Category Archives: Security

Zuckerberg on Rogan: Meta Has Always Been “something out of 1984”

Facebook was literally founded on stealing private images to abuse women, using a popularity pageant as pretext for public shaming.

Mark E. Zuckerberg ’06 said he was accused of breaching security, violating copyrights and violating individual privacy… Zuckerberg said that he was aware of the shortcomings of his site, and that he had not intended it to be seen by such a large number of students.

Yeah, ok Mark.

The bank robber didn’t expect the bank to see him rob it? Did he think he was Big Brother? All seeing, but never seen…

He setup a public website to watch and control women. We’re supposed to believe it wasn’t intended to be accountable from “such a large number of students” (meaning he thought his victims shouldn’t have a say in his abuse of them), as if that’s even a reasonable excuse?

When women of color at Harvard called out this privileged criminal’s dishonest disinformation tactics, Zuckerberg faced absolutely no consequences and instead grabbed himself a girl to ride off into Silicon Valley like a bro celebrity with millions of dollars in his pockets somehow.

But my best memory from Harvard was… I had just launched this prank website Facemash, and the ad board wanted to “see me”. Everyone thought I was going to get kicked out. My parents came to help me pack. My friends threw me a going away party… in what must be one of the all time romantic lines, I said [to a girl at the party]: “I’m going to get kicked out in three days, so we need to go on a date quickly.” Actually, any of you graduating can use that line. I didn’t end up getting kicked out — I did that to myself. …you could say [Facemash] was the most important thing I built in my time here.

Framing serious ethics violations as pranks while converting harm into personal gain didn’t just continue, it was rewarded by Harvard. The institution itself became an early investor into his bigger platform concept of capture and extraction of value from targets (especially women), setting a pattern that continues today.

Twenty years later, it seems things maybe are getting even worse, thanks to people like Joe Rogan. In his recent interview, Zuckerberg deployed a classic tactic of information warfare: reframing accountability for attacks as being persecuted.

“It really is a slippery slope,” Zuckerberg told Rogan, while expressing worry about “becoming this sort of decider of what is true in the world.”

By claiming Meta’s fact-checking was “something out of 1984” while invoking a “slippery slope” fallacy, he attempts to recast being in absolute control over his content moderation system as also being a victim of oppression by basic societal ethics (known since the 1700s as a system of inherited rights — law and order — that prevents tyrannical abuses).

His intentional self-contradiction is glaring. Every algorithm tweak and content policy is Zuckerberg actively deciding truth on his platform as evidenced by his own admission that he unilaterally was always “deciding truth” and overseeing all fact-checking.

Relationships were so frayed [by refusing to admit I was wrong] that within a year or so every single person on the management team was gone.

Zuckerberg’s rhetorical duplicity and sleight-of-hand becomes particularly stark alongside his dismantling of diversity programs and relaxation of hate speech policies. When faced with responsibility for egregious harm, Zuckerberg’s defense is as absurd as an industrial-era factory owner claiming coal restrictions would be on a slippery slope to “dangerously clean air” – it’s simply a privileged attempt to avoid accountability through childish fallacies for narrative control.

He may as well have said he was in danger of being run over by a unicorn that morning. There’s never a unicorn, there’s never a slippery slope – there’s only Zuckerberg intentionally facilitating widespread abuse of people with a big wink and a nod from someone who also rose to prominence promoting violence for profit.

The parallel is telling: Rogan got rich promoting consensual fights while Zuckerberg got rich exploiting non-consensual ones. Is it any wonder Rogan rolled over like a lapdog when Zuckerberg claimed he should face no external restrictions of any kind when aiming to profit from external harms?

Trump’s Hoover Maneuver: 1932 Bonus Crisis Looms Over “Severance” Case of Federal Workers

As a student of information warfare and American history, I can’t help but notice the unsettling parallels between today’s federal workforce crisis and the Bonus Army situation of 1932. In both cases, we see a fundamental conflict over promised government compensation during times of economic uncertainty.

Nearly 100 years ago American military veterans marched en masse on Washington demanding early payment of service certificates they were owed.

