There’s a bizarre thing happening online right now where everything is getting worse.

Your Google results have become so bad that you’ve likely typed what you’re looking for, plus the word “Reddit,” so you can find discussion from actual humans. If you didn’t take this route, you might get served AI results from Google Gemini, which once recommended that every person should eat “at least one small rock per day.” Your Amazon results are a slog, filled with products that have surreptitiously paid reviews. Your Facebook feed could be entirely irrelevant because the company decided years ago that you didn’t want to see what your friends posted, you wanted to see what brands posted, because brands pay Facebook, and you don’t, so brands are more important than your friends.

But, according to digital rights activist and award-winning author Cory Doctorow, this wave of online deterioration isn’t an accident—it’s a business strategy, and it can be summed up in a word he coined a couple of years ago: Enshittification.

Enshittification is the process by which an online platform—like Facebook, Google, or Amazon—harms its own services and products for short-term gain while managing to avoid any meaningful consequences, like the loss of customers or the impact of meaningful government regulation. It begins with an online platform treating new users with care, offering services, products, or connectivity that they may not find elsewhere. Then, the platform invites businesses on board that want to sell things to those users. This means businesses become the priority and the everyday user experience is hindered. But then, in the final stage, the platform also makes things worse for its business customers, making things better only for itself.

This is how a company like Amazon went from helping you find nearly anything you wanted to buy online to helping businesses sell you anything you wanted to buy online to making those businesses pay increasingly high fees to even be discovered online. Everyone, from buyers to sellers, is pretty much entrenched in the platform, so Amazon gets to dictate the terms.

Today, on the Lock and Code podcast with host David Ruiz, we speak with Doctorow about enshittification’s fast damage across the internet, how to fight back, and where we can lay blame for where it all started.

”Once these laws were established, the tech companies were able to take advantage of them. And today we have a bunch of companies that aren’t tech companies that are nevertheless using technology to rig the game in ways that the tech companies pioneered.”

Tune in today.

There’s an entire surveillance network popping up across the United States that has likely already captured your information, all for the non-suspicion of driving a car.

Automated License Plate Readers, or ALPRs, are AI-powered cameras that scan and store an image of every single vehicle that passes their view. They are mounted onto street lights, installed under bridges, disguised in water barrels, and affixed onto telephone poles, lampposts, parking signs, and even cop cars.

Once installed, these cameras capture a vehicle’s license plate number, along with its make, model, and color, and any identifying features, like a bumper sticker, or damage, or even sport trim options. Because nearly every ALPR camera has an associated location, these devices can reveal where a car was headed, and at what time, and by linking data from multiple ALPRs, it’s easy to determine a car’s daylong route and, by proxy, it’s owner’s daily routine.

This deeply sensitive information has been exposed in recent history.

In 2024, the US Cybersecurity and Information Security Agency discovered seven vulnerabilities in cameras made by Motorola Solutions, and at the start of 2025, the outlet Wired reported that more than 150 ALPR cameras were leaking their live streams.

But there’s another concern with ALPRs besides data security and potential vulnerability exploits, and that’s with what they store and how they’re accessed.

ALPRs are almost uniformly purchased and used by law enforcement. These devices have been used to help solve crime, but their databases can be accessed by police who do not live in your city, or county, or even state, and who do not need a warrant before making a search.

In fact, when police access the databases managed by one major ALPR manufacturer, named Flock, one of the few guardrails those police encounter is needing to type a single word in a basic text box. When Electronic Frontier Foundation analyzed 12 million searches made by police in Flock’s systems, they learned that police sometimes filled that text box with the word “protest,” meaning that police were potentially investigating activity that is protected by the First Amendment.

Today, on the Lock and Code podcast with host David Ruiz, we speak with Will Freeman, founder of the ALRP-tracking project DeFlock Me, about this growing tide of neighborhood surveillance and the flimsy protections afforded to everyday people.

