If you weren’t taking deepfakes seriously before, it’s too late now to ignore them.
According to new research from Malwarebytes, one in three people who use AI every day said it’s okay to generate pornography of people without their consent.
Nearly 10 years ago, “deepfake” technology provided hobbyists and film editors with artificial intelligence (AI) tools to swap the face of one person onto the body of another. In its infancy, this technology brought silly film experiments like swapping Tom Cruise in Mission Impossible with Keanu Reeves. Today, this same technology produces something far more harmful—fake nude images of teenagers.
On the Lock and Code podcast today with host David Ruiz, we are re-visiting an interview from 2024, in which we spoke with a lawyer named David Chiu about his lawsuit against 16 deepfake nude generation websites.
The websites named in that lawsuit often needed just one image of a person to generate fake pornography. And while nearly everyone has at least one image of themselves online, even if they had hundreds, the path towards deletion is somewhat understood—start by deactivating and deleting popular social media accounts. But for teenagers today, raised mostly online, and who share images directly with friends and boyfriends and girlfriends and exes, it’s likely impossible to remove every visual trace of themselves. Also, they shouldn’t have to face this problem alone.
The Lock and Code podcast frequently discusses structural problems that require individual management. You have to skirt corporate data collection. You have to find the automated license plate readers in your hometown. You have to review every single message you get with a certain antagonism, to guard yourself against scams.
So, it’s rare to encounter a solution that benefits more than one person.
Chiu serves as the City Attorney for San Francisco, which means his department can file a lawsuit on behalf of not just the people of San Francisco, but also California, and that’s what his team did in going after the deepfake websites.
Since then, Chiu’s department has shut down 10 deepfake nude websites, and it received a settlement agreement from a company called Briver LLC to no longer operate any website that creates nonconsensual deepfake pornography.
And, as California goes, so goes the nation.
In May of last year, the Take It Down Act became effective as law in the United States, which criminalizes “revenge porn” and AI-generated nonconsensual intimate imagery. The law is not perfect but so far it is being used as intended. Last month, two men in the US were among the first to be charged with violating the Take It Down act for allegedly creating deepfake nudes that, according to the AP, “included both celebrities as well as private women, including recent high school graduates.”
Today, we revisit our conversation with San Francisco City Attorney David Chiu about the important fight against deepfake porn and the clear threat that his department found against the public.
“At least one of these websites specifically promotes the non-consensual nature of this. So, and I’ll just quote, ‘Imagine wasting time taking her out on dates when you can just use website X to get her nudes.'”
If you weren’t taking deepfakes seriously before, it’s too late now to ignore them.
According to new research from Malwarebytes, one in three people who use AI every day said it’s okay to generate pornography of people without their consent.
Nearly 10 years ago, “deepfake” technology provided hobbyists and film editors with artificial intelligence (AI) tools to swap the face of one person onto the body of another. In its infancy, this technology brought silly film experiments like swapping Tom Cruise in Mission Impossible with Keanu Reeves. Today, this same technology produces something far more harmful—fake nude images of teenagers.
On the Lock and Code podcast today with host David Ruiz, we are re-visiting an interview from 2024, in which we spoke with a lawyer named David Chiu about his lawsuit against 16 deepfake nude generation websites.
The websites named in that lawsuit often needed just one image of a person to generate fake pornography. And while nearly everyone has at least one image of themselves online, even if they had hundreds, the path towards deletion is somewhat understood—start by deactivating and deleting popular social media accounts. But for teenagers today, raised mostly online, and who share images directly with friends and boyfriends and girlfriends and exes, it’s likely impossible to remove every visual trace of themselves. Also, they shouldn’t have to face this problem alone.
The Lock and Code podcast frequently discusses structural problems that require individual management. You have to skirt corporate data collection. You have to find the automated license plate readers in your hometown. You have to review every single message you get with a certain antagonism, to guard yourself against scams.
So, it’s rare to encounter a solution that benefits more than one person.
Chiu serves as the City Attorney for San Francisco, which means his department can file a lawsuit on behalf of not just the people of San Francisco, but also California, and that’s what his team did in going after the deepfake websites.
Since then, Chiu’s department has shut down 10 deepfake nude websites, and it received a settlement agreement from a company called Briver LLC to no longer operate any website that creates nonconsensual deepfake pornography.
And, as California goes, so goes the nation.
In May of last year, the Take It Down Act became effective as law in the United States, which criminalizes “revenge porn” and AI-generated nonconsensual intimate imagery. The law is not perfect but so far it is being used as intended. Last month, two men in the US were among the first to be charged with violating the Take It Down act for allegedly creating deepfake nudes that, according to the AP, “included both celebrities as well as private women, including recent high school graduates.”
Today, we revisit our conversation with San Francisco City Attorney David Chiu about the important fight against deepfake porn and the clear threat that his department found against the public.
“At least one of these websites specifically promotes the non-consensual nature of this. So, and I’ll just quote, ‘Imagine wasting time taking her out on dates when you can just use website X to get her nudes.'”
In the United States today, you can have your bank account closed, your credit cards cancelled, and your online payments revoked for any number of crimes, like funding terrorism, engaging in money laundering, or violating sanctions.
Sensible, right? Well, you can also face financial ruin for teaching poetry.
That’s what seemingly happened to a Persian poetry teacher from Detroit whose accounts were flagged for “sanctions violations” because his students wrote “Persian classes” in their Venmo memos. There’s also the story about the naked yoga practitioners who lost their payment processor for 60 days, forced to rebuild a subscriber list from scratch. And we can’t forget the San Diego cannabis journalist cut off from Stripe—and from a paid Substack newsletter—because of the payment platform’s rules that prohibit the promotion of the sale of cannabis.
This is “financial censorship,” and it often happens when a bank, credit card provider, or payment app decides that a customer is too risky to serve. But “risky” doesn’t always mean “illegal,” and when a major financial institution errs towards caution about what a customer is saying, advocating for, representing, or publishing, a lot of innocent people can be hurt in the process.
