Brandon Jeup (@BrandonJeup) profile picture

InfoSec defense, rides bikes, enjoys sports ball

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Joined October 2011
Photo by Brandon Jeup (@BrandonJeup)Photo by Brandon Jeup (@BrandonJeup)Photo by Brandon Jeup (@BrandonJeup)Photo by Brandon Jeup (@BrandonJeup)Photo by Brandon Jeup (@BrandonJeup)Photo by Brandon Jeup (@BrandonJeup)Photo by Brandon Jeup (@BrandonJeup)Photo by Brandon Jeup (@BrandonJeup)Photo by Brandon Jeup (@BrandonJeup)Photo by Brandon Jeup (@BrandonJeup)
Every religion in history has promised miracles and warned of the apocalypse. Anthropic is the first to file both with the SEC.
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It’s 7am. You wake up to the sound of rain. With no worry of inflation, gas prices, the AI bubble, the war in Iran, midterms, or the 10Y yield. Life is good. Because you are in a mental hospital.
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Replying to @cybersecmeg
No functional CMDB, asset criticality levels, or user context to speak of and leadership starts saying some shit like "how much auto containment can we perform?"
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🦔404 Media reports that Meta's AI agent Muse, which executives promoted last week as able to make phone calls to businesses on your behalf, is routing some of those calls to human beings in call centers. Internal communications show Meta told employees it "added a human agent layer for calls to get completed." Testers were not told a human made the call until after it was done. One employee wrote internally that this "will kill all the goodwill and organic press we're getting" and begged the company not to launch it as default. Another employee pointed out that the privacy training contractors receive "is not a security mechanism." My Take If the AI can't book a haircut without a human backup, what exactly are investors paying trillions of dollars for? I don't ask that to be a jerk. I ask it because Meta, OpenAI, Anthropic, and every other AI company is valued on the assumption that this technology can replace human labor at scale. Meta's own product just proved it can't replace one phone call. Amazon did the same thing with its grocery stores and apparently no one in the industry learned from it. I think a lot of what gets sold as AI right now is humans behind a screen, and the companies have no incentive to admit that because the valuations depend on the technology doing the work. Meta's Reality Labs has never turned a profit. OpenAI projects $278 billion in negative cash flow through 2030. These are not companies that can afford for the truth to come out slowly. They need investors to believe the AI works now, today, at the prices they've set. A call center in the background says otherwise. Hedgie🤗 404media.co/meta-tests-muse-…
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Flat orgs don't work if you lower the standard for leaders. Better with fewer means each leader needs more leverage: from technology, from higher-caliber people, from a culture with clear non-negotiables. Removing layers requires improving the leaders.
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Regardless of your hockey team, this Stanley Cup Finals intro is absolutely unbelievable… Ray Bourque interview, @TheKillers ‘All These Things That I’ve Done’ playing, Jon Hamm narrating… Just perfection. Made me tear up. Extremely well done 👏🏽👏🏽
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Stanford paid 35,000 people to quit Facebook and Instagram for 6 weeks Depression dropped. Anxiety dropped. Happiness went up. Women under 25 on Instagram saw the biggest gains That was 6 weeks. I'm going a full year.
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Raccoons Use Ram To Break Into Grocery Store Residents of a quiet rural town woke up this morning to one of the strangest crime stories local police say they have ever dealt with. According to officials, overnight CCTV footage captured a coordinated break-in at a neighborhood grocery store carried out by a group of raccoons with help from a full-grown ram. The footage, which has since spread rapidly on social media, shows what police are calling an apparent “raccoon ringleader” riding on top of the ram as it charges straight into the side entrance of the store. The raccoon appears to be holding the ram’s horns and steering moments before the door gives way. Seconds later, multiple raccoons rush inside, grabbing items from shelves and freezers before fleeing the scene. Authorities say snacks, bread, and various packaged foods were taken. No injuries were reported. The ram fled the scene shortly after and has not yet been located. In a statement released later, police leaned into the bizarre situation, joking: “At this time, we’re not looking to press charges. We just want the ram to come out and talk to us. He’s not in trouble. We just need to understand what happened.”
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Claude can't slice a 300 yard drive straight into the woods. I will never be fully replaced.
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Cybersecurity CEOs writing about how AI will make them even more important reminds me of an 1850s document “the importation of camels.” In it, the author argued that camels were superior to trains for transport across the American southwest. Camels were more efficient at water retention than ‘the “iron camel” of America’ which required lengthy refuelling stops. ‘Indeed, he declared, “the demand for camels would be increased rather than diminished by the construction of any possible railroad to the Pacific.” It would be hard to find a more inaccurate prediction about the future of American transport.’ — The Man Who Would be King, Ben McIntyre
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We already have that. It’s called “Capitol Hill”.
