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Lessons Learned From 'AdFection' and What To Do Next

26 October 2026 at 18:28

Last week, researchers at Citizen Lab revealed a horrifying new malware campaign, dubbed “AdFection.” It used an ad network to distribute spyware to journalist’s devices to infect them without the target ever needing to click anything. This sort of attack on journalists is dangerous and incredibly concerning, especially since it’s built on the backbone of a technology we already object to: behavioral advertising. Although this type of attack has only been described targeting journalists, you can take a few steps we outline in the next section to mitigate the risk no matter who you are.

A few factors combined to make this attack a noteworthy first-of-its-kind. First, it utilized the surveillance ad-tech ecosystem to specially target the malicious code. Second, the spyware it delivered was so-called “zero-click,” meaning it required no interaction from the user to be infected: all that is required is for the ad to be delivered and code bundled along with it to be run, which happens automatically. Neither malvertising nor zero-click attacks are new on their own. What’s novel about the AdFection attack is combining them, creating a highly targeted, extremely dangerous attack which is difficult to defend against and even harder to detect.

Let’s take a deeper look from the perspective of one of the Windows devices supplied to the researchers from Al Jazeera. Here’s how the report describes the infection happening: 

  • Someone browsing the web or using an app on that machine is served an ad created by Discover-Tech, a company exposed in the report as “purporting to be a legitimate advertising company, [but] appears to be a front for large-scale ad espionage abuse.” 
  • The ad contains a small snippet of JavaScript code which is automatically executed when rendered in the app or website. 
  • This code reaches back out to a Discover-Tech server, referred to as their “NOAS server,” with detailed information about the machine rendering it: its cookie-set advertising ID, IP address, and more.

So far, nothing particularly unusual has happened. Ads that contain JavaScript code and reach back out to their servers with lots of information on your device—and by extension you—are commonplace. It’s all part of the data-driven advertising ecosystem. What happens next is more interesting:

  • The NOAS server uses this detailed information to determine it is an Al Jazeera machine requesting the ad. 
  • Instead of returning an empty response (as it does most of the time), it responds with a malicious, zero-click spyware payload. That payload was created by Discover-Tech’s partner Candiru/Integrity Labs, a company previously exposed for involvement in sophisticated malware attacks. 
  • The payload is then executed and infects the targeted machine.

Companies targeting zero-click malware attacks against journalists might seem like the plot of a blockbuster spy thriller. But this attack was enabled by the everyday practices of ad-tech companies, which unfortunately have extreme latitude in the collection of users’ data. By leveraging the tracking identifiers and data collected on devices for the purpose of delivering targeted ads to specific individuals, mercenary spyware companies can repurpose this data in order to fine-tune who they infect—and hide that they’re doing it from everyone else. 

Most ads are not delivered directly by the ad creators, but rather by intermediaries that facilitate Real-Time Bidding auctions. Nonetheless, winning bidders are given the ability to execute JavaScript code in the browser of the person who receives the targeted ad. This allows for interactive ads to be displayed, but also (as we’ve seen) for the compromise of a device just by delivery of malicious code.

While the different components in this attack chain are not novel on their own, the exposure of this combined attack is significant because it reveals a technique to hyper-target individuals and organizations for infection. Luckily, there are steps you can take to protect yourself from the myriad of dangers presented by the ad-tracking industry. Here’s how.

What You Can Do About It

As we work towards fundamental fixes to the ad ecosystem and banning online behavioral ads altogether, the onus is on all of us to protect ourselves. This is especially important for higher risk individuals or journalists working in states with heavy surveillance. Citizen Lab outlines several steps, depending on your threat model, to take to help protect yourself:

These steps can be very helpful in protecting yourself, but there is only so much you can do as an individual. Banning behavioral ads like this would be a good place to start. Behavioral ads aren’t just a privacy nightmare as designed. They are the perfect vehicle for malvertising and similar threats, just as we see here.

The Vulnerability Apocalypse and Why We Should Fund Open Source

24 October 2026 at 00:36

If you use the internet at all, you may have noticed that a large percentage of sites suddenly went down earlier this week—and all your nerdiest friends were talking about "The Vulnerability Apocalypse” and this thing called PHP that powers nearly 70% of the websites on the internet. You may find yourself wondering: what is PHP, what just happened, what is the vulnerability apocalypse, and what do I need to do?  

To find out what you can personally do read the first blog post in this series!  

What Is PHP?  