That’s what the digital rights activist Rainey Reitman learned in writing “Transaction Denied: Big Finance’s Power to Punish Speech.” As Reitman explained about these hugely impactful decisions:
“Even if they are well-intentioned, the financial systems can end up pulling in a lot of people that are not the actual target… Sometimes we talk about this as dolphins in the fishing lines.”
These decisions are difficult to fight, frustratingly opaque, and nearly impossible to reverse. Compounding the problem is that that there aren’t enough alternatives available for the financially censored to easily regain their freedom.
The reality for hundreds of millions of people in this country is that about a dozen companies control all their finances. People mostly bank with Chase, or Bank of America, or Citigroup, or Wells Fargo. They mostly use credit cards assigned by Visa, MasterCard, American Express, or Capital One. And they mostly send money to one another and to small businesses using services like PayPal, Venmo, Cash app, and Square.
For most people, these companies are supposed to operate in the background of their lives, providing reliable, secure financing to sustain and manage their livelihoods. But in practice, these companies can become quite interested in what you say online, what payments you receive each month, and the locations those payments arrived from.
Today, on the Lock and Code podcast with host David Ruiz, we speak with Reitman—who is also the president and a co-founder of the Freedom of the Press Foundation—about the real stories of those who have been financially censored, why financial companies cut off customers for legal speech, and how a single company’s decision can create cascading consequences that feel impossible to fight.
“They’d be locked out of Venmo, then they’d be locked out of PayPal—which is connected to Venmo—and then they’d suddenly lose their Chase Bank account. You could see that in a lot of instances, losing one form of access to the financial system, it could result in a pattern where they would be losing access repeatedly.”
In the United States today, you can have your bank account closed, your credit cards cancelled, and your online payments revoked for any number of crimes, like funding terrorism, engaging in money laundering, or violating sanctions.
Sensible, right? Well, you can also face financial ruin for teaching poetry.
That’s what seemingly happened to a Persian poetry teacher from Detroit whose accounts were flagged for “sanctions violations” because his students wrote “Persian classes” in their Venmo memos. There’s also the story about the naked yoga practitioners who lost their payment processor for 60 days, forced to rebuild a subscriber list from scratch. And we can’t forget the San Diego cannabis journalist cut off from Stripe—and from a paid Substack newsletter—because of the payment platform’s rules that prohibit the promotion of the sale of cannabis.
This is “financial censorship,” and it often happens when a bank, credit card provider, or payment app decides that a customer is too risky to serve. But “risky” doesn’t always mean “illegal,” and when a major financial institution errs towards caution about what a customer is saying, advocating for, representing, or publishing, a lot of innocent people can be hurt in the process.
That’s what the digital rights activist Rainey Reitman learned in writing “Transaction Denied: Big Finance’s Power to Punish Speech.” As Reitman explained about these hugely impactful decisions:
“Even if they are well-intentioned, the financial systems can end up pulling in a lot of people that are not the actual target… Sometimes we talk about this as dolphins in the fishing lines.”
These decisions are difficult to fight, frustratingly opaque, and nearly impossible to reverse. Compounding the problem is that that there aren’t enough alternatives available for the financially censored to easily regain their freedom.
The reality for hundreds of millions of people in this country is that about a dozen companies control all their finances. People mostly bank with Chase, or Bank of America, or Citigroup, or Wells Fargo. They mostly use credit cards assigned by Visa, MasterCard, American Express, or Capital One. And they mostly send money to one another and to small businesses using services like PayPal, Venmo, Cash app, and Square.
For most people, these companies are supposed to operate in the background of their lives, providing reliable, secure financing to sustain and manage their livelihoods. But in practice, these companies can become quite interested in what you say online, what payments you receive each month, and the locations those payments arrived from.
Today, on the Lock and Code podcast with host David Ruiz, we speak with Reitman—who is also the president and a co-founder of the Freedom of the Press Foundation—about the real stories of those who have been financially censored, why financial companies cut off customers for legal speech, and how a single company’s decision can create cascading consequences that feel impossible to fight.
“They’d be locked out of Venmo, then they’d be locked out of PayPal—which is connected to Venmo—and then they’d suddenly lose their Chase Bank account. You could see that in a lot of instances, losing one form of access to the financial system, it could result in a pattern where they would be losing access repeatedly.”
In May of last year, a warning about AI came from somewhere unexpected: The Auschwitz-Birkenau State Museum.
Posting publicly on social media, the museum warned about a Facebook account using generative AI to create fake images of people who died in the Holocaust. Despite using AI to generate fake images, the people in said images were sometimes real. They had real names, birthplaces, and stories of deportation that the Auschwitz-Birkenau State Museum itself had shared before. They had real faces captured in real surviving photographs, which were likely abused to generate the false images.
In other words, someone, or some team of people online, was deepfaking the Holocaust.
“These are not real photos of the victims. They are digital inventions, often stylized or sanitized, that risk turning remembrance into fictionalized performance. The history of Auschwitz is a well-documented story. Altering its visual record with AI imagery introduces distortion, no matter the intent.”
Months later, the public found out what that intent was: money.
A BBC investigation found an international network of Facebook accounts posting AI-generated images to earn money from those images’ potential virality. It’s a problem sometimes referred to as “AI slop” but it comes with a major incentive. When accounts that make these kinds of images are invited to Facebook’s content monetization program, they can make $1,000 a month for posting anything that gets clicks.
And on Facebook, the BBC found, that means several accounts posting AI-generated images about the Holocaust. As the BBC reported:
“AI spammers have posted fake images purporting to be from inside [Auschwitz], such as a prisoner playing a violin or lovers meeting at the boundaries of fences—attracting tens of thousands of likes and shares.”
The economics of lying are concrete today. People can use AI to make fake images that make people feel good about terrible things or feel scared about untrue things, and they can make money until shut down by the Big Tech platforms themselves, which, in this case, only happened because of the BBC’s investigation. In fact, it’s that type of inaction from social media platforms that compelled the German government and multiple Holocaust memorial institutions to send an open letter earlier this year that asked for better controls and restrictions against this type of content.
