were seeded. I call it Adversary Amplification. An Agent with intent, foreign or domestic, seeds a narrative onto a grievance that already exists. The commercial platform Ecosystem, built to sell ads, amplifies it because outrage generates engagement. Sincere Nodes carry it forward on their own conviction and credibility. The Impact is never the specific belief. It is distrust, exhaustion, and paralysis, a population that cannot resolve consequential decisions. Once seeded, the machine runs itself and the Agent walks away. It does not even need a foreign hand. The USS Maine, the Iraq WMD case, and the SPLC’s captured hate group designations all ran on the same mechanism. This is the battlefield Qiao and Wang described in Unrestricted Warfare. Their doctrine names the target. Adversary Amplification is how it works.
The companion paper goes one level down to the meme, the compressed image-anchored claim built to be judged in three seconds and shared before the analytical part of your brain shows up. A chart makes a claim feel true even when it proves nothing, agreement feels like evidence, and most people were never taught to ask what else changed at the same time. Fact-checking cannot fix this, because the meme travels without its refutation and organized communities mass-report the correction until it disappears. The durable answer is inoculation: teach the exploitation pattern before people meet the instance, and ask who benefits before you share. You cannot audit everything you see. You can audit what you are about to amplify. A Node that does not share is not infrastructure. The full papers follow.
A Scout Sniper’s Forensic Analysis of the Charlie Kirk Assassination: Terminal Ballistics, Hydro-static Shock, and the Science Behind the Shot July 11, 2026
Posted by Chris Mark in Uncategorized.Tags: Assassination, ballistics, Candace Owens, Charlie Kirk, Charlie Kirk Murder, Chris Mark, security, Shawn Ryan, sniper, TPUSA
6 comments
UPDATE! I have expanded upon this post and turned it into a much more comprehensive whitepaper. You can download here at Zenodo.org! or directly from this site below!
This is a long post but I think it is important. Recently I came across what I can only describe is an offensive AI ‘explanation’ by Candace Owen’ group that attempted to refute that Charlie Kirk was killed by a rifle round. More disturbingly, the ‘video’ is a mocking explanation of ‘conspiracy theorists’ who know what happened. The video was wrong at nearly every turn and was, quite frankly, offensively incorrect. Unfortunately, reading numerous comments on her page, a number of social media members believe and bought into her commentary. I want to refute her and explain with very direct math and science why it is 100% how Charlie Kirk was killed. Who am I to comment on this? I am a former Marine Corps Scout/Sniper, and Urban Sniper with combat time as a Sniper in the USMC. I was also a Force Reconnaissance Marine, and I have not only shot tens of thousands of rounds through rifles and am an avid hunter, but I also write extensively on firearm technology. In fact, I was selected for a DARPA counter sniper project during my time in the military due to my knowledge of ballistics and shooting.
Every time a high-profile shooting makes national news, social media fills with confident proclamations from people who have never fired a weapon in anger, never studied wound ballistics, and whose entire frame of reference comes from action movies and video games. The commentary ranges from the merely ignorant to the dangerously misleading (as in Ms. Owen’s) — and in some cases it is being amplified by public figures with large platforms who should know better. Recently, I was on a popular political commentator’s website and was amazed at how many people are now, suddenly, ballistics experts. Some of their comments were staggeringly ignorant. One person actually justified her very incorrect statement by saying she was the “ex-girlfriend of a hunter.” That is not a ballistics credential.
This post is not political. It is a ballistics education to provide insight into a terrible murder that is being overshadowed by a person’s pursuit of clicks, and money. That being said — for every so-called “ballistics expert” on social media who is doubting that Charlie Kirk was actually killed by that rifle at that distance, you need to read this post and understand a bit about how terminal ballistics actually works.
On September 10, 2025, at 12:23 PM local time, a single shot was fired from the roof of the Losee Center at Utah Valley University in Orem, Utah. The shooter was positioned approximately 142 yards from where Charlie Kirk was speaking. The weapon recovered was a Mauser-type bolt-action hunting rifle chambered in .30-06, loaded with (what appeared to be) Sierra GameKing 180-grain soft point ammunition. For consistency and we will simply say a non-bonded soft point bullet. Kirk was struck in the neck by a single bullet and was pronounced dead at Timpanogos Regional Hospital a short time later.
Within 5 minutes of the shooting my phone was blowing up with people asking what happened. My response: “Watching the impact, he was hit hard by a .30 cal. From an incline, close range. He was smacked so hard it looked like a .30-06”. Then, the hard question. Do you think he will live? My response? “No chance. His brain was dead nearly immediately and that was not a survivable wound. People asked why I thought that? Easy. He showed Decorticate posturing immediately upon being hit. Decorticate posturing is when arms flex inward, hands curl in. Indicates cortical or upper brain stem disruption. This is classic with hydro static shock impacting the brain (to be explained later). Classic high powered rifle shot that impacted the brain or nervous system.