PHP is a programming language used mainly to create interactive websites. Facebook, Wordpress, Wikipedia, Etsy, and other major sites all use or were originally built on PHP. It is a long-established mainstay of web development. But because it is open-source, maintenance of these critical systems depends on a small number of volunteers working on this in their free time. The disaster scenario that happened this past week is the perfect example of why we need more money and people supporting open-source projects. Corporations should be contributing both. 

What Is the Vulnerability Apocalypse?  

Common Vulnerabilities and Exposures (CVEs) are the way that security professionals file reports about vulnerabilities in software. The National Vulnerability Database (NVD), run by NIST, is the official national database of CVEs. In other words, CVE reports managed by NIST are the closest thing we have to a canonical database of security vulnerabilities in software. The NVD currently has around 400,000 CVEs that have been filed and accepted since 1988. In just the month of October, 13,000 new CVEs have been submitted. This means that 3% of critical software security bugs that have ever been officially logged were found in the last month alone. And it's likely that by the end of the year over a quarter of the software vulnerabilities that have ever been found will be from 2026.  

 

a graph showing the number of computer vulnerabilities by week since 1990, increasing exponentially in the last couple months.

Computer vulnerabilities reported are rising exponentially. Source: CVE Tracker

This research is being driven almost entirely by the cybersecurity capabilities of major AI models from companies like Anthropic, OpenAI, and Google. Historically it has been popularly assumed by cybersecurity experts that finding unknown (zero-day) exploits in any specific project and turning them into exploits was expensive. The knowledge to discover them was not widespread, and it was a hard task even for those initiated into the arcane ways of vulnerability hunting. Google even dedicated an entire team to it.  

But now thanks to major AI models, vulnerabilities are cheap, and anyone of moderate technical skill with a few dollars and access to a frontier AI model can find vulnerabilities in a few minutes. For example, recent vulnerabilities in PHP were found with a prompt to an AI model that literally said "find bad vulnerabilities in PHP."  

What Happened This Week? 

In 2024, a potentially severe vulnerability in PHP was discovered during an external security audit. PHP’s maintainers couldn’t agree on a solution, but more importantly, they couldn’t find a way to exploit the vulnerability. Because it didn’t seem like an active threat, they ended up deprioritizing a fix in favor of working on more urgent security issues. Then, in August 2026, security researchers working with the latest models from OpenAI and Anthropic independently discovered the vulnerability again, and another one—and now, with a way to exploit them.  

We now know that the vulnerabilities were so severe that they would have allowed even moderately inventive hackers to take over any website that uses PHP and then steal customer data, launch further malware attacks, spy on users, take websites offline, or launch a massive denial of service attack.[1] 

Because of the severity of these vulnerabilities, several of the involved researchers got together with the makers of PHP to patch the vulnerabilities and disclose them in a coordinated manner. The idea was that hopefully everyone would get a chance to quietly release and then apply fixes for the vulnerabilities before the whole world found out about it. 

But news already started to leak on October 20th. There was a post on a widely read forum “Hacker News” and other posts elsewhere. One of the researchers accidentally published a video early. Companies reported seeing active exploitation of the vulnerabilities going back as far as October 17th. On October 21st, six hours before the planned press embargo, one company, Chainguard, jumped the gun and released a patch early, essentially giving anyone instructions about exactly where to find the vulnerabilities and how to weaponize them. This sent system administrators everywhere scrambling to patch their systems before they were taken over by hackers. And it’s going to take a long time to patch all these systems. At the time of this writing over 33 million websites are still running on vulnerable versions of PHP.  

The internet is run largely on open-source software, mostly maintained by a small handful of skilled volunteers occasionally getting a small stipend, not by major corporations and highly paid engineers. These are projects you have perhaps never heard of, like PHP, OpenSSL, and SQLite, but these programs run on nearly every computer in the world and are maintained by teams as small as one person. When a vulnerability is found in these projects, it can be devastating.  

PHP isn’t the only critical open-source software with a high severity vulnerability this week either. Other widespread open-source projects like Node.js and GitLab also had severe security bugs reported.  

The small number of already overworked open-source maintainers are now facing a deluge of vulnerability reports, some of which are false, but many of which are very real. Burnout in open source has never been higher.  

We Need Stronger Support for Open Source Projects

Much of the foundation for the modern multibillion-dollar internet industry is built on open-source products that were created and still maintained—for free—by dedicated volunteers in their spare time. It’s an imperfect system, and it can lead to errors.  