“License plate readers are a hundred percent used to circumvent the Fourth Amendment because [police] don’t have to see a judge. They don’t have to find probable cause. According to the policies of most police departments, they don’t even have to have reasonable suspicion.”

Tune in today.

You can also find us on Apple Podcasts, Spotify, and whatever preferred podcast platform you use.

For all our cybersecurity coverage, visit Malwarebytes Labs at malwarebytes.com/blog.

Show notes and credits:

Intro Music: “Spellbound” by Kevin MacLeod (incompetech.com)

Licensed under Creative Commons: By Attribution 4.0 License

http://creativecommons.org/licenses/by/4.0/

Outro Music: “Good God” by Wowa (unminus.com)

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This is the story of the world’s worst scam and how it is being used to fuel entire underground economies that have the power to rival nation-states across the globe. This is the story of “pig butchering.”

“Pig butchering” is a violent term that is used to describe a growing type of online investment scam that has ruined the lives of countless victims all across the world. No age group is spared, nearly no country is untouched, and, if the numbers are true, with more than $6.5 billion stolen in 2024 alone, no scam might be more serious today, than this.

Despite this severity, like many types of online fraud today, most pig-butchering scams start with a simple “hello.”

Sent through text or as a direct message on social media platforms like X, Facebook, Instagram, or elsewhere, these initial communications are often framed as simple mistakes—a kind stranger was given your number by accident, and if you reply, you’re given a kind apology and a simple lure: “You seem like such a kind person… where are you from?”

Here, the scam has already begun. Pig butchers, like romance scammers, build emotional connections with their victims. For months, their messages focus on everyday life, from family to children to marriage to work.

But, with time, once the scammer believes they’ve gained the trust of their victim, they launch their attack: An investment “opportunity.”

Pig butchers tell their victims that they’ve personally struck it rich by investing in cryptocurrency, and they want to share the wealth. Here, the scammers will lead their victims through opening an entirely bogus investment account, which is made to look real through sham websites that are littered with convincing tickers, snazzy analytics, and eye-popping financial returns.

When the victims “invest” in these accounts, they’re actually giving money directly to their scammers. But when the victims log into their online “accounts,” they see their money growing and growing, which convinces many of them to invest even more, perhaps even until their life savings are drained.

This charade goes on as long as possible until the victims learn the truth and the scammers disappear. The continued theft from these victims is where “pig-butchering” gets its name—with scammers fattening up their victims before slaughter.

Today, on the Lock and Code podcast with host David Ruiz, we speak with Erin West, founder of Operation Shamrock and former Deputy District Attorney of Santa Clara County, about pig butchering scams, the failures of major platforms like Meta to stop them, and why this global crisis represents far more than just a few lost dollars.

“It’s really the most compelling, horrific, humanitarian global crisis that is happening in the world today.”

Tune in today.

You can also find us on Apple Podcasts, Spotify, and whatever preferred podcast platform you use.

For all our cybersecurity coverage, visit Malwarebytes Labs at malwarebytes.com/blog.

Show notes and credits:

Intro Music: “Spellbound” by Kevin MacLeod (incompetech.com)

Licensed under Creative Commons: By Attribution 4.0 License

http://creativecommons.org/licenses/by/4.0/

Outro Music: “Good God” by Wowa (unminus.com)

Listen up—Malwarebytes doesn't just talk cybersecurity, we provide it.

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It’s often said online that if a product is free, you’re the product, but what if that bargain was no longer true? What if, depending on the device you paid hard-earned money for, you still became a product yourself, to be measured, anonymized, collated, shared, or sold, often away from view?

In 2024, a consumer rights group out of the UK teased this new reality when it published research into whether people’s air fryers—seriously–might be spying on them.

By analyzing the associated Android apps for three separate air fryer models from three different companies, researchers learned that these kitchen devices didn’t just promise to make crispier mozzarella sticks, crunchier chicken wings, and flakier reheated pastries—they also wanted a lot of user data, from precise location to voice recordings from a user’s phone.