Just before Congress adjourned in the summer of 1932, thousands of desperate World War I veterans surrounded the U.S. Capitol. With the nation in the grips of the Great Depression, the House of Representatives had approved a bill to provide immediate cash payments to veterans. Servicemembers now waited anxiously as the Senate debated the same bill. At issue was the question, What did the nation owe its veterans?

Notably, servicemember camps setup around the Capitol were “racially integrated, vibrant communities“, a very alarming situation to those holding a line on extremely racist power. In other words the outspoken primary opponent to giving veterans money owed was from Senator Joseph T. Robinson of Arkansas – a violent segregationist during the Jim Crow era who also opposed anti-lynching legislation. He rose to Senate Majority Leader in 1933 where he blocked all civil rights legislation for the next four years.

September 15, 1932, an American Black man named Frank Tucker was lynched in Crossett (Ashley County), Arkansas. He was paraded through the business district with a rope around his neck to generate a mob of 500 people, who then hanged him from an iron pipe, later dismembering Tucker’s body into pieces for the American “lynching souvenir” business of profiting from racist torture and murder.

The Hoover administration’s response to the integrated Americans demanding rights was to characterize military veterans – who had served their country faithfully and had followed the proper channels for basic income – as opportunists and troublemakers. Today, we hear similar rhetoric, with the White House describing federal workers as “lazy” and accusing them of “ripping off the American people” by doing their jobs.

The Bonus Army crisis escalated when the Hoover administration sent the racist and segregationist General Douglas MacArthur to forcibly remove the veterans from their integrated encampments. For context, MacArthur’s tenure as Army Chief of Staff from 1930 to 1935 heavily promoted institutional racism. Later, as Supreme Commander of Allied Powers in occupied Japan, he again promoted racial segregation policies. However it was his conduct during the Korean War that has drawn the most scrutiny from historians in terms of his deeply flawed strategic decision making – racism against Asians caused unnecessary losses due to consistent underestimation of Chinese military capabilities.

Thurgood Marshall recalled that General MacArthur, who believed that American Blacks were inferior to whites, was the greatest impediment to the Army’s desegregation in Korea. Things changed rapidly as soon as Truman fired him in 1951.

Today’s situation, while different in its details, shows similar signs of escalating tension, as well as racist underpinnings to attacks on diverse groups of federal workers. The administration’s recent memo threatening those who remain with “enhanced standards of suitability and conduct” and warning of prioritized “investigation and discipline” creates an atmosphere of intimidation reminiscent of the Jim Crow era.

Just as the Bonus Army veterans faced uncertainty about whether they would ever receive their promised compensation, today’s federal workers are being offered a deal that unions warn may never be paid because it lacks congressional authorization. The administration’s pressure tactics – including warnings about impending layoffs and demands for “loyalty” – echo the kind of strong-arm approaches that characterized the government’s response to the Bonus Army.

What’s particularly concerning is how this situation could potentially escalate. The Bonus Army crisis became a watershed moment in American history not because of the initial dispute, but because of how the government chose to handle it. The sight of American troops attacking American veterans created a public relations disaster that contributed to Hoover’s defeat.

Today, we’re seeing scattered protests outside federal buildings. One worker quoted in recent reporting expressed fear that “we’re all going to lose our jobs and they’re going to put all these loyalists or people that will be their shock troops.” This language of “shock troops” and loyalty tests yet again eerily mirrors the militaristic response to the Bonus Army.

The critical difference now is that we have the benefit of historical hindsight.

The Bonus Army crisis teaches us that handling of regular government workers – whether veterans or civil servants – as enemies of the state rather than as dedicated public servants tends to backfire both politically and practically. When the racist segregationist MacArthur led troops against the desegregated Bonus Army, he wasn’t just attacking a group of protesters – he was attacking the very idea that the government should honor its commitments to all those Americans who serve it.

In the current situation, federal courts have already stepped in to temporarily halt the administration’s plans. This judicial intervention offers hope that we might avoid the kind of confrontation that marked the Bonus Army crisis. However, the administration’s rhetoric and tactics suggest they may not be learning the correct lessons that history offers.

The ultimate resolution of the Bonus Army crisis – Congress finally authorizing early payment in 1936 – reminds us that these situations eventually require legislative solutions, not executive force. Today’s federal workers, like the veterans of 1932, are simply asking the government to treat them with the respect and consideration they’ve earned through their service.