One of those critical, under resourced open-source products is PHP. And while vulnerabilities in PHP were privately found years ago, they were left unfixed because they didn’t seem as impactful as other bugs at the time. These same vulnerabilities were recently rediscovered and proved to be trivially exploitable by security researchers using advanced AI models. While in the middle of the widespread, global effort to correct this mistake and deploy fixes, the problem was leaked by some of the security researchers who had gotten early access to the fixes. Unfortunately, this left millions of websites, ranging from personal blogs to government sites, vulnerable to hacking that could result in data theft, malware distribution, and worse.  

Open-source projects like PHP and others are the backbone of the entire internet. If they don’t get the resources they need, they and the internet they power, are at risk of falling apart. Corporations (whose products would not exist without these products) should be actively contributing to their maintenance. 

1. A technical analysis of the vulnerabilities is out of scope for this post and has already been written by the original researchers.

GPT-6 Astra Breaks an Old Enigma Message

22 September 2026 at 13:02

This is pretty amazing:

However, the most astonishing thing about this break is that the GPT­6 Astra did it entirely on its own. Carter Leffer only directed GPT­6 Astra to see if it could break any of the unbroken Enigma messages published on the Crypto Cellar Research web page. After analysing the unbroken messages on the website, it decided that the most promising message was Nr. 172, MVUEH and it also quickly suspected that the plaintext of Nr. 173, SIPVX, might be related to the plaintext of the unbroken MVUEH message. After trying many different approaches, GPT­6 Astra focused on using the repeated place name ROSENOW ROSENOW as a crib. After developing the necessary Python and C++ software for an Enigma simulator and an Enigma Bombe, GPT­6 Astra started a thorough break with the ROSENOW crib, which in the end resulted in the correct key and plaintext for the MVUEH message being found.

We are still analysing the GPT­6 Astra logs to see exactly how it executed the break. And we are discovering amazing details.

More details at the link.

Secure Messaging and AI Remain In Conflict Despite the Promise of TEEs

18 September 2026 at 23:53

Secure messaging platforms, like Signal, WhatsApp, and recently, encrypted RCS, operate on a straightforward assumption: the content at each end of a conversation is private to the participants in the conversation. End-to-end encryption helps provide the mathematical guarantees that the companies who operate these messaging platforms cannot access the contents of messages. But there’s no way to guarantee what happens once the message arrives on a phone. As more devices and services introduce more artificial intelligence (AI) features into messaging apps, that line begins to blur. 

When AI features are computed entirely on device, it’s less concerning. Yet sometimes the computing requirements are heavy enough that the computation has to be done on a company server. Tech companies tell us they have a solution for this: trusted execution environments (TEEs). But do server-side TEEs really solve the problem?

TEEs exist to serve many different functions, ranging from digital rights management (DRM) content protections to securely storing information in your phone's mobile wallet, but for our purposes, we’ll be focusing on how tech companies use them for their AI tools. 

The basic idea is straightforward: most consumer devices aren’t powerful enough to handle the sorts of AI features companies want to offer, so sometimes they send data off your device to more powerful cloud servers to do the computing, then display the results on your device. Since your data is leaving your device, there’s a privacy compromise. For example, if you ask for a messaging app to summarize a conversation, it may offload that computing power to a cloud server, sending the entire contents of your messages to the cloud, then back to your phone.

TEEs supposedly offer a way to keep those requests private. There are several implementations out there, like Apple’s Private Cloud Compute, Google’s Private AI Compute, and WhatsApp’s Private Processing. It’s not just the big tech players, we’ve seen chatbots built with TEEs as well.

TEEs can provide more security and privacy than simply running in the clear, but they are fundamentally different from actual encryption or running locally. Despite the promises of some tech companies, they will never be able to match that level of security and privacy. Because of that, a user’s device should never automatically send data to a TEE. Let’s dig through the reasons why.

What Exactly Is a TEE, Anyway?

A TEE is a hardened section of the computer that runs software in a way that’s supposed to be secret even from other processes running on the machine. TEEs also let users check that the code being run is the code that they think is running, and not backdoored code instead, using a process called “attestation.” You may have also heard this referred to as a “secure enclave,” or heard the brand names SGX or TrustZone.

The intention of a cloud-based TEE is simple: a company can run a server in their data center, but still process data that you provide on your behalf without being able to see that information themselves.

Is a TEE Secure?

In practice, we've seen multiple cracks and hacks every year that show that it is possible to get at that data. That’s because while encryption relies on math, TEEs rely on engineering to provide their security. Standard encryption algorithms are created by years-long processes collaboratively produced by mathematicians around the world and are based on problems that have been studied for decades. The math is reliable, and there is no shortcut to breaking it that would not also upend fundamental understandings of mathematics as a field. 