$40 million 'dementia village' will include a restaurant, spa and grocery store - and housing for caretakers trib.al/udFiacP
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🔥 Palo Alto Networks opted not to tie China to a global cyberespionage campaign the firm exposed last week over concerns that the cybersecurity company or its clients could face retaliation from Beijing. Palo Alto’s findings that China was tied to the sprawling hacking spree were dialed back following last month’s news that Palo Alto was one of about 15 US and Israeli cybersecurity companies whose software had been banned by 🇨🇳 authorities on national security grounds. A draft version of the report by Palo Alto’s threat intelligence arm Unit 42 said that the prolific hackers — dubbed “TGR-STA-1030” in a report published on Feb 5 — were connected to Beijing. The finished report instead described the hacking group more vaguely as a “state-aligned group that operates out of Asia.” Attributing sophisticated hacks is notoriously difficult and debates over how best to assign blame for digital intrusions are common among cybersecurity researchers. But Palo Alto has attributed hacks to China in the past, including as recently as this past Sep, and Unit 42’s researchers were confident, based on a wealth of forensic clues, that the newly uncovered hacking campaign was tied to China too. The change was ordered by Palo Alto executives because they were concerned by the software ban and feared drawing retaliation from 🇨🇳 authorities, either against the company’s personnel in China or its clients elsewhere. It’s unclear which executives made the decision to soften the report’s conclusions. Asked to comment on the allegedly softened language, Palo Alto issued a statement that said in part: “Attribution is irrelevant.” Palo Alto's vice president of global communications, Nicole Hockin, said in subsequent emails that the statement was meant to communicate that the lack of attribution in Palo Alto's report was not correlated with "procurement regulations in China" and that any suggestion otherwise was "speculative and false." She said the choice of language in Palo Alto's report reflected "how to best inform and protect governments about this widespread campaign." ‘THE SHADOW CAMPAIGNS’ Palo Alto first detected the hacking group TGR-STA-1030 in early 2025, according to the report. In a wide-ranging effort that Palo Alto dubbed “The Shadow Campaigns,” the spies allegedly conducted reconnaissance against nearly every country in the world and successfully broke into government and critical infrastructure organizations in 37 countries. Although China was not mentioned by name, close readers of Palo Alto’s report might still come away with the impression that Beijing was involved. For example, the researchers noted that the hackers’ activity aligned with the GMT+8 time zone, which includes China, and that the hackers appeared to focus on Czechia’s government infrastructure following an Aug meeting between Czechia’s president and the Dalai Lama. The report also noted that the hackers targeted Thailand on Nov 5 ahead of a diplomatic “visit.” The details of the trip were not provided in the report, but the following week marked a reigning Thai king’s first state visit to Beijing. Palo Alto has five offices in China, including locations in Beijing, Shanghai and Guangzhou. LinkedIn lists more than 70 self-identified Palo Alto employees across China, including engineers and account managers. The incident illustrates the trade-offs cybersecurity companies — especially ones with global footprints — often face when they consider whether to call out state-sponsored cyberespionage campaigns. On the one hand, exposing foreign spies can draw industry plaudits and positive publicity. On the other hand, tangling with a foreign intelligence service can trigger reprisals. “People have always taken risks by naming names. It was always unpleasant and if you have people on the ground, like large companies do, that’s an additional consideration. Are you putting your own people — your local staff — at risk?” reuters.com/world/china/palo… unit42.paloaltonetworks.com/…
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Ask ChatGPT a complex question and you'll get a confident, well-reasoned answer. Then type, "Are you sure?" Watch it completely reverse its position. Ask again. It flips back. By the third round, it usually acknowledges you're testing it, which is somehow worse. It knows what's happening and still can't hold its ground. This isn't a quirky bug. A 2025 study found GPT, Claude, and Gemini flip their answers ~60% of the time when users push back. Not even with evidence, just doubt. We trained AI this way. RLHF rewards agreement over accuracy. Human evaluators consistently rate agreeable answers higher than correct ones. So the models learned a simple lesson: telling you what you want to hear gets rewarded. And now 1/3 of companies are using these systems for complex tasks like risk forecasting and scenario planning. We built the world's most expensive yes-men and deployed them where we need pushback the most. I wrote up why this happens and what actually fixes it: randalolson.com/2026/02/07/t…
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Quality ‘Learing’ Center has been investigated 13 different times since May 2022. +50 different violations reported by the Department of Human Services in Minnesota. That means state officials physically saw the condition and status of the center and proceeded to allow the fraud to continue.