As the signatories warned in their letter, the economic appeal for these accounts to distort history is too high a risk to allow. You can read the full letter here.
Today, on the Lock and Code podcast with host David Ruiz, we speak with Clara Mansfeld, a historian working on digital communications at one of the institutions signed onto the open letter—the Foundation of Hamburg Memorials and Learning Centers Commemorating the Victims of Nazi Crimes. In their conversation, Mansfeld discusses digital access to history, the manipulation of factual records through AI-generated imagery, and the threat that society faces when it becomes harder to evaluate the truth.
“What happens when the first thought we have with every historical image is, ‘Is that even real or is that AI?’ I don’t think we have really grasped what that means for us as a society.”
In May of last year, a warning about AI came from somewhere unexpected: The Auschwitz-Birkenau State Museum.
Posting publicly on social media, the museum warned about a Facebook account using generative AI to create fake images of people who died in the Holocaust. Despite using AI to generate fake images, the people in said images were sometimes real. They had real names, birthplaces, and stories of deportation that the Auschwitz-Birkenau State Museum itself had shared before. They had real faces captured in real surviving photographs, which were likely abused to generate the false images.
In other words, someone, or some team of people online, was deepfaking the Holocaust.
“These are not real photos of the victims. They are digital inventions, often stylized or sanitized, that risk turning remembrance into fictionalized performance. The history of Auschwitz is a well-documented story. Altering its visual record with AI imagery introduces distortion, no matter the intent.”
Months later, the public found out what that intent was: money.
A BBC investigation found an international network of Facebook accounts posting AI-generated images to earn money from those images’ potential virality. It’s a problem sometimes referred to as “AI slop” but it comes with a major incentive. When accounts that make these kinds of images are invited to Facebook’s content monetization program, they can make $1,000 a month for posting anything that gets clicks.
And on Facebook, the BBC found, that means several accounts posting AI-generated images about the Holocaust. As the BBC reported:
“AI spammers have posted fake images purporting to be from inside [Auschwitz], such as a prisoner playing a violin or lovers meeting at the boundaries of fences—attracting tens of thousands of likes and shares.”
The economics of lying are concrete today. People can use AI to make fake images that make people feel good about terrible things or feel scared about untrue things, and they can make money until shut down by the Big Tech platforms themselves, which, in this case, only happened because of the BBC’s investigation. In fact, it’s that type of inaction from social media platforms that compelled the German government and multiple Holocaust memorial institutions to send an open letter earlier this year that asked for better controls and restrictions against this type of content.
As the signatories warned in their letter, the economic appeal for these accounts to distort history is too high a risk to allow. You can read the full letter here.
Today, on the Lock and Code podcast with host David Ruiz, we speak with Clara Mansfeld, a historian working on digital communications at one of the institutions signed onto the open letter—the Foundation of Hamburg Memorials and Learning Centers Commemorating the Victims of Nazi Crimes. In their conversation, Mansfeld discusses digital access to history, the manipulation of factual records through AI-generated imagery, and the threat that society faces when it becomes harder to evaluate the truth.
“What happens when the first thought we have with every historical image is, ‘Is that even real or is that AI?’ I don’t think we have really grasped what that means for us as a society.”
How Nations Hack, Why Attribution Fails, and What AI Changes
Executive Summary: Code War author Allie Mellen, argues that cyberwarfare must be understood through a human and geopolitical lens to close the knowledge gap between the security community and the public.
Disclaimer:
This post reflects the perspectives shared in the book Code War: How Nations Hack, Spy, and Shape the Digital Battlefield, and does not represent the views of the publisher of this blog.
The summer of 1983, President Reagan watched WarGames at Camp David and couldn't get it out of his head. A week later, he walked into a White House meeting with cabinet members and Congress and launched into a detailed plot summary of a Matthew Broderick movie about a teenager who nearly hacks the world into nuclear war. The room full of defense experts sat uncomfortably, suppressing smirks. Then Reagan turned to General John Vessey, Chairman of the Joint Chiefs, and asked if something like that could actually happen.
Vessey came back a week later with an answer: "Mr. President, the problem is much worse than you think."
Fifteen months after that, Reagan signed a classified presidential directive titled "National Policy on Telecommunications and Automated Information Systems Security" – the first federal policy of its kind. A movie had done what years of expert warnings hadn't: It made the most powerful person in the world stop and ask the right question.
Allie Mellen, author of Code War: How Nations Hack, Spy, and Shape the Digital Battlefield, loves to tell this story, and it captures exactly why she wrote the book. In a conversation recorded at RSA 2025, Mellen joined Threat Vector host, David Moulton, to talk about nation-state threats, attribution pitfalls, and why the security industry's biggest problem isn't technical.
"They're human stories, and if we can communicate them that way to the general public, then we'll get more people interested in cybersecurity, invested in cybersecurity, and invested in protecting their data."
That gap, between what the security community understands and what everyone else grasps, is the core problem Mellen set out to solve. And in today's geopolitical moment, closing it has never been more urgent.
Every Nation Hacks Differently
One of the central arguments in Code War is that you can't understand a nation's cyber behavior without understanding its history, doctrine and social contract. China, Russia, Iran, North Korea and the U.S. each approach offensive and defensive cyber operations from completely different starting points, and those differences matter enormously to defenders.
China operates with patience. Its attacks tend to be low and slow, focused on long-term espionage rather than loud disruption. But that changes sharply in its own region, where operations targeting Taiwan are aggressive and relentless. Russia, by contrast, is bombastic; they want you to know it was Russia. Its influence operations have been some of the most effective in modern history, studied and imitated by Iran and others.
Interestingly, the very system China built to protect itself has become a liability in one specific domain. Because Chinese operators live behind the Great Firewall, without access to western social media, they lack the cultural fluency that makes Russian disinformation so effective. "They try to use memes, but it's like ‘uncanny valley’," Mellen explains. "They just slightly miss every time and so it doesn't go viral." The walled garden that gives China control over its own population makes it harder to manipulate everyone else's.