People are claiming the distance is too far, the rifle was not ‘zeroed’ etc. etc. etc.. Many claimed that the wound characteristics don’t add up. That the bullet behavior was inconsistent with the stated circumstances. Every one of those claims reflects a fundamental misunderstanding of projectile physics, atmospheric ballistics, and terminal wound mechanics. This post addresses them directly, with math and science. What I am seeing circulate on social media right now needs to be corrected with facts, not speculation. A hunter is not a ballistics professional nor a professional at shooting humans.
I have radically updated the whitepaper as I received a number of requets from people wanting more information. You can download the whitepaper here or at Zenodo.com
Fighting Misinformation: The Impact of Adversary Amplification in Society June 8, 2026
Posted by Chris Mark in cybersecurity, Industry News, Politics, privacy, security, Uncategorized, War.add a comment
This is a brief 10 minute discussion on Adversary Amplification. We all hear it every day. The outrage over AI DataCenters. The Lone Star Tick, name it. The people spreading this are not malicious, they are simply passionately misinformed and doing the work of a centralized agent. That could be China, Russia, or a competitor. With the advances in AI and explosion of Social Media, propagating and advancing these fears have become easy. Today’s hearings on the SPLC are a perfect example of Adversary Amplification. To think the SPLC is supporting NeoNazi groups, the KKK and other simply to hurt Republicans! Here is a link to the actual paper.
Statistical Anomalies in LA Mayoral Election: A Deeper Analysis June 7, 2026
Posted by Chris Mark in Industry News, Laws and Leglslation, News, Politics, Uncategorized.Tags: music, News, poetry, politics, writing
add a comment
DISCLAIMER: This article presents a statistical analysis of publicly available election data. It does not allege fraud, illegal conduct, or wrongdoing by any candidate, election official, or government entity. The statistical anomalies documented below demand transparent explanation. That is the appropriate standard in a functioning democracy. Nothing more is claimed here.
Introduction
Elections in the United States are decided by votes. The integrity of those votes depends not only on the honesty of those casting them but on the transparency and consistency of how they are counted. When the statistical profile of mail-in ballot counting diverges from election day results by a margin that falls outside any reasonable probability model, the public interest demands a clear and documented explanation.
This article presents a statistical analysis of Spencer Pratt’s performance in the 2026 Los Angeles mayoral primary election. The analysis compares his election day vote share to his performance in subsequently counted mail-in ballot batches. The divergence between these two data sets is not a matter of opinion or political interpretation. It is a mathematical fact that warrants examination.
This is not an endorsement of any candidate. It is an application of basic statistical principles to publicly available election data.
Background: The Race
The 2026 Los Angeles mayoral primary featured fourteen candidates, with incumbent Mayor Karen Bass seeking a second term against a field that included former reality television personality Spencer Pratt, a registered Republican whose Palisades home was destroyed in the devastating 2025 wildfires, and Los Angeles City Councilwoman Nithya Raman, a Democratic Socialists of America member challenging Bass from the left. [1]
Under California’s election rules, if no candidate receives more than fifty percent of votes in the primary, the top two candidates advance to a November runoff election. Mayor Bass secured enough votes to advance. The race for second place — and the November runoff slot — became a contest between Pratt and Raman. [2]
A pre-election UC Berkeley-LA Times poll conducted in May 2026 showed Bass with twenty-six percent support, Raman at twenty-five percent, and Pratt at twenty-two percent among likely voters — a margin of error of approximately three percent. [3]
Figure 1: Election Night vs. Mail-In Ballot Performance — LA Mayoral Race 2026
Election Night Results
Pratt significantly outperformed his pre-election polling. With sixty-six percent of the expected vote counted on election night, results showed:
Karen Bass: 35% Projected to advance to November runoff
Spencer Pratt: 29.4% Comfortably in second place
Nithya Raman: 23.4% Trailing Pratt by approximately six percentage points
Pratt held what appeared to be a comfortable lead over Raman. By Thursday, with additional votes counted, the gap remained near six percentage points. [4]
With 163,549 votes in Los Angeles’ latest tabulation, Pratt maintains a near 6% lead on Raman, who has 130,473 votes. — Fox News, Thursday June 5, 2026 [4]
The Mail-In Ballot Divergence
As mail-in ballot batches were counted and released in the days following the election, a striking divergence from election night results emerged. Rather than tracking the established proportions, the mail-in batches showed a dramatic and statistically extraordinary shift.