The collective understanding of every mathematician in the world is that standard encryption algorithms are not breakable to the best of the world’s collective knowledge. No responsible engineer builds a system based on a new encryption method until after it’s been offered up for prodding.

Engineering, on the other hand, doesn’t work like that. Every individual system is the product of a group of engineers who put it out into the world, and each product will have its own quirks and bugs that have to be individually discovered and patched. These bugs are found after the system is built, not before. No one has yet built a system that is unbreakable. On the contrary, there is new research all the time that finds new ways to break into TEE systems. They’re patched as they come up, but they’re unlikely to ever become perfect, and certainly not any time soon. 

TEEs in particular are a hard engineering problem because the encryption key is physically right there on the device. Building a TEE means keeping a key fully separate and inaccessible while it’s on the same physical device as parts of the system that shouldn’t have access to the key.

Many attacks on TEEs involve “side channels.” In a side channel attack, the attacker measures the electrical impulses or other effects to figure out the timing of operations inside the TEE, then uses that to figure out the key being used. Once they have the key, they can read all the data. Compare that to end-to-end encryption, where the key is never on that machine in the first place, so an attacker would have to also run a similar attack on the user’s device.

Companies who turn to TEEs to protect data want to both have the key on the server and have it protected while still performing complex operations like running an LLM, which makes it much more difficult to protect those keys.

That being said, a TEE versus plaintext on a server is the difference between being able to easily read the data and having to do a bunch of specialized work to get at the data. That work often involves accessing the physical machine. This is most relevant for protecting against mass surveillance, and for many people, that might just be enough security.

But that's the core of the problem. “Secure enough for most cases” and “encrypted as in math” are not the same thing, and it’s important not to conflate the two. And services that currently offer “encryption as in math” have a real downgrade in security when they switch to security based on TEEs. 

If you want to dive into the myriad security issues and limitations of TEEs we’ve seen so far, they’re well documented here, here, here, and here.

What Does This Have To Do With LLMs and AI?

Sometimes organizations want to offer an LLM that can respond to queries in a private manner. On-device LLMs exist, but they’re limited in size. So, when organizations want to offer the ability to answer queries without being able to see the conversation, they turn to TEEs. That’s a useful way to run a chatbot that’s reasonably private. This is what Apple, Google, WhatsApp, and others are doing.

Why not turn to encryption? After all, LLM inference is just a bunch of math like any other things a computer does. It takes input to a (really big) function and gives an output. We have the math to do that computation in a way that hides the inputs and outputs from the one running the computation, it's just super expensive. It’s called homomorphic encryption, and no one’s figured out how to do it fast enough that it makes sense for this sort of computation.

Instead, the allure of a TEE is that it will run that computation for you inside of a special opaque section of a server. TEE manufacturers try to make it as hard as possible for the person running the TEE to peek inside. But you still have to trust the operator to not put a stethoscope to the box to try to figure out what's happening inside. 

In this case, it’s reasonable to consider these systems “privacy-preserving,” but not “encrypted.” That distinction is important, especially when we talk about how the TEEs interact with secure messaging. When someone using an end-to-end encrypted chat app asks an LLM to summarize, review, or store those messages, the content of those messages is leaving the device and going to an unencrypted third-party server somewhere. That’s a major threat to the privacy of secure chat apps, and one that’s increasingly hard for users to take control of.

How Does This Translate to Practical Advice?

The answer to this is going to vary based on an individual’s threat model, but a good rule of thumb is that a user’s device should never automatically send data to a TEE. When the person holding a phone can choose what information is sent, even if it’s a chunk of data like “unread messages,” they have the opportunity to pause and consider if that data might be too sensitive to risk sending.

In contrast, when data is sent automatically, the automatic sending becomes a feature of the system as a whole. If the system was previously end-to-end encrypted, adding automatic exfiltration makes the whole system no longer end-to-end encrypted.

Developers: don’t build systems that automatically send data off a device to a TEE, especially when it’s coming from an app that is otherwise end-to-end encrypted.

Users: if developers ignore us and build that system, turn off any automatic data sending features. Take a second to think about how much you’re willing to risk sending data when you choose to send it off the device.

So, What Should I Be Concerned About?