Attribution Is a Geopolitical Tool, Not Just a Technical One
Mellen is careful about attribution, and she wants defenders to be too. The standard technical signals (coding language, infrastructure patterns, operational hours) are necessary but not sufficient. Nation-states, especially the U.S., have developed tools specifically designed to mimic other actors' signatures. AI will make that problem significantly worse.
But the bigger issue is motivation. Mellen walks through a case from the Olympics where an attack was initially attributed to North Korea, even though North Korea was actively trying to normalize relations at the time by sending Kim Jong Un's sister to the games. The actual perpetrator was Russian, using a false flag to obscure its involvement. The lesson: Attribution requires asking not just "who has the technical capability?" but "who has the motive right now, given everything happening geopolitically?"
The pitfalls are real:
Tools once used exclusively by intelligence agencies are now publicly available, making code signatures unreliable.
Working-hours analysis is easy to spoof, especially for sophisticated actors.
Government-controlled research in adversarial nations can deliberately skew attribution findings.
False flag operations are increasingly sophisticated and harder to disentangle.
Why Your Data Is a Geopolitical Asset
One of the more powerful sections of the conversation centers on a question Mellen hears constantly: why would China care about my data?
Her answer cuts through the dismissiveness. These nations aren't collecting data out of idle curiosity. They're willing to constrain companies for it, invest billions in infrastructure for it, and in some cases, far worse. "Whether you wanna be involved in that system or not, you are involved in that system," she says. "And so you can either choose to take control of your information in that environment, or you can just pretend like it's not your problem."
The historical context she offers is striking. One of the driving forces behind GDPR in the EU was the collective memory of how Nazi Germany used data to target Jewish people during the Holocaust. Europe built privacy protections into law because it had seen what happens when governments gain unrestricted access to population data. That's not an abstract concern. It's a lesson written in history that the rest of the world is still catching up to.
AI Makes Everything Harder
Mellen isn't optimistic about the trajectory. Attribution is about to get much harder. Attacks are about to get much more dynamic. And AI is the reason for both.
She points to research on Chinese state-sponsored actors using AI to orchestrate attacks across the full kill chain, with only a couple of human checkpoints in the loop. The implication isn't just faster attacks. It's more adaptive malware that can adjust to different operating environments, more convincing disinformation that clears the cultural context bar, and reconnaissance-to-exploitation cycles that move faster than most defenders can process.
The constraints that have always slowed sophisticated attackers – understanding the operating system, identifying vulnerabilities, crafting exploits, mimicking attribution – all get easier with AI. All of that becomes more dynamic. And most enterprises, Mellen acknowledges, are not yet equipped to respond effectively.
The investment required is in the basics the industry has always struggled to get right, executed now at a pace and scale that demands automation and AI on the defensive side. Fighting AI with AI isn't a vendor talking point. It's the only math that works.
Your prices could be going up because of a little something that one group has started calling the “cyber tax.”
Not a “tax” in any regulatory sense of the word, this newly named “cyber tax” is instead a consequence of the growing number of cyberattacks on small businesses. According to the latest research from the Identity Theft Resource Center, 81% of small- and medium-sized businesses suffered a data breach, a security breach, or both, within the past year. And of those businesses, more than 50% of lost more than $250,000.
According to the most recent data from the US Federal Reserve, the median American family has just $8,000 in savings, meaning that a hit of $250,000 could bankrupt a family and turn their lives upside down. But there’s an interesting layer within this data—the median American family is quite similar to the median American business. In fact, they’re often the exact same person.
The local grocer, the nearby HVAC repair service, the avid cyclist who just opened a bike shop, and the tax professional, and physical therapist helping out neighbors are everyday individuals and family members. They do not have multimillion dollar corporations at their backs, supporting them with legal teams, insurance policies, and dedicated IT support teams.
A loss of $250,000, then, is a potential loss of their business. And to stay afloat, the Identity Theft Resource Center found, for the first time ever, that 38% decided to raise their prices.
“It was near 40% said ‘We actually had to raise prices—we had to pass this cost onto our customers,’” said Eva Velasquez, CEO of the Identity Theft Resource Center. “We’re now really seeing the long-term downstream effects of cyberattacks.”
As frustrating as the cyber tax can be, small businesses themselves are also facing a new wave of cyberattacks, from AI-powered phishing emails so convincing that small business owners can’t tell the legitimate from the illegitimate, to deepfake calls that impersonate the CEO of a three-person company, to supply-chain attacks that target small companies as a way to reach bigger ones.
Today, on the Lock and Code podcast with host David Ruiz, we speak with Velasquez about cybercrime’s impact on small businesses, the new threats being deployed because of AI, and what is necessary to protect business owners and their consumers.
“Great businesses with great protocols in place can still have a vulnerability exploited because this is what the cyber bad guys are doing all day long. They only have to be right once, whereas small business owners have to be right 100% of the time.”
Your prices could be going up because of a little something that one group has started calling the “cyber tax.”
Not a “tax” in any regulatory sense of the word, this newly named “cyber tax” is instead a consequence of the growing number of cyberattacks on small businesses. According to the latest research from the Identity Theft Resource Center, 81% of small- and medium-sized businesses suffered a data breach, a security breach, or both, within the past year. And of those businesses, more than 50% of lost more than $250,000.
According to the most recent data from the US Federal Reserve, the median American family has just $8,000 in savings, meaning that a hit of $250,000 could bankrupt a family and turn their lives upside down. But there’s an interesting layer within this data—the median American family is quite similar to the median American business. In fact, they’re often the exact same person.
The local grocer, the nearby HVAC repair service, the avid cyclist who just opened a bike shop, and the tax professional, and physical therapist helping out neighbors are everyday individuals and family members. They do not have multimillion dollar corporations at their backs, supporting them with legal teams, insurance policies, and dedicated IT support teams.
A loss of $250,000, then, is a potential loss of their business. And to stay afloat, the Identity Theft Resource Center found, for the first time ever, that 38% decided to raise their prices.
“It was near 40% said ‘We actually had to raise prices—we had to pass this cost onto our customers,’” said Eva Velasquez, CEO of the Identity Theft Resource Center. “We’re now really seeing the long-term downstream effects of cyberattacks.”