As the researchers wrote:

“In the air fryer category, as well as knowing customers’ precise location, all three products wanted permission to record audio on the user’s phone, for no specified reason.”

Bizarrely, these types of data requests are far from rare.

Today, on the Lock and Code podcast, we revisit a 2024 episode in which host David Ruiz tells three separate stories about consumer devices that somewhat invisibly collected user data and then spread it in unexpected ways. This includes kitchen utilities that sent data to China, a smart ring maker that published de-identified, aggregate data about the stress levels of its users, and a smart vacuum that recorded a sensitive image of a woman that was later shared on Facebook.

These stories aren’t about mass government surveillance, and they’re not about spying, or the targeting of political dissidents. Their intrigue is elsewhere, in how common it is for what we say, where we go, and how we feel, to be collected and analyzed in ways we never anticipated.

Tune in today.

You can also find us on Apple Podcasts, Spotify, and whatever preferred podcast platform you use.

For all our cybersecurity coverage, visit Malwarebytes Labs at malwarebytes.com/blog.

Show notes and credits:

Intro Music: “Spellbound” by Kevin MacLeod (incompetech.com)

Licensed under Creative Commons: By Attribution 4.0 License

http://creativecommons.org/licenses/by/4.0/

Outro Music: “Good God” by Wowa (unminus.com)

Listen up—Malwarebytes doesn't just talk cybersecurity, we provide it.

Protect yourself from online attacks that threaten your identity, your files, your system, and your financial well-being with our exclusive offer for Malwarebytes Premium for Lock and Code listeners.

Everything’s easier with AI… except having to correct it.

In just the three years since OpenAI released ChatGPT, not only has onlife life changed at home—it’s also changed at work. Some of the biggest software companies today, like Microsoft and Google, are forwarding a vision of an AI-powered future where people don’t write their own emails anymore, or make their own slide decks for presentations, or compile their own reports, or even read their own notifications, because AI will do it for them.

But it turns out that offloading this type of work onto AI has consequences.

In September, a group of researchers from Stanford University and BetterUp Labs published findings from an ongoing study into how AI-produced work impacts the people who receive that work. And it turns out that the people who receive that work aren’t its biggest fans, because it it’s not just work that they’re having to read, review, and finalize. It is, as the researchers called it, “workslop.”

Workslop is:

“AI generated work content that masquerades as good work, but lacks the substance to meaningfully advance a given task. It can appear in many different forms, including documents, slide decks, emails, and code. It often looks good, but is overly long, hard to read, fancy, or sounds off.”

Far from an indictment on AI tools in the workplace, the study instead reveals the economic and human costs that come with this new phenomenon of “workslop.” The problem, according to the researchers, is not that people are using technology to help accomplish tasks. The problem is that people are using technology to create ill-fitting work that still requires human input, review, and correction down the line.

“The insidious effect of workslop is that it shifts the burden of the work downstream, requiring the receiver to interpret, correct, or redo the work,” the researchers wrote.

Today, on the Lock and Code podcast with host David Ruiz, we speak with Dr. Kristina Rapuano, senior research scientist at BetterUp Labs, about AI tools in the workplace, the potential lost productivity costs that come from “workslop,” and the sometimes dismal opinions that teammates develop about one another when receiving this type of work.

“This person said, ‘Having to read through workshop is demoralizing. It takes away time I could be spending doing my job because someone was too lazy to do theirs.'”

Tune in today.

You can also find us on Apple Podcasts, Spotify, and whatever preferred podcast platform you use.

For all our cybersecurity coverage, visit Malwarebytes Labs at malwarebytes.com/blog.

Show notes and credits:

Intro Music: “Spellbound” by Kevin MacLeod (incompetech.com)

Licensed under Creative Commons: By Attribution 4.0 License

http://creativecommons.org/licenses/by/4.0/

Outro Music: “Good God” by Wowa (unminus.com)

Listen up—Malwarebytes doesn't just talk cybersecurity, we provide it.