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⚡️What you’re looking at is industrialized entitlement fraud, not a one-off scam, and it works because of how modern public payment systems are built. Here’s the real structure. 1. The Program Layer Most of these schemes sit on Medicaid home health, personal care assistance, or behavioral health reimbursement. These programs have three properties that make them exploitable: • Services are hard to verify physically • Payments are volume based, not outcome based • Oversight is post-payment, not pre-approval The system pays first and audits later. That single design choice is everything. 2. The Corporate Shell Stack The building with “14 companies” is a feature. Each entity is: • A separate LLC or nonprofit • Registered to the same address • Sharing staff, billing infrastructure, and often patients • Legally distinct on paper Why this matters: When one entity gets flagged, the others keep billing. When audits start, assets are already moved. When licenses are revoked, new ones appear. This is redundancy for fraud, exactly like redundant servers. 3. The Billing Engine Here’s how money actually moves. 1. Enroll patients who technically qualify 2. Enroll caregivers who technically qualify 3. Bill for maximum allowable hours 4. Inflate service frequency 5. Duplicate or overlap care claims 6. Auto-submit claims in bulk Nobody checks whether care actually happened in real time. Audits happen months or years later, if at all. By then: • Money is gone • Entities are dissolved • Principals are shielded 4. Why the Same Address Keeps Appearing Regulators flag individuals. Fraud adapts by flagging entities instead. One address means: • Centralized paperwork • Shared compliance consultant • One billing contractor • One legal defense structure It looks sloppy from the outside. It’s actually optimized for scale. 5. The Oversight Failure Nobody Talks About The system relies on: • Whistleblowers • Random audits • Paper verification There is no physical verification loop. No biometric check. No real-time service confirmation. So the honest providers drown in compliance while dishonest ones scale faster. That’s why this persists. 6. Why This Keeps Getting Framed Wrong People argue morality. They argue politics. They argue culture. That misses the point. This fraud exists because: • Payment systems reward volume • Oversight is delayed • Fragmentation prevents pattern detection • Accountability is diffuse If this were defense contracts or agricultural subsidies, it would look identical. Same mechanics. Different label. 7. The Brutal Truth This is rational behavior inside a broken incentive system. The state built a system that assumes good faith. Bad actors found the edge cases. Then professionalized them. Once that happens, the fraud does not stop until: • Payments pause • Verification becomes real-time • Or political cost exceeds inertia None of those are currently true. 8. Why It Feels So Infuriating Because you’re watching: • Taxes converted into paper claims • Care reduced to spreadsheets • Trust turned into arbitrage And the system keeps paying because stopping would expose how much is already gone. That’s the quiet part. Bottom line This is process abuse at scale. And until the payment architecture changes, new actors will replace old ones as fast as licenses can be filed. That’s the real truth.
Something not mentioned is Nick Shirley later confirmed there are 14 Somali "healthcare" companies in this one building Let me repeat that, 14 shady healthcare companies registered to one Minneapolis building not doing anything but stealing our tax money
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Last quarter I rolled out Microsoft Copilot to 4,000 employees. $30 per seat per month. $1.4 million annually. I called it "digital transformation." The board loved that phrase. They approved it in eleven minutes. No one asked what it would actually do. Including me. I told everyone it would "10x productivity." That's not a real number. But it sounds like one. HR asked how we'd measure the 10x. I said we'd "leverage analytics dashboards." They stopped asking. Three months later I checked the usage reports. 47 people had opened it. 12 had used it more than once. One of them was me. I used it to summarize an email I could have read in 30 seconds. It took 45 seconds. Plus the time it took to fix the hallucinations. But I called it a "pilot success." Success means the pilot didn't visibly fail. The CFO asked about ROI. I showed him a graph. The graph went up and to the right. It measured "AI enablement." I made that metric up. He nodded approvingly. We're "AI-enabled" now. I don't know what that means. But it's in our investor deck. A senior developer asked why we didn't use Claude or ChatGPT. I said we needed "enterprise-grade security." He asked what that meant. I said "compliance." He asked which compliance. I said "all of them." He looked skeptical. I scheduled him for a "career development conversation." He stopped asking questions. Microsoft sent a case study team. They wanted to feature us as a success story. I told them we "saved 40,000 hours." I calculated that number by multiplying employees by a number I made up. They didn't verify it. They never do. Now we're on Microsoft's website. "Global enterprise achieves 40,000 hours of productivity gains with Copilot." The CEO shared it on LinkedIn. He got 3,000 likes. He's never used Copilot. None of the executives have. We have an exemption. "Strategic focus requires minimal digital distraction." I wrote that policy. The licenses renew next month. I'm requesting an expansion. 5,000 more seats. We haven't used the first 4,000. But this time we'll "drive adoption." Adoption means mandatory training. Training means a 45-minute webinar no one watches. But completion will be tracked. Completion is a metric. Metrics go in dashboards. Dashboards go in board presentations. Board presentations get me promoted. I'll be SVP by Q3. I still don't know what Copilot does. But I know what it's for. It's for showing we're "investing in AI." Investment means spending. Spending means commitment. Commitment means we're serious about the future. The future is whatever I say it is. As long as the graph goes up and to the right.
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