As frustrating as the cyber tax can be, small businesses themselves are also facing a new wave of cyberattacks, from AI-powered phishing emails so convincing that small business owners can’t tell the legitimate from the illegitimate, to deepfake calls that impersonate the CEO of a three-person company, to supply-chain attacks that target small companies as a way to reach bigger ones.
Today, on the Lock and Code podcast with host David Ruiz, we speak with Velasquez about cybercrime’s impact on small businesses, the new threats being deployed because of AI, and what is necessary to protect business owners and their consumers.
“Great businesses with great protocols in place can still have a vulnerability exploited because this is what the cyber bad guys are doing all day long. They only have to be right once, whereas small business owners have to be right 100% of the time.”
A dreadful thing happens far too often whenever an older adult falls for a scam: They get blamed for it. Not the scammers who lied and cheated their victim out of money. Not law enforcement for failing to recover funds. Not even the Big Tech companies that could have the most important role in protecting people online—and which, it turns out, knowingly bring in revenue every year from fraud.
Instead, it is the older adults themselves whose stories are often shirked aside because of a mix of ageism and denial. Allegedly left behind by technology, only an octogenarian would hand their password over in a phishing scheme, or open an email attachment from a stranger, or send money to a fake charity online. Everyone else, everyone else believes, is too savvy for the same.
The data disagrees.
When Malwarebytes studied this last year, it found that, depending on the type of scam—especially for things like “sextortion”—younger individuals were far more likely to report falling victim. Further, digging into data from the US Federal Trade Commission revealed entirely separate patterns. For example, while Americans between the ages of 80 and 89 reported the highest median loss due to fraud in 2024, they also made up the smallest share of their population to report a loss at all. And in 2025, that same group represented the smallest share of reported identity theft, a crime far more likely to be reported by people between 30 and 39.
Questions about who reports what crimes at what rate are valid to explore, but it’s important to see the big picture: Americans lost at least $15.9 billion to fraud last year. Protecting older adults is actually about protecting everyone, and that’s because modern scams don’t arrive only where people over 70 spend time. They arrive where we all are, which is online. They come through endless text messages, they slide into social media DMs, and they prey on things any of us can be—a widow, a divorcee, or simply a lonely person.
According to Marti DeLiema, Assistant Professor at the University of Minnesota’s School of Social Work, scams and fraud are now the most common form of organized crime globally, rivaling weapons trafficking, drug trafficking, human trafficking, and sex trafficking. In 2024 alone, she said, the FTC estimated that older adults in the US had as much as $81.5 billion stolen from them. And the tools meant to fight back—broad consumer awareness campaigns, embedded warning messages at the point of transaction, the training of bank tellers and retail clerks—are nowhere near keeping pace.
So what actually works? And who, if anyone, is doing the work?
Today, on the Lock and Code podcast with host David Ruiz, we speak with DeLiema about who is really susceptible to financial fraud, why victims often describe a scam as a form of betrayal trauma, and why the companies best positioned to stop scam messages from reaching consumers may be the ones least motivated to do so.
“This is not a technical capability problem at all. This is a conflict of incentives.”
A dreadful thing happens far too often whenever an older adult falls for a scam: They get blamed for it. Not the scammers who lied and cheated their victim out of money. Not law enforcement for failing to recover funds. Not even the Big Tech companies that could have the most important role in protecting people online—and which, it turns out, knowingly bring in revenue every year from fraud.
Instead, it is the older adults themselves whose stories are often shirked aside because of a mix of ageism and denial. Allegedly left behind by technology, only an octogenarian would hand their password over in a phishing scheme, or open an email attachment from a stranger, or send money to a fake charity online. Everyone else, everyone else believes, is too savvy for the same.
The data disagrees.
When Malwarebytes studied this last year, it found that, depending on the type of scam—especially for things like “sextortion”—younger individuals were far more likely to report falling victim. Further, digging into data from the US Federal Trade Commission revealed entirely separate patterns. For example, while Americans between the ages of 80 and 89 reported the highest median loss due to fraud in 2024, they also made up the smallest share of their population to report a loss at all. And in 2025, that same group represented the smallest share of reported identity theft, a crime far more likely to be reported by people between 30 and 39.
Questions about who reports what crimes at what rate are valid to explore, but it’s important to see the big picture: Americans lost at least $15.9 billion to fraud last year. Protecting older adults is actually about protecting everyone, and that’s because modern scams don’t arrive only where people over 70 spend time. They arrive where we all are, which is online. They come through endless text messages, they slide into social media DMs, and they prey on things any of us can be—a widow, a divorcee, or simply a lonely person.
According to Marti DeLiema, Assistant Professor at the University of Minnesota’s School of Social Work, scams and fraud are now the most common form of organized crime globally, rivaling weapons trafficking, drug trafficking, human trafficking, and sex trafficking. In 2024 alone, she said, the FTC estimated that older adults in the US had as much as $81.5 billion stolen from them. And the tools meant to fight back—broad consumer awareness campaigns, embedded warning messages at the point of transaction, the training of bank tellers and retail clerks—are nowhere near keeping pace.
So what actually works? And who, if anyone, is doing the work?
Today, on the Lock and Code podcast with host David Ruiz, we speak with DeLiema about who is really susceptible to financial fraud, why victims often describe a scam as a form of betrayal trauma, and why the companies best positioned to stop scam messages from reaching consumers may be the ones least motivated to do so.
“This is not a technical capability problem at all. This is a conflict of incentives.”
Forget the runaway train thrillingly shot in Buster Keaton’s 1926 film “The General,” and never mind the charging locomotive rescued by actors Denzel Washington and Chris Pine in the 2010 film “Unstoppable,” as there’s a far more frequent (and far less heart-pounding) railcar drama happening across California’s Bay Area: The repeated breakdown of the Bay Area Rapid Transit (BART) system, all because of a few networking errors.