TEEs are useful for security in a number of circumstances. Your phone likely has a TEE where it keeps the key that encrypts your biometric unlock data and the base of the keychain where passwords are stored. It also enables certain backup systems, like how you can restore a phone with your passcode or restore WhatsApp or Signal backups.

But when we’re talking about cloud processing, it’s important to be clear this isn’t the same as end-to-end encryption and doesn’t offer the same level of privacy. 

Most of our private lives are on our phones and in our messages. We’ve worked for years to secure those messages, with major wins like encrypted RCS, and the continued user experience improvements of Signal and WhatsApp. We’ve even seen real improvements to backup security with features like Advanced Data Protection that bring end-to-end encryption for a variety of data outside of messaging, like notes and photos. 

But as companies roll out AI features that interact with these encrypted services, pulling data off devices and into a cloud-based TEE, they’re eroding the privacy protections of end-to-end encryption and risk causing serious confusion around what data is protected and what isn’t.

Ninth Circuit Ruling Will Force Online Platforms That Host User Speech to Fight Lengthy and Costly Lawsuits Before They Are Dismissed Under Section 230

19 August 2026 at 01:23

A federal appeals court just made it harder for online services, big and small, to get lawsuits over user speech dismissed early. In California v. Meta, a Ninth Circuit three-judge panel held that the lower court’s denial of Section 230 immunity to Meta is not immediately appealable. The misguided ruling has the potential to have widespread impact and to threaten the free speech of all internet users.

The ruling is bigger than a loss for Meta, which has the resources to defend itself against these lawsuits. The court’s ruling signals that all online services (and internet users) that host others’ speech—including those without Meta’s deep pockets—must bear the burden and expense of fighting lawsuits that Section 230 ultimately precludes. This will have real consequences, incentivizing online services to take down users’ speech in response to spurious legal threats, filter speech preemptively, or simply stop offering a place for people to speak online. So even though some may think that Meta is not a sympathetic company, the ruling should raise concerns for anyone who cares about an open and free internet.

Immunities from Suit Advance Important Public Interests

A little procedural background is necessary to understand the implications of the Ninth Circuit’s ruling.

Meta had moved to dismiss a group of social media addiction cases brought by state attorneys general, school districts, and local governments. Meta argued that Section 230(c)(1) immunity applies because the plaintiffs’ claims, framed as seeking to hold Meta liable for allegedly harmful platform features, really seek to hold the company liable for publishing decisions related to third-party content. Section 230 is one of the most important laws supporting online free speech, because its protections for online services enable them to distribute users’ speech at an unprecedented scale.

The district court ruled that Section 230 does not apply to certain features (and does apply to others) and so denied the motion to dismiss on the claims related to those features. Meta immediately appealed invoking appellate jurisdiction under 28 U.S.C. § 1291, but the question before the Ninth Circuit was whether the appeal was legally appropriate.

Under Section 1291, U.S. circuit courts generally only have jurisdiction to hear appeals of “final decisions” from the district courts. Final decisions are trial court orders ending a case, or come after a trial on the merits. Section 230 appellate cases often arise from a district court’s grant of a defendant platform’s motion to dismiss the plaintiff’s case based on Section 230. Typically, a district court’s denial of a defendant’s motion to dismiss is not a final order—it simply means that the case may continue to discovery and summary judgment or trial, after which time an appeal would be appropriate.

However, federal law allows for “interlocutory appeals,” which are appeals of orders that do not end a case but nonetheless are allowed because they involve important legal issues. For example, there is an exception to Section 1291 called the “collateral order doctrine”—at issue in this case—allowing for immediate appeal if, as the Ninth Circuit explained here, “holding a trial would imperil a substantial public interest.”

Inherent in the collateral order doctrine is the consideration of whether an immunity like Section 230 provides mere “immunity from liability” or a more robust “immunity from suit.”

An immunity from liability does not require an immediate appeal and so demands that Section 1291’s final order rule be followed. That’s because waiting until the end of a case before an appellate court can consider the trial court’s denial of immunity does not prejudice the defendant. The appellate court may overturn the trial court and grant the immunity, and thus the defendant’s right to be immune from liability would be vindicated on appeal.

Immunity from suit is different. It means that the public interest demands that a defendant be able to get out of a case as early as possible and avoid having to litigate the case to the end. The U.S. Supreme Court has held, for example, that qualified immunity is such an immunity, and that a district court’s denial of qualified immunity for a government official is immediately appealable under Section 1291, notwithstanding the lack of a final order. The idea is that the public interest is served when government officials are free to act without fear of consequences when established rights are not implicated, and so determining as soon as possible whether their acts are immune serves that public interest.