As we watch this situation unfold, we would do well to remember that the Bonus Army crisis didn’t have to end in tear gas and burning encampments. It escalated because racist leadership chose confrontation over negotiation, forceful bluster over competency in dialogue. Let’s hope today’s leaders can learn from clear historical mistakes before we witness another awful MacArthur moment in American history.

Trump keeps praising a controversial American general whose actions nearly prompted World War III: “MacArthur was considered a ‘media whore’ of his time, Daniel Drezner, a professor of international affairs at Tufts University, told Reuters.” […] “I fired him because he wouldn’t respect the authority of the president,” Truman later explained. “I didn’t fire him because he was a dumb son of a bitch, although he was, but that’s not against the laws for generals.”

Truman later said that he had become anti-racist by 1946, which perhaps helps explains why he put such an abrupt end to huge “dumb” mistakes being made by an obviously racist MacArthur. And also explains why Trump keeps trying to repeat those same mistakes.

The Bluster of AI Nationalism: Comrade Hawley Cancels Chinese Code

Xenophobic Political Theater Undermines Security and Innovation

Recent legislation proposing to “decouple” American AI from China presents itself as a national security measure. However, it follows a disturbing historical pattern of technological nationalism that has repeatedly harmed both innovation and human dignity in American history.

The rhetoric surrounding this AI legislation eerily mirrors the Chinese Exclusion Act of 1882, the first major law restricting immigration based on nationality.

Leland Stanford’s racist platform targeting American Asians became increasingly violent over just five years, setting the stage for internment camps.

Both share a fundamental contradiction: wanting Chinese labor and expertise while simultaneously seeking to exclude Chinese people and contributions.

Stanford University’s own history exemplifies this contradiction. Chinese laborers were instrumental in building the transcontinental railroad that created the fortune of Leland Stanford. These workers faced brutal conditions, earned lower wages than their white counterparts, and were forced to work in the most dangerous conditions – leading to the horrific practice of measuring tunnel-blasting time as a “Chinaman minute,” calculating how many Chinese would be killed per unit of progress.

Yet after the railroads were built, these same workers were blocked from citizenship, property ownership, and economic advancement through systematic legal discrimination. Stanford University itself, built with wealth from Chinese labor, would later enforce strict quotas on Chinese students.

California white businessmen simply criminalized Asians to eliminate them from competition in agriculture, which is why Hawaii never saw these camps despite 37% of its population being of Japanese descent in 1940, compared to less than 2% on the West Coast. Left: A Japanese-American woman holds her sleeping daughter as they prepare to leave their home for an internment camp in 1942. Right: Japanese-Americans interned at the Santa Anita Assembly Center at the Santa Anita racetrack near Los Angeles in 1942. (Library of Congress/Corbis/VCG via Getty Images/Foreign Policy illustration)

Notably the proposed AI bill literally suggests 20 years of jail for anyone found using a computer that has evidence of “models” from China.

According to the language of the proposed bill, people who download AI models from China could face up to 20 years in jail, a million dollar fine, or both.

Imagine the kind of politician who dreams of a future where simply dropping a model on someone’s computer gets them swept off to jail for decades.

This pattern of wanting Chinese contribution while seeking to criminalize and exclude Chinese influence is technically impossible in modern AI development. The reality of artificial intelligence creation defies such artificial boundaries. Modern AI stands on the shoulders of Chinese-American innovators, perhaps most notably in the case of ImageNet. This revolutionary dataset, which transformed computer vision and helped launch the deep learning revolution, was created by Fei-Fei Li, who immigrated from China to the US and led the project at Stanford. The story of ImageNet exemplifies how arbitrary and harmful national divisions in technology can be.

The technical integration goes even deeper when we examine a typical large language model. Its attention mechanism derives from Google’s transformer architecture, developed in the US, while incorporating optimization techniques pioneered at Tsinghua University. The model runs on GPUs designed in America but manufactured in Taiwan, implementing deep learning principles advanced through international collaboration between researchers like Yann LeCun in the US and Jian Sun at Microsoft Research Asia. The training data necessarily incorporates Chinese web content and academic research, while the underlying software libraries include crucial contributions from developers worldwide, including significant optimizations from teams at Alibaba and Baidu.