Opened in 1972, BART today carries about 175,000 people every weekday on five separate lines to 50 different stations placed across dozens of cities in the Bay Area, including San Francisco, Oakland, Berkeley, Daly City, Fremont, Richmond, and more. Its tracks and railcars travel both above ground and below, and it is one of the only public transit systems in the US that goes underwater—traveling through what is called the TransBay tube. It is likely the region’s largest public project, spanning 131 miles of track, with a fleet of more than 700 cars, proving vital to workers and residents everywhere, and on May 9, 2025, it all came grinding to a halt, due to what BART officials called a “computer networking problem.”
At the Glen Park station in San Francisco, would-be travelers found yellow caution tape at the entry gates. At the El Cerrito Plaza station, BART staff and police informed visitors that the system was down. And at the Rockridge station in Oakland, a reporter for The San Francisco Chronicle witnessed a small group of people sprinting up the stairs to try and catch a train that never came.
It was the kind of meltdown for public infrastructure that puts an entire system in peril.
And it happened again just months later.
In September, a network crash brought BART to a halt, repeating almost the exact same frustrations and delays for travelers left without transportation to work.
That’s the end of it, right? Wrong. In February 2026, another computer failure caused another outage.
So, in one of the wealthiest regions in America, the subway doesn’t always run, its network is prone to crash, and any money for technology often goes elsewhere.
Today, on the Lock and Code podcast with host David Ruiz, we speak with San Francisco Chronicle transportation report Rachel Swan about what the BART outages revealed about the state of the system’s aging technology, why public infrastructure so often struggles to modernize, and what exactly went wrong in the three prior outages.
“One piece of equipment—and again, this is old equipment—one piece breaks down and they completely lose visibility, so they don’t know where any of the trains are.”
While How to Fix the Internet is on hiatus, we wanted to share a great conversation with you from last week. EFF Executive Director Cindy Cohn spoke with bestselling novelist, journalist, and EFF Special Advisor Cory Doctorow about Cindy’s new book, “Privacy’s Defender: My Thirty-Year Fight Against Digital Surveillance” (MIT Press).
Part memoir, part battle cry, “Privacy’s Defender” is the story of Cindy’s fights alongside the visionaries who looked at the early internet and understood that the legal and political battles over this new technology - the Crypto Wars, the NSA’s dragnet, the FBI gag orders - were really over the future of free speech, privacy, and power for all.
This conversation was recorded on Tuesday, March 10 in front of a packed house at San Francisco’s iconic City Lights Bookstore. For more about the book and Cindy’s national book tour - with stops in places including Seattle, Silicon Valley, Denver, Boston, Ann Arbor, Iowa City, Washington DC and New York City - check out https://www.eff.org/Privacys-Defender
And finally, stay tuned to this feed; we’re working on a special podcast series featuring key players and moments from the book!
On February 8, during the Super Bowl in the United States, countless owners of one of the most popular smart products today got a bit of a wakeup call: Their Ring doorbells could be used to see a whole lot more than they knew.
In a commercial that was broadcast to one of most reliably enormous audiences in the country, Amazon, which owns the company Ring, promoted a new feature for its smart doorbells called “Search Party.” By scouring the footage of individual Ring cameras across a specific region, “Search Party” can implement AI-powered image recognition technology to find, as the commercial portrayed it, a lost dog. But immediately after the commercial aired, people began wondering what else their Ring cameras could be used to find.
“Ring’s Super Bowl ad exposed a scary truth: the technology in its doorbell cameras could be used to hunt down a lost pet…or a person. Amazon must discontinue its dystopian monitoring features.”
These “dystopian monitoring features” aren’t entirely new, but that’s not to say that most Ring owners knew what they were allowing when they originally bought their devices.
Bought by Amazon in 2018, Ring is the most popular manufacturer of a product that, as of 15 years ago, didn’t really exist. And while other “smart” innovations failed, smart doorbells have become a fixture of American neighborhoods, providing a mixture of convenience and security. For instance, a Ring owner away from home can verify and buzz in their mailman dropping off a package behind a gated entrance. Or, a Ring owner can see on their phone that the person knocking at their door is a salesman and choose to avoid talking to them. Or, a Ring owner can help police who are investigating a crime in their area by handing over relevant footage. Even the presence of a Ring doorbell, and its variety of motion-detecting alerts, could possibly serve as a deterrent to crime.
What has seemingly upset so many of those same owners, then, is learning exactly how their personal devices might be used for a company’s gains.
Today, on the Lock and Code podcast with host David Ruiz, we speak with Matthew Guariglia, senior policy analyst at Electronic Frontier Foundation, about Ring’s long history of partnering with—and sometimes even speaking directly for—police, who can access Ring doorbell footage both inside the company and outside it, and what people really open themselves up to when purchasing a Ring device.
”There’s this impression, a myth practically, that ‘I buy a ring doorbell to put on my house, I control the footage… But there is [an] entire secondary use of this device, which is by police that you don’t really get a lot of say in.”
On February 8, during the Super Bowl in the United States, countless owners of one of the most popular smart products today got a bit of a wakeup call: Their Ring doorbells could be used to see a whole lot more than they knew.
In a commercial that was broadcast to one of most reliably enormous audiences in the country, Amazon, which owns the company Ring, promoted a new feature for its smart doorbells called “Search Party.” By scouring the footage of individual Ring cameras across a specific region, “Search Party” can implement AI-powered image recognition technology to find, as the commercial portrayed it, a lost dog. But immediately after the commercial aired, people began wondering what else their Ring cameras could be used to find.
“Ring’s Super Bowl ad exposed a scary truth: the technology in its doorbell cameras could be used to hunt down a lost pet…or a person. Amazon must discontinue its dystopian monitoring features.”
These “dystopian monitoring features” aren’t entirely new, but that’s not to say that most Ring owners knew what they were allowing when they originally bought their devices.