Protect yourself from online attacks that threaten your identity, your files, your system, and your financial well-being with our exclusive offer for Malwarebytes Premium for Lock and Code listeners.

In the final, cold winter months of the year, ChatGPT could be heating up.

On October 14, OpenAI CEO Sam Altman said that the “restrictions” that his company previously placed on their flagship product, ChatGPT, would be removed, allowing, perhaps, for “erotica” in the future.

“We made ChatGPT pretty restrictive to make sure we were being careful with mental health issues,” Altman wrote on the platform X. “We realize this made it less useful/enjoyable to many users who had no mental health problems, but given the seriousness of the issue we wanted to get this right.”

This wasn’t the first time that OpenAI or its executive had addressed mental health.

On August 26, OpenAI published a blog titled “Helping people when they need it most,” which explored new protections for users, including stronger safeguards for long conversations, better recognition of people in crisis, and easier access to outside emergency services and even family and friends. The blog alludes to “recent heartbreaking cases of people using ChatGPT in the midst of acute crises,” but it never explains what, explicitly, that means.

But on the very same day the blog was posted, OpenAI was sued for the alleged role that ChatGPT played in the suicide of a 16-year-old boy. According to chat logs disclosed in the lawsuit, the teenager spoke openly to the AI chatbot about suicide, he shared that he wanted to leave a noose in his room, and he even reportedly received an offer to help write a suicide note.

Bizarrely, this tragedy plays a role in the larger story, because it was Altman himself who tied the company’s mental health campaign to its possible debut of erotic content.

“In December, as we roll out age-gating more fully and as part of our ‘treat adult users like adults’ principle, we will allow even more, like erotica for verified adults.”

What “erotica” entails is unclear, but one could safely assume it involves all the capabilities currently present in ChatGPT, through generative chat, of course, but also image generation.  

Today, on the Lock and Code podcast with host David Ruiz, we speak with Deb Donig, on faculty at the UC Berkeley School of Information, about the ethics of AI erotica, the possible accountability that belongs to users and to OpenAI, and why intimacy with an AI-power chatbot feels so strange.

“A chat bot offers, we might call it, ‘intimacy’s performance,’ without any of its substance, so you get all of the linguistic markers of connection, but no possibility for, for example, rejection. That’s part of the human experience of a relationship.”

Tune in today.

You can also find us on Apple Podcasts, Spotify, and whatever preferred podcast platform you use.

For all our cybersecurity coverage, visit Malwarebytes Labs at malwarebytes.com/blog.

Show notes and credits:

Intro Music: “Spellbound” by Kevin MacLeod (incompetech.com)

Licensed under Creative Commons: By Attribution 4.0 License

http://creativecommons.org/licenses/by/4.0/

Outro Music: “Good God” by Wowa (unminus.com)

Listen up—Malwarebytes doesn't just talk cybersecurity, we provide it.

Protect yourself from online attacks that threaten your identity, your files, your system, and your financial well-being with our exclusive offer for Malwarebytes Premium for Lock and Code listeners.

Google is everywhere in our lives. It’s reach into our data extends just as far.

After investigating how much data Facebook had collected about him in his nearly 20 years with the platform, Lock and Code host David Ruiz had similar questions about the other Big Tech platforms in his life, and this time, he turned his attention to Google.

Google dominates much of the modern web. It has a search engine that handles billions of requests a day. Its tracking and metrics service, Google Analytics, is embedded into reportedly 10s of millions of websites. Its Maps feature not only serves up directions around the world, it also tracks traffic patterns across countless streets, highways, and more. Its online services for email (Gmail), cloud storage (Google Drive), and office software (Google Docs, Sheets, and Slides) are household names. And it also runs the most popular web browser in the world, Google Chrome, and the most popular operating system in the world, Android.