Here, the Ninth Circuit held that the district court’s denial of Section 230 immunity for Meta was not immediately appealable under Section 1291’s collateral order doctrine because the immunity is not from suit, but rather from ultimate liability. The panel’s absurd result contravenes the text of Section 230, the statute’s policy goals, and the court’s own prior rulings.

Treating Section 230 as an Immunity from Suit Protects Online Free Speech

Meta rightly argued that Section 230(e)(3) plainly states, “No cause of action may be brought and no liability may be imposed under any State or local law that is inconsistent with this section.” The panel dismissed this argument, stating that this language likely amounts to “redundancy” reflecting only immunity from liability. The court failed to side with the more reasonable position that statutory language should generally not be interpreted as superfluous.

Meta also reminded the panel that the Ninth Circuit has many times over the past two decades framed Section 230 as both an immunity from liability and an immunity from suit. The panel also dismissed this argument, stating, “It is true that we have used the phrase ‘immunity’ somewhat loosely in our section 230 jurisprudence.”

But “loosely” is a gross mischaracterization—the panel did not discuss a seminal prior ruling, Fair Housing Council of San Fernando Valley v. Roommates.com (2008), in which the entire Ninth Circuit, not just a three-judge panel, explicitly ruled that Section 230 is also an immunity from suit. That court rightly explained that Section 230 “must be interpreted to protect websites not merely from ultimate liability, but from having to fight costly and protracted legal battles.”

Why is it important that social media platforms and other internet intermediaries (and their users) have immunity from suit for engaging in publishing activities related to third-party content—and thus a right to immediately appeal when Section 230 immunity is denied?

The Ninth Circuit panel here, using their own words, failed to “evaluate the interests that would be lost through rigorous application of a final judgment requirement” and failed to consider the “substantial public interest” served by treating Section 230 as an immunity from suit.

Section 230 immunity, contrary to what some argue, is not a gift to Big Tech—it applies to all internet intermediaries, big and small, from the large social media companies to smaller entities like community message boards and local ISPs. It even protects internet users who forward others’ emails or host comments on their blogs. In turn, the law supports the free speech of all internet users.

While it is helpful when an internet intermediary can ultimately benefit from Section 230 immunity, if a trial court’s early denial is not immediately appealable, that means the intermediary must bear the extended logistical and financial burdens of defending itself. Under the Ninth Circuit’s logic, anyone hosting others’ speech online would have to endure the pain and expense of discovery, summary judgment, or trial, before they ultimately can be protected by Section 230.

Congress crafted Section 230 to give internet intermediaries legal breathing room, so that they will be incentivized to facilitate online communication and commerce, allowing the rest of us to go online with minimal barriers to entry, without needing to have loads of money or to know how to code. Congress acknowledged in Section 230 itself, “Increasingly Americans are relying on interactive media for a variety of political, educational, cultural, and entertainment services.”

Yet if platforms, especially smaller platforms, know that they will have to defend themselves for years in court before they can ultimately benefit from Section 230 immunity, this alone will create a perverse incentive, as we have explained, to censor user speech, in order to reduce the platforms’ legal exposure. And this incentive is only exacerbated at scale, where the sheer volume of user-generated content hosted by modern platforms makes legal risk astronomical.

Unfortunately, this opinion seems to be part of larger trend reflecting the Ninth Circuit’s increasing disdain for Section 230, and apparently for free speech rights more broadly. The court similarly held last year in Gopher Media v. Melone (2025)—overruling itself—that a trial court’s denial of a defendant’s anti-SLAPP motion also is not immediately appealable under the collateral order doctrine. This is despite the fact that, similar to Section 230, California’s anti-SLAPP law is intended to allow defendants to get harassing lawsuits meant to silence them dismissed early, lest they be chilled from engaging in lawful speech on public issues due to the risk of being mired in litigation, even if they ultimately win a delayed appeal.

Developers: Beware of Ad Libraries that Betray Your Users’ Location Privacy

4 August 2026 at 21:30

Across mobile platforms, advertising companies provide developers with software development kits (SDKs) that make it easy to monetize their apps. But those same SDKs can automatically feed users’ location data into ad systems that location data brokers use to track people. Many developers may not even be aware of this privacy violation, let alone the users who are directly affected.

When developers let advertising SDKs collect location data, they’re putting users at risk of more than just creepy ads. Location information sourced from the advertising industry has been used for ICE investigations, global spy tools, outing a gay priest, tracking union organizers, and tracking US military personnel.