Bought by Amazon in 2018, Ring is the most popular manufacturer of a product that, as of 15 years ago, didn’t really exist. And while other “smart” innovations failed, smart doorbells have become a fixture of American neighborhoods, providing a mixture of convenience and security. For instance, a Ring owner away from home can verify and buzz in their mailman dropping off a package behind a gated entrance. Or, a Ring owner can see on their phone that the person knocking at their door is a salesman and choose to avoid talking to them. Or, a Ring owner can help police who are investigating a crime in their area by handing over relevant footage. Even the presence of a Ring doorbell, and its variety of motion-detecting alerts, could possibly serve as a deterrent to crime.
What has seemingly upset so many of those same owners, then, is learning exactly how their personal devices might be used for a company’s gains.
Today, on the Lock and Code podcast with host David Ruiz, we speak with Matthew Guariglia, senior policy analyst at Electronic Frontier Foundation, about Ring’s long history of partnering with—and sometimes even speaking directly for—police, who can access Ring doorbell footage both inside the company and outside it, and what people really open themselves up to when purchasing a Ring device.
”There’s this impression, a myth practically, that ‘I buy a ring doorbell to put on my house, I control the footage… But there is [an] entire secondary use of this device, which is by police that you don’t really get a lot of say in.”
This article is based on a conversation with Nikesh Arora on the 100th episode of the Threat Vector podcast.
David Moulton interviews Nikesh Arora on the Threat Vector podcast.
"Most technologists think about technology, not about cybersecurity," Nikesh Arora says. "Cybersecurity is kind of like insurance. Let's go make great things happen, and let's make sure on the way we purchase insurance."
Coming from the CEO of the world's largest cybersecurity company, it's the quiet part said out loud, and it explains why AI deployment is racing ahead while security scrambles to keep up.
Earlier this year, Arora spoke with a CIO entirely focused on AI deployment challenges: building viable products, training models, measuring customer impact. Security never came up once. "If you're still going through the motion, trying to understand, ‘Can I actually make this thing work?’ You're not worried about security," Arora notes. The logic is brutal but consistent: Why secure something that might not even function?
Why the gap between innovation and security keeps widening.
How to read inflection points before they're obvious.
What separates organizations that prepare from those that scramble.
The Gap That Keeps Growing
The disconnect isn't new. It's the same psychology that makes airport security feel like overhead – necessary friction that slows down what should be seamless. But with AI, the gap is widening at an unprecedented pace.
Consider the infrastructure buildup happening right now. Nvidia has become a $4 trillion company selling chips that can't stay in stock. Hundreds of billions of dollars are flowing into AI-computer infrastructure. Cloud providers are buying out entire methane gas companies to power their data centers.
Yet organizations are treating AI security as something to bolt on later. That same CIO told Arora: "We worked on some stuff ourselves, and we're just jerry-rigging some things to make sure this happens securely."
Arora's response:
Jerry rig, production, and security don't work together as three terms.
Reading Signals Before They're Obvious
Arora has watched enough technology cycles to recognize the pattern. "You start seeing signs early, and then you look around, you don't see enough impact. You say, okay, maybe this is going to be just a passing shower. But you don't realize that over time this thing's getting more and more momentum."
The signs around AI are adding up:
Individual behavior has shifted.
Arora went from never talking to ChatGPT or Gemini to conducting 10-15 conversations daily. During a recent Tokyo trip, he used Gemini as his primary navigation tool, asking it to rank sumo wrestling shows for his kids rather than "trying to go read 14 websites and figure out what makes sense."
The spend is massive and accelerating.
Not just chips, entire energy infrastructures are being rebuilt to support AI compute needs.
Consumer and enterprise adoption are both surging.
From coding assistants to business analysis, use cases are expanding faster than security models can adapt.
"This thing's going to change our life fundamentally," Arora tells Moulton. "We're not seeing it at scale in our customers just yet. That doesn't mean we can sit back and wait."
Arora understands the risks involved in being late to new technology.
You have to not just anticipate where the trend is going. You have to prepare your organization and the resources to get there. Otherwise, the risk is that Silicon Valley will go fund those people who are thinking purely about the new world... and one of them's going to hit. Then you'll be two years behind with no organization, no resources deployed against it.
The Bets That Paid Off
When Arora joined Palo Alto Networks seven and a half years ago, he wrote two words on a piece of paper: cloud and AI. The company was a firewall business. Those two inflection points would require fundamental transformation, and, just as with AI now, being late was not an option.
If you don't get the network transformation right, 80% of our business will falter.
That insight drove a strategic bet on moving from point products to platform thinking, consolidating security tools rather than adding to the sprawl.
The platform approach wasn't about vendor consolidation for its own sake. It was about correlation. Unit 42® data shows that 70% of incidents now span three or more attack surfaces. When attacks move across endpoints, networks, cloud services and applications simultaneously, fragmented security creates gaps that attackers exploit ruthlessly.
Today we have coverage for 80 plus percent of the industry, which means our customers can come talk to us about a myriad of problems, and we can actually cross-correlate across all the different things we do.
With AI deployments touching every part of the technology stack, that cross-correlation becomes essential. Data flows between training environments and production systems. Models access APIs across cloud and on premises infrastructure. Applications consume AI services from multiple providers. Security that can't see and correlate across that entire landscape will miss the threats that matter most.
First Principles Over Tradition
What drives Arora's ability to spot inflection points isn't just pattern recognition, it's his refusal to accept how things have always been done.
His pet peeve: "Somebody said, well, this is how we've traditionally done it." The response reveals his approach: "You use the word traditional. I use the historical context saying, yeah, sure, they used to dig fields with picks and shovels, and now they use tractors."
This thinking drove Palo Alto Networks to reimagine SOC performance. The industry accepted four days as the normal time to detect and remediate security incidents. Arora called that unacceptable. "We need to get it to be real time."
The result was a fundamentally different architecture that analyzes data as it arrives rather than waiting for problems to appear, enabling 1-minute detection and response instead of four days.
Traditionally, SOCs would analyze the problem when the problem appeared. We said forget it. We're going to analyze everything to see if there's a problem. That architecture fundamentally transformed what we do compared to everybody else in the market.
The same first-principles approach needs to apply to AI security. Organizations can't simply extend existing security models and hope they work.