Today, on the Lock and Code podcast, Ruiz explains how he requested his data from Google and what he learned not only about the company, but about himself, in the process. That includes the 142,729 items in his Gmail inbox right now, along with the 8,079 searches he made, 3,050 related websites he visited, and 4,610 YouTube videos he watched in just the past 18 months. It also includes his late-night searches for worrying medical symptoms, his movements across the US as his IP address was recorded when logging into Google Maps, his emails, his photos, his notes, his old freelance work as a journalist, his outdated cover letters when he was unemployed, his teenage-year Google Chrome bookmarks, his flight and hotel searches, and even the searches he made within his own Gmail inbox and his Google Drive.

After digging into the data for long enough, Ruiz came to a frightening conclusion: Google knows whatever the hell it wants about him, it just has to look.

But Ruiz wasn’t happy to let the company’s access continue. So he has a plan.

”I am taking steps to change that [access] so that the next time I ask, “What does Google know about me?” I can hopefully answer: A little bit less.”

Tune in today.

You can also find us on Apple Podcasts, Spotify, and whatever preferred podcast platform you use.

For all our cybersecurity coverage, visit Malwarebytes Labs at malwarebytes.com/blog.

Show notes and credits:

Intro Music: “Spellbound” by Kevin MacLeod (incompetech.com)

Licensed under Creative Commons: By Attribution 4.0 License

http://creativecommons.org/licenses/by/4.0/

Outro Music: “Good God” by Wowa (unminus.com)

Listen up—Malwarebytes doesn't just talk cybersecurity, we provide it.

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“Connection” was the promise—and goal—of much of the early internet. No longer would people be separated from vital resources and news that was either too hard to reach or made simply inaccessible by governments. No longer would education be guarded behind walls both physical and paid. And no longer would your birthplace determine so much about the path of your life, as the internet could connect people to places, ideas, businesses, collaborations, and agency.

Somewhere along the line though, “connection” got co-opted. The same platforms that brought billions of people together—including Facebook, Twitter, Instagram, TikTok, and Snapchat—started to divide them for profit. These companies made more money by showing people whatever was most likely to keep them online, even if it upset them. More time spent on the platfrom meant more likelihood of encountering ads which meant more advertising revenue for Big Tech.

Today, these same platforms are now symbols of some of the worst aspects of being online. Nation-states have abused the platforms to push disinformation campaigns. An impossible sense of scale allows gore and porn and hate speech to slip by even the best efforts at content moderation. And children can be exposed to bullying, peer pressure, and harassment.

So, what would it take to make online connection a good thing?

Today, on the Lock and Code podcast with host David Ruiz, we speak with Rabble—an early architect of social media, Twitter’s first employee, and host of the podcast Revolution.Social—about what good remains inside social media and what steps are being taken to preserve it.

“ I don’t think that what we’re seeing with social media is so much a set of new things that are disasters that are rising up from this Pandora’s box… but rather they’re all things that existed in society and now they’re not all kept locked away. So we can see them and we have to address them now.”

Tune in today.

There’s more about you online than you know.

The company Acxiom, for example, has probably determined whether you’re a heavy drinker, or if you’re overweight, or if you smoke (or all three). The same company has also probably estimated—to the exact dollar—the amount you spend every year on dining out, donating to charities, and traveling domestically. Another company Experian, has probably made a series of decisions about whether you are “Likely,” “Unlikely,” “Highly Likely,” etc., to shop at a mattress store, visit a theme park, or frequent the gym.

This isn’t the data most people think about when considering their online privacy. Yes, names, addresses, phone numbers, and age are all important and potentially sensitive, and yes, there’s a universe of social media posts, photos, videos, and comments that are likely at the harvesting whim of major platforms to collect, package, and sell access to for targeted advertising.

But so much of the data that you leave behind online has nothing to do with what you willingly write, post, share, or say. Instead, it is data that is collected from online and offline interactions, like the items you add in a webpage’s shopping cart, the articles you read, the searches you make, and the objects you buy at a physical store.