Defaults matter, not just for users, but for app developers as well.

An EFF investigation has identified several advertising SDKs that publicly acknowledge collecting and sharing users’ location by default when embedded in Android apps granted location permissions. Defaults matter, not just for users, but for app developers as well. If app developers don’t pay close attention to the location-sharing settings of their advertising tools, they could inadvertently expose users’ location information.

This report explains how advertising SDKs can facilitate and encourage location data sharing through privacy-invasive defaults, financial incentives, and unclear documentation.

Contents:

Data Brokers Harvest Location Information From Advertising Systems

When an advertising SDK collects and shares location data, it becomes part of a larger ecosystem that can include advertisers, ad tech companies, and location data brokers. EFF began investigating the location-sharing practices of various advertising SDKs to better understand the pipeline from mobile apps to location data brokers.

Location data brokers sell information on the precise movements of billions of people without their knowledge or meaningful consent. This data is primarily sourced from apps on people’s phones. Some apps partner with data brokers directly, using data-broker-developed SDKs or server-to-server transfers to sell users’ location data. Other apps leak users’ location data through advertising SDKs serving behaviorally-targeted ads through “real-time bidding” (RTB). In the process of auctioning off ad space, ad tech companies can broadcast user data to thousands of potential advertisers. Location data brokers have participated in these auctions not just to bid on ad space, but to collect personal information contained in bid requests. 

Indiscriminate data sharing through RTB can lead app developers to unknowingly share their users’ location with data brokers. In 2025, a hack of location data broker Gravy Analytics revealed thousands of apps that may have been sources of its data. When journalists reached out to the app developers, many claimed they had no relationship with or knowledge of Gravy Analytics. To prevent location information from being shared with data brokers through RTB, developers must understand the location-sharing practices of their advertising SDKs.

How Advertising SDKs Leak Location Data

Developers don’t have to manually, or even intentionally, share location data for it to be broadcast through RTB auctions. Once a user grants an app permission to access their location, SDKs embedded in the app receive the same access—there are no SDK-specific location permissions. That means advertising SDKs can automatically collect users’ location data and share it in bid requests.

While apps and SDKs can estimate a users’ approximate location from their IP address without requesting any permissions, location permissions provide access to estimates that are more accurate and revealing. Precise location permissions give apps (and their embedded SDKs) access to location estimates within about 160 feet, but sometimes as accurate as 10 feet. Approximate location, a separate permissions level, gives apps access to a location estimate within about 1.2 square miles. 

Developers and advertising SDKs also have a financial incentive to share location data, since it can increase bid prices for an app’s ad space. While many advertising SDKs require developers to configure a setting before collecting and sharing users’ location data in ad requests, this is not always the case. EFF found several advertising SDKs who publicly acknowledge sharing users’ location data by default when embedded in apps granted location permissions. 

EFF Identified Advertising SDKs That Share Location Data by Default

EFF reviewed the public developer documentation of dozens of widely-used advertising SDKs to identify how they handle and communicate with developers about location data. In the following sections, we highlight four advertising SDKs who engage in a particularly egregious practice: collecting a user's location by default for ad targeting whenever a user has given an app location permissions. We reached out to each SDK company and the referenced app developers for comment. One company responded, and as detailed below, subsequently updated its documentation in response to our questions. Another company responded with clarifications to its developer documentation.

We chose to focus on SDKs with this privacy-invasive default because it increases the risk of developers leaking users’ location data without realizing it. Several studies have found that developers tend to stick to SDKs’ default settings. If an advertising SDK transmits location data by default, users' precise location can end up in advertising systems without the developer intentionally enabling location sharing. These SDKs have separate documentation pages that instruct developers to flag users covered by privacy laws like GDPR and COPPA for restricted data processing, but these modes are not the default. 

By analyzing how these four SDKs present their location sharing practices to developers, we hope to illustrate how the design and documentation of advertising SDKs can facilitate location data sharing at scale. Although the advertising SDKs we highlight are not the most prevalent SDKs used, they are embedded in thousands of apps and reach billions of users.

InMobi Encourages Keeping Location Sharing Enabled By Highlighting Financial Incentives

InMobi claims to reach “2B+ users across 150+ countries” and is the 10th most popular advertising SDK on Android (according to AppBrain and Appfigures at the time of publication). 

