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Privacy Please: Daily Summaries Delivered
by A Problem Lounge Show
Welcome to "Privacy Please," a podcast for anyone who wants to know more about data privacy and security. Join your hosts Cam and Gabe as they talk to experts, academics, authors, and activists to break down complex privacy topics in a way that's easy to understand. In today's connected world, our personal information is constantly being collected, analyzed, and sometimes exploited. We believe everyone has a right to understand how their data is being used and what they can do to protect their privacy.
Latest Episodes
The most recent episodes — sign up to get AI-powered summaries of each one.
- 2 weeks ago9 min
S7, E275 - Choose Wisely: GigaWiper, Your New Delete Button & The Gold Bar Grift
Send us Fan Mail Full Show Notes This week on Privacy Please, Cam breaks down four stories that all come back to one theme: choice. GigaWiper — Microsoft researchers uncovered a new backdoor malware built from pieces of older malware families, giving attackers the ability to decide after they're already inside a network how they want to cause damage — from low-level disk wipes to fake ransomware with encryption keys that are never even saved. Multiple security firms are independently trackin...
- Jun 29, 202614 min
S7, E274 - Your Password Is Already For Sale
Send us Fan Mail Last year, every major outlet ran the same story: 16 billion passwords exposed. Apple. Google. Facebook. The largest breach in history. It was overblown. Security experts tore it apart within 48 hours. But here's the thing: the real story underneath that headline is actually scarier. And nobody covered it. It's called infostealer malware. It's been quietly running on millions of devices — stealing passwords, bypassing MFA, and feeding an underground credential economy that's ...
- Jun 4, 202624 min
S7, E273 - Inside Shiny Hunters And The New Era Of SaaS Breaches
Send us Fan Mail Gabe and I dig into Shiny Hunters and why the scariest cyberattacks now look like ordinary logins instead of dramatic break-ins. We map how credential theft, social engineering, and SaaS data exports turn basic security hygiene into the difference between a close call and a headline. • Shiny Hunters’ scale, loose structure, and why takedowns rarely stick • Why ransomware and extortion keep growing as a business model • How the tactics evolve from Microsoft ...
- May 23, 202616 min
S7, E272 - They Know What You Watched
Send us Fan Mail SHOW NOTES The Pornhub breach is being reported as a data story. It's actually a story about shame as a weapon. In December 2025, a hacker group called ShinyHunters claimed to have stolen 200 million records from Pornhub Premium users — including email addresses, locations, and intimate watch and search history. They sent extortion demands. The data was verified as real. In this episode of Privacy Please, Cameron Ivey breaks down: ✅ What was actually stolen — and why i...
- May 5, 202622 min
S7, E271 - One File to Rule Them All
Send us Fan Mail In this episode of Privacy Please, Cameron Ivey investigates Palantir Technologies — a data analytics company founded in 2003 with CIA backing that has quietly become embedded across nearly every major arm of the U.S. federal government. This week's investigation covers: The USDA Deal On April 22nd, the Department of Agriculture signed a $300 million blanket purchase agreement with Palantir to build "One Farmer, One File" — a unified digital profile for every American farmer....
- Apr 20, 202613 min
S7, E270 - The 40-Minute Hack That Stole the Blueprint for AI | The Mercor Breach
Send us Fan Mail A normal data breach steals names and passwords. This one may have stolen the recipe for building the world’s most powerful AI models, and it happened through software most people will never notice until it breaks. We follow the Mercor breach from the first warning signs to the moment poisoned Python packages hit PyPI and spread in minutes across systems that were set to auto-update. We walk through what Mercor actually does in the AI economy, especially RLHF (Reinforc...
- Apr 1, 202612 min
S7, E269 - You're the Teacher Now: How Companies Are Using Your Data to Build AI That Replaces You
Send us Fan Mail You already knew you were the product. But did you know you're also the teacher? Companies are quietly feeding your emails, your work decisions, your customer interactions, and your daily patterns into AI systems — systems designed to automate exactly what you do. And most people have no idea it's happening. In this episode of Privacy Please, we break down how it works, who's doing it, why your right to delete your own data is functionally broken in the AI era, and what you can actually do about it. What we cover: How "function creep" turns your data into AI training fuel without new consent The GitHub policy change that's happening right now — and how to opt out Why employees at Amazon, Google, and JPMorgan described training AI as "building your own coffin." The deletion problem — why you can't remove yourself from a trained model Practical steps to audit your tools and protect yourself today Links: GitHub opt-out: github.com/settings/copilot/features Khan v. Figma lawsuit: rainintelligence.com FTC on AI data practices: ftc.gov Check your state privacy rights: iapp.org/resources/article/us-state-privacy-legislation-tracker Delete old posts: redact.dev Privacy Please is part of The Problem Lounge network. 🌐 theproblemlounge.com 🎙️ Subscribe on Apple Podcasts, Spotify, or wherever you listen Support the show
- Mar 13, 202610 min
S7, E268 - AI Can Unmask Your Anonymous Account for $4 | Here's How
Send us Fan Mail Your anonymous account isn't anonymous anymore. Researchers just proved it costs $4 to find out who you are. In February 2026, a team from ETH Zurich and Anthropic published a paper that quietly ended the era of practical online anonymity. Their AI pipeline, using nothing but your posts, comments, and forum activity, correctly identified 67% of pseudonymous users from a pool of 89,000 candidates. No name. No photo. No metadata. Just your words. This episode breaks down exactly how it works, why it's different from every deanonymization scare before it, who's most at risk, and what you can actually do about it. In this episode: How the ESRC pipeline (Extract, Search, Reason, Calibrate) works Why previous anonymity attacks required structured data, and this one doesn't Why commercial AI safety guardrails didn't stop it What "practical obscurity" meant, and why it's gone Concrete steps to reduce your exposure today Links: Research paper: arxiv.org/abs/2602.16800 Delete your Reddit history: redact.dev Tor Project: torproject.org Signal: signal.org Privacy Please is part of The Problem Lounge network. 🌐 theproblemlounge.com 🎙️ Subscribe on Apple Podcasts, Spotify, or wherever you listen Support the show
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About Privacy Please
Welcome to "Privacy Please," a podcast for anyone who wants to know more about data privacy and security. Join your hosts Cam and Gabe as they talk to experts, academics, authors, and activists to break down complex privacy topics in a way that's easy to understand. In today's connected world, our personal information is constantly being collected, analyzed, and sometimes exploited. We believe everyone has a right to understand how their data is being used and what they can do to protect their privacy.
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Frequently Asked Questions
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It's a free AI-powered email that summarizes new episodes of Privacy Please as soon as they're published. You get the key takeaways, notable quotes, and links & mentions — all in a quick read.
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When a new episode drops, our AI transcribes and analyzes it, then generates a personalized summary tailored to your interests and profession. It's delivered to your inbox every morning.
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How often does Privacy Please release new episodes?
Privacy Please publishes biweekly. Our AI generates a summary within hours of each new episode.
What topics does Privacy Please cover?
Privacy Please covers topics including Comedy, News, Technology. Our AI identifies the specific themes in each episode and highlights what matters most to you.
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