The Zero-Vote Batch
The initial anomaly identified was a batch of approximately 24,000 mail-in ballots in which Pratt received zero votes. At his election night rate of 29.4 percent, the expected number of Pratt votes in such a batch would be approximately 7,056.
Probability of zero Pratt votes in 24,000 ballots at 29.4%: 1 in 10^3,629 Effectively impossible by random chance
For context: the total number of atoms in the observable universe is estimated at approximately 10^80. The probability of Pratt receiving zero votes in that batch, if his actual support rate was 29.4 percent, is incomparably smaller than randomly selecting one specific atom from the entire universe on the first attempt.
The Subsequent Batch Analysis
Examining the larger batch of mail-in votes reported since Thursday — totaling 54,245 votes across Pratt, Raman, and Bass — the divergence becomes statistically quantifiable. [5]
Pratt mail-in share: 19.7% vs. 29.4% election night — deficit of 9.7 percentage points
Raman mail-in share: 42.6% vs. 23.4% election night — gain of 19.2 percentage points
Pratt vote deficit: 5,237 votes Below statistically expected count in this batch alone
In concrete terms: if mail-in ballots had simply reflected election night proportions, Pratt would have received approximately 15,948 votes in the analyzed batch. He received 10,711 — a shortfall of 5,237 votes in a single counting batch.
Statistical Analysis
The Chi-Square Test
The chi-square test measures whether an observed distribution of votes differs significantly from what would be expected based on a reference distribution — in this case, election night proportions. Applying this test to the mail-in batch:
Chi-square statistic: 10,376.18 Extraordinarily high — any value above 6 is statistically significant at the 95% confidence level
Degrees of freedom: 2 Three candidates minus one
P-value: Effectively zero The probability this divergence occurred by random chance
A p-value of zero means the observed distribution of mail-in votes cannot be explained by random sampling variation from the election night population. Under standard statistical thresholds, a p-value below 0.05 is considered statistically significant. A p-value below 0.001 is considered highly significant. This result is not in that range — it is below any threshold that statistical science has developed to describe.
The Z-Score Analysis
The z-score measures how many standard deviations an observed result falls from its expected value. In normal human affairs, results beyond three standard deviations are considered extraordinary and warrant investigation. Results beyond five standard deviations are considered essentially impossible by random chance.
Z-score for Pratt’s mail-in performance: -49.35 Forty-nine standard deviations below his election night rate
A z-score of negative forty-nine does not exist in the normal range of human statistical experience. To find a naturally occurring phenomenon with a z-score of this magnitude would require examining astronomical datasets, not election results. This number is not an anomaly. It is a mathematical impossibility under any standard probability model that assumes mail-in voters come from the same population as election day voters.
In statistics, anything beyond three standard deviations is considered extraordinary. Forty-nine standard deviations is not a number that occurs in nature through random variation.
The Current State of the Race
The cumulative effect of these mail-in batches has been dramatic. [6][7]
Pratt current share (78% counted): 27.3% Down from 29.4% election night
Raman current share (78% counted): 26.2% Up from 23.4% election night
Current Pratt lead: Approximately 7,500 votes Narrowing with each batch
Raman received forty percent of votes counted on Saturday — a figure that, if sustained, would be sufficient to overtake Pratt before all ballots are counted. [7]
The race remains uncalled. California law allows counties up to thirty days to complete the official canvass. Millions of mail-in and provisional ballots remain to be processed in Los Angeles County alone — the largest voting jurisdiction in the United States, with 5.8 million registered voters. [8]
Three Possible Explanations
Statistical analysis identifies the anomaly. It does not, by itself, determine the cause. There are three explanations that must be considered:
Explanation One: Population Differences
California leads the nation in mail-in voting, with eighty-one percent of voters sending their choices by post in 2024 — nearly double the national average. [9] It is theoretically possible that Pratt’s support is concentrated among voters who specifically chose to vote in person on election day, and that mail-in voters skew heavily toward Raman and Bass.
However: even accepting significant population differences, a forty-nine standard deviation divergence cannot be explained by population variation alone. The pre-election poll showing Pratt at twenty-two percent among likely voters — not a dramatically different figure from his election night performance — did not distinguish between mail-in and in-person likely voters in a manner that would predict a divergence of this magnitude.
Explanation Two: Counting Methodology or Batch Composition
It is possible that specific batches of mail-in ballots being counted represent geographically concentrated areas where Raman has disproportionate support — council districts she represents, for example — and that the batches are not representative of the overall mail-in population.