Importantly, it is also data that is very hard to get rid of.

Today, on the Lock and Code podcast with host David Ruiz, we speak with Peter Dolanjski, director of product at DuckDuckGo, about why the internet is so hungry for your data, how parents can help protect the privacy of their children, and whether it is pointless to try to “disappear” online.

“It’s not futile… Taking steps now, despite the fact that you already have information out there, will help you into the future.”

Tune in today.

You can also find us on Apple Podcasts, Spotify, and whatever preferred podcast platform you use.

For all our cybersecurity coverage, visit Malwarebytes Labs at malwarebytes.com/blog.

Show notes and credits:

Intro Music: “Spellbound” by Kevin MacLeod (incompetech.com)

Licensed under Creative Commons: By Attribution 4.0 License

http://creativecommons.org/licenses/by/4.0/

Outro Music: “Good God” by Wowa (unminus.com)

Listen up—Malwarebytes doesn't just talk cybersecurity, we provide it.

Protect yourself from online attacks that threaten your identity, your files, your system, and your financial well-being with our exclusive offer for Malwarebytes Premium for Lock and Code listeners.

In the late 2010s, a group of sheriffs out of Pasco County, Florida, believed they could predict crime. The Sheriff’s Department there had piloted a program called “Intelligence-Led Policing” and the program would allegedly analyze disparate points of data to identify would-be criminals.

But in reality, the program didn’t so much predict crime, as it did make criminals out of everyday people, including children. 

High schoolers’ grades were fed into the Florida program, along with their attendance records and their history with “office discipline.” And after the “Intelligence-Led Policing” service analyzed the data, it instructed law enforcement officers on who they should pay visit to, who they should check in on, and who they should pester.

As reported by The Tampa Bay Times in 2020:

“They swarm homes in the middle of the night, waking families and embarrassing people in front of their neighbors. They write tickets for missing mailbox numbers and overgrown grass, saddling residents with court dates and fines. They come again and again, making arrests for any reason they can.One former deputy described the directive like this: ‘Make their lives miserable until they move or sue.’”

Predictive policing can sound like science fiction, but it is neither scientific nor is it confined to fiction.

Police and sheriff’s departments across the US have used these systems to plug broad varieties of data into algorithmic models to try and predict not just who may be a criminal, but where crime may take place. Historical crime data, traffic information, and even weather patterns are sometimes offered up to tech platforms to suggest where, when, and how forcefully police units should be deployed.

And when the police go to those areas, they often find and document minor infractions that, when reported, reinforce the algorithmic analysis that an area is crime-ridden, even if those crimes are, as the Tampa Bay Times investigation found, a teenager smoking a cigarette, or stray trash bags outside a home.

Today, on the Lock and Code podcast with host David Ruiz, we speak with Emily Galvin-Almanza, cofounder of Partners for Justice and author of the upcoming book “The Price of Mercy,” about predictive policing, its impact on communities, and the dangerous outcomes that might arise when police offload their decision-making to data.

“ I am worried about anything that a data broker can sell, they can sell to a police department, who can then feed that into an algorithmic or AI predictive policing system, who can then use that system—based on the purchases of people in ‘Neighborhood A’—to decide whether to hyper-police ‘Neighborhood A.’”

Tune in today.

You can also find us on Apple Podcasts, Spotify, and whatever preferred podcast platform you use.

For all our cybersecurity coverage, visit Malwarebytes Labs at malwarebytes.com/blog.

Show notes and credits:

Intro Music: “Spellbound” by Kevin MacLeod (incompetech.com)

Licensed under Creative Commons: By Attribution 4.0 License

http://creativecommons.org/licenses/by/4.0/

Outro Music: “Good God” by Wowa (unminus.com)

Listen up—Malwarebytes doesn't just talk cybersecurity, we provide it.

Protect yourself from online attacks that threaten your identity, your files, your system, and your financial well-being with our exclusive offer for Malwarebytes Premium for Lock and Code listeners.