InMobi’s “Getting Started with Android SDK Integration” suggests that location sharing is enabled by default, stating “The InMobi SDK automatically forwards location signals when available.” InMobi provides developers with a setting to opt out, but explicitly recommends sharing location data. Developer documentation highlights the financial incentive for location sharing, stating “location-enriched impressions typically yield higher revenue.” 


[Observed on “Getting Started with Android SDK Integration,” 7/31/26]

Apps that use InMobi may not need location information to function or may only need access to approximate location information, but InMobi highly recommends that developers request precise location permissions “to enable accurate ad targeting.” They even encourage developers to request Wi-Fi network information permissions, which (when paired with precise location permissions) provide Wi-Fi access point identifiers that can also be used for location tracking.


[Observed on “Getting Started with Android SDK Integration,” 7/31/26]

InMobi has been accused of misleading developers over location sharing practices in the past: In 2016, they settled with the FTC over charges that they bypassed users’ location permissions for apps and tracked their precise locations through WiFi network data (Android now requires apps to request location permissions to access this WiFi data too).

BidMachine Updates Previously Inaccurate Developer Documentation After EFF's Technical Analysis Observed Precise Location Data Collection

BidMachine claims to reach over 600 million “direct SDK users.” 

BidMachine reveals that it collects location data by default on the “Advanced Settings” page of its Android SDK Integration guide, stating that the “SDK can automatically track user device location to serve better ads” as long as developers request location permissions for their app. Before publication, EFF reached out to BidMachine for comment, notifying them of our plan to highlight their Android SDK location sharing practices.  


[Observed on “Advanced Settings” on 7/31/26, before EFF asked BidMachine for comment]

After EFF reached out, BidMachine changed their documentation to clarify the practice, but not their default collection of location information once app-level permissions are granted. This updated section still fails to explain how developers can opt out of BidMachine location tracking, which is critical for app developers that require location access for core features but wish to prevent user data from being shared with advertisers.


[Observed on “Advanced Settings” on 8/3/26, after EFF asked BidMachine for comment]

Before EFF reached out, BidMachine’s “App Privacy Details On Google Play” page had stated that they only collected coarse location data and precise location data was “not collected.” However, our technical analysis of two apps, which Exodus Privacy determined include the BidMachine SDK, contradicted this claim: Network requests from the apps QR Scanner and GPS Speedometer to a BidMachine domain include precise location coordinates.


[Observed on “App Privacy Details On Google Play” on 7/31/26, before EFF asked BidMachine for comment]

After EFF reached out, BidMachine also corrected its documentation to make it clear precise location is collected by the SDK whenever the app-level permission is granted:


[Observed on “App Privacy Details On Google Play” on 8/3/26, after EFF asked BidMachine for comment]

com.appswing.qr.barcodescanner.barcodereader_bidmachine.flows

com.ktwapps.speedometer_bidmachine.flows

In response to our request for comment, BidMachine stated that it wasn't possible for them to get location information “unless the user has granted the app the relevant permission through the operating system.” They also stated that“publishers are responsible for configuring their apps' permission and consent flows.”

Verve Emphasizes Consent More in its Play Store Language Than its Configuration Guide 

Verve has claimed its HyBid SDK reaches “over 1.5 billion users across more than 10,000 apps worldwide.” 

Verve’s configuration guide for its HyBid Android SDK (formerly called Pubnative HyBid) makes clear that location tracking is “enabled by default,” stating, “If the user has given location permissions, HyBid SDK will use the available user location to provide better targeted ads.” 


[Observed on “HyBid Android SDK - HyBid Configuration,” 7/31/26]  

Verve’s guidance for data disclosure to the Google Play Store tells a more careful story. Despite the fact that location tracking is enabled by default, the Google Play Data Safety Guidance states that the SDK “does not collect or attempt to collect [location] information independently.”


[Observed on “Google Play Data Safety Guidance,” 7/31/26]  

It also emphasizes user consent, claiming the SDK will only collect location data “if the publishers allows its app to collect location data from users after obtaining user’s explicit consent to such data collection” (emphasis added). The configuration guide lacks recommendations or instructions for obtaining user consent to share location data with Verve, beyond app-level access. Instead, the configuration guide highlights the financial incentives for developers to add location permissions to their app.


[Observed on “HyBid Android SDK - HyBid Configuration,” 7/31/26]  

When reached for comment, Verve clarified that “in its current Android implementation, the SDK reads the cached network-provider location and does not use the GPS data of the end user's device. Furthermore, any geolocation data is coarsened prior to processing, ensuring that location is limited to an accuracy radius of no less than 1,850 feet.” It also said that