What Comes Next
With ransomware attacks now completing in as little as 25 minutes (100 times faster than just three years ago, according to Unit 42 research) reactive security simply can't keep pace. Organizations need security that thinks and responds at machine speed, built into AI deployments from day one.
"AI has become the biggest inflection point in current technology," Arora observes. Organizations are too busy deploying to worry about security. That's human nature. But it's also the moment when security teams need to stay in lockstep.
The question isn't whether to secure AI, it's whether security will be designed in or bolted on. The former takes strategic thinking now. The latter takes crisis management later.
Our job at Palo Alto and our industry is to make sure as they go build these experimental ideas into real production capability that we're staying in lockstep with them and saying, ‘Oh, by the way, here's something that can secure what you just built in a way that is not gonna get you into trouble.’
Listen to the full conversation between Nikesh Arora and David Moulton, senior director of thought leadership for Cortex® and Unit 42, on the 100th episode of Threat Vector.
In January, Google settled a lawsuit that pricked up a few ears: It agreed to pay $68 million to a wide array of people who sued the company together, alleging that Google’s voice-activated smart assistant had secretly recorded their conversations, which were then sent to advertisers to target them with promotions.
Google denied any admission of wrongdoing in the settlement agreement, but the fact stands that one of the largest phone makers in the world decided to forego a trial against some potentially explosive surveillance allegations. It’s a decision that the public has already seen in the past, when Apple agreed to pay $95 million last year to settle similar legal claims against its smart assistant, Siri.
Back-to-back, the stories raise a question that just seems to never go away: Are our phones listening to us?
This week, on the Lock and Code podcast with host David Ruiz, we revisit an episode from last year in which we tried to find the answer. In speaking to Electronic Frontier Foundation Staff Technologist Lena Cohen about mobile tracking overall, it becomes clear that, even if our phones aren’t literally listening to our conversations, the devices are stuffed with so many novel forms of surveillance that we need not say something out loud to be predictably targeted with ads for it.
“Companies are collecting so much information about us and in such covert ways that it really feels like they’re listening to us.”
In January, Google settled a lawsuit that pricked up a few ears: It agreed to pay $68 million to a wide array of people who sued the company together, alleging that Google’s voice-activated smart assistant had secretly recorded their conversations, which were then sent to advertisers to target them with promotions.
Google denied any admission of wrongdoing in the settlement agreement, but the fact stands that one of the largest phone makers in the world decided to forego a trial against some potentially explosive surveillance allegations. It’s a decision that the public has already seen in the past, when Apple agreed to pay $95 million last year to settle similar legal claims against its smart assistant, Siri.
Back-to-back, the stories raise a question that just seems to never go away: Are our phones listening to us?
This week, on the Lock and Code podcast with host David Ruiz, we revisit an episode from last year in which we tried to find the answer. In speaking to Electronic Frontier Foundation Staff Technologist Lena Cohen about mobile tracking overall, it becomes clear that, even if our phones aren’t literally listening to our conversations, the devices are stuffed with so many novel forms of surveillance that we need not say something out loud to be predictably targeted with ads for it.
“Companies are collecting so much information about us and in such covert ways that it really feels like they’re listening to us.”
When you hear the words “data privacy,” what do you first imagine?
Maybe you picture going into your social media apps and setting your profile and posts to private. Maybe you think about who you’ve shared your location with and deciding to revoke some of that access. Maybe you want to remove a few apps entirely from your smartphone, maybe you want to try a new web browser, maybe you even want to skirt the type of street-level surveillance provided by Automated License Plate Readers, which can record your car model, license plate number, and location on your morning drive to work.
Importantly, all of these are “data privacy,” but trying to do all of these things at once can feel impossible.
That’s why, this year, for Data Privacy Day, Malwarebytes Senior Privacy Advocate (and Lock and Code host) David Ruiz is sharing the one thing he’s doing different to improve his privacy. And it’s this: He’s given up Google Search entirely.
When Ruiz requested the data that Google had collected about him last year, he saw that the company had recorded an eye-popping 8,000 searches in just the span of 18 months. And those 8,000 searches didn’t just reveal what he was thinking about on any given day—including his shopping interests, his home improvement projects, and his late-night medical concerns—they also revealed when he clicked on an ad based on the words he searched. This type of data, which connects a person’s searches to the likelihood of engaging with an online ad, is vital to Google’s revenue, and it’s the type of thing that Ruiz is seeking to finally cut off.
So, for 2026, he has switched to a new search engine, Brave Search.
Today, on the Lock and Code podcast, Ruiz explains why he made the switch, what he values about Brave Search, and why he also refused to switch to any of the major AI platforms in replacing Google.
When you hear the words “data privacy,” what do you first imagine?
Maybe you picture going into your social media apps and setting your profile and posts to private. Maybe you think about who you’ve shared your location with and deciding to revoke some of that access. Maybe you want to remove a few apps entirely from your smartphone, maybe you want to try a new web browser, maybe you even want to skirt the type of street-level surveillance provided by Automated License Plate Readers, which can record your car model, license plate number, and location on your morning drive to work.
Importantly, all of these are “data privacy,” but trying to do all of these things at once can feel impossible.
That’s why, this year, for Data Privacy Day, Malwarebytes Senior Privacy Advocate (and Lock and Code host) David Ruiz is sharing the one thing he’s doing different to improve his privacy. And it’s this: He’s given up Google Search entirely.
When Ruiz requested the data that Google had collected about him last year, he saw that the company had recorded an eye-popping 8,000 searches in just the span of 18 months. And those 8,000 searches didn’t just reveal what he was thinking about on any given day—including his shopping interests, his home improvement projects, and his late-night medical concerns—they also revealed when he clicked on an ad based on the words he searched. This type of data, which connects a person’s searches to the likelihood of engaging with an online ad, is vital to Google’s revenue, and it’s the type of thing that Ruiz is seeking to finally cut off.
So, for 2026, he has switched to a new search engine, Brave Search.
Today, on the Lock and Code podcast, Ruiz explains why he made the switch, what he values about Brave Search, and why he also refused to switch to any of the major AI platforms in replacing Google.
Login