The recent panic over DeepSeek perfectly illustrates this contradiction. While lawmakers rush to ban a Chinese AI model from American devices, they ignore that any open model can be fully air-gapped and run offline without any connection to its origin servers. Meanwhile, Zoom – which handles everything from classified research discussions to defense contractor meetings on university campuses – frequently processes data through Chinese code and infrastructure with minimal or no security review.

Or consider Tesla, whose Nazi-promoting eugenicist South African CEO openly praises China as his favorite government with the largest market and manufacturing base while simultaneously acquiring unprecedented access to U.S. government contracts and infrastructure projects. There couldn’t be a more obvious immediate national security threat than Elon Musk.

This inconsistent approach – where some Chinese technology connections trigger alarm while others are ignored – reveals how these policies are more about political theater than actual security. Real security would focus on technical capabilities and specific vulnerabilities, not simplistic national origins.

Modern AI development relies on an intricate web of globally distributed computing infrastructure. The hardware supply chains span continents, while the open-source software that powers these systems represents the collective effort of developers across the world. Research breakthroughs emerge from international collaborations, building on shared knowledge that flows across borders as freely as the data these systems require.

Let’s be clear: espionage threats are real, and data security across borders is a legitimate concern. However, the fundamental weakness of nationalist approaches to security is their reliance on binary, overly simplistic classifications. “Chinese” versus “American” AI creates exactly the kind of rigid, brittle reactive security model that sophisticated attackers exploit most easily, making everything less safe.

Robust security systems thrive on nuance and depth. They employ multiple layers of validation, contextual analysis, and sophisticated inference to detect and prevent threats. A security model that sorts researchers, code, or data into simple national categories without thought is like France thinking defense meant an expensive concrete Maginot line, without trucks or planes. No adaptive, intelligent internal security means one simple breach compromises everything. Real security requires technical solutions that can handle nuance, detect subtle patterns, and proactively adapt to emerging threats.

The defense of Ukraine against Russian invasion demonstrates this principle perfectly. When Russian forces attempted to seize Hostomel Airport near Kyiv, Ukraine’s defense succeeded not through static border fortifications, but through rapid threat identification and adaptive response. While main forces were positioned at the borders, regular troops at Hostomel identified and engaged helicopter-borne attackers immediately, holding out for two crucial hours until reinforcement brigades arrived. This adaptive defense against an unexpected vector saved Kyiv from potential capture. Similarly, effective AI security requires moving beyond simplistic border-based restrictions to develop dynamic, responsive security frameworks that can identify and counter threats regardless of their origin point.

Consider how actual security breaches typically occur: not through broad categories of static nationality, but through specific vulnerabilities, social engineering, and careful exploitation of trust boundaries. Effective security measures therefore need to focus on technical rigor, behavioral analysis, and sophisticated validation frameworks – approaches that become harder, not easier, when we artificially restrict collaboration and create simplistic trust boundaries based on nationality.

Just as the Chinese Exclusion Act failed to address real economic challenges while causing immense human suffering, this attempt at technological segregation would fail to address real security concerns while hampering innovation and perpetuating harmful nationalist narratives.

The future of AI development lies not in futile attempts at nationalistic segregation and incarceration, but in thoughtful collaboration guided by strong technical standards and security frameworks. The global nature of AI development isn’t a vulnerability to be feared, it’s a strength to be lead by embracing technical excellence and rigorous security practices that focus on capabilities rather than simplistic national origins.

As we stand at the dawn of the AI era, we face the same choice that has confronted American innovation throughout history: we can repeat the mistakes of xenophobic restrictions that ultimately harmed both American security and human dignity, or we can embrace the inherently open nature of technological progress while building the technical frameworks needed to ensure its responsible development.

Dangerous Leaks Reported From Elon Musk’s Big Balls

The guy called Big Balls who was hired by Elon Musk to breach federal data, has a history of ethics violations.

Musk’s DOGE Teen Was Fired By Cybersecurity Firm for Leaking Company Secrets. Edward Coristine posted online that he had retained access to the firm’s servers. Now he has access to sensitive government information.

DOGE having Big Balls is now described as threat to public health