If this is the explanation, the Los Angeles County Registrar-Recorder should be able to document precisely which geographic areas each batch represents and demonstrate that the composition explains the divergence. That documentation should be made public.
Explanation Three: Something Requiring Investigation
The third possibility is that something in the counting or reporting process is producing results that do not accurately reflect the votes cast. This article does not allege this is the case. However, the statistical evidence is sufficiently extreme that it cannot be dismissed without documented, transparent explanation of the first or second type.
What Transparency Requires
In a functioning democracy, election results that produce statistical anomalies of this magnitude demand documented explanation — not reassurance, not dismissal, but transparent accounting of the counting process. Specifically:
The Los Angeles County Registrar-Recorder should publicly document the geographic composition of each mail-in batch released since election day — demonstrating which precincts or council districts each batch represents and how that composition accounts for the observed divergence.
The methodology for selecting, processing, and releasing mail-in ballot batches should be made publicly available.
Any candidate or party requesting observation of the counting process should be granted that access consistent with California election law.
The zero-vote batch — 24,000 ballots producing zero votes for a candidate receiving approximately 29.4 percent of all other votes — requires specific and documented explanation.
The appropriate response to a statistical anomaly in a democracy is transparency and documentation — not political dismissal or reassurance. The numbers are what they are. They deserve a clear answer.
Conclusion
Spencer Pratt received approximately 29.4 percent of votes cast on election day in the Los Angeles mayoral primary. In subsequently counted mail-in ballot batches, he has received approximately 19.7 percent — a divergence of 9.7 percentage points that produces a z-score of negative forty-nine and a chi-square statistic of over 10,000.
These numbers are not consistent with random sampling variation from the same voter population. They are not explained by normal statistical fluctuation. They demand a documented, transparent, and geographically specific explanation from Los Angeles County election officials.
The question is not whether Spencer Pratt should be the next mayor of Los Angeles. The question is whether the vote count accurately reflects the votes that were cast. In a democracy, that question is never inappropriate to ask — and it is always appropriate to demand a clear answer.
Chris Mark is an Enterprise Security and Risk Strategist, published author, co-author of PCI DSS, named patent holder, and United States Marine Corps combat veteran. He writes on security, risk, and emerging threats at GlobalRiskInfo.com.
References
[1] NBC News. (2026, June 2). Los Angeles Mayor Primary 2026 Live Results. nbcnews.com/politics/2026-primary-elections/los-angeles-mayor-results
[2] ABC7 Los Angeles. (2026, June 4). Los Angeles mayor race: Live election results and updates on front runners Karen Bass, Nithya Raman, Spencer Pratt. abc7.com
[3] CBS Los Angeles. (2026, June 7). Pratt’s lead over Raman slims in new L.A. mayoral election results. [Citing UC Berkeley-LA Times poll, May 28, 2026, margin of error approximately 3%.] cbsnews.com/losangeles
[4] Fox News. (2026, June 5). Spencer Pratt loses ground to Democrat while Hilton maintains lead in latest California ballot batch drop. foxnews.com
[5] Fox 11 Los Angeles. (2026, June 6). LA mayor’s race: Nithya Raman surges, closes gap on Spencer Pratt for runoff spot. foxla.com. [Reporting Raman: 23,115 votes (38%), Bass: 20,419 votes (34%), Pratt: 10,711 votes (18%) in mail-in batch since Thursday.]
[6] CBS Los Angeles. (2026, June 7). Pratt’s lead over Raman slims in new L.A. mayoral election results. cbsnews.com/losangeles. [Citing 78% of votes counted, Pratt 27.3%, Raman 26.2%.]
[7] The Wrap. (2026, June 7). Nithya Raman Inches Within 1% of Spencer Pratt After Winning 40% of Saturday Tally in LA Mayor’s Race. thewrap.com
[8] NBC Los Angeles. (2026, June 6). Gap between Pratt and Raman gets tighter in LA mayoral race. nbclosangeles.com. [Noting 5.8 million registered voters in Los Angeles County.]
[9] Fox News. (2026, June 5). Spencer Pratt loses ground to Democrat. [Citing California leads nation in mail-in voting at 81% of voters in 2024, nearly double national average of 43%.]
[10] Statistical methodology: Binomial probability calculation P(X=0) = (1-p)^n. Chi-square test comparing observed mail-in distribution to election night baseline. Z-test for proportions: z = (p_observed – p_expected) / sqrt(p_expected*(1-p_expected)/n). All calculations performed using Python scipy.stats library.© 2026 Chris Mark / GlobalRiskInfo.com. All rights reserved. Reproduction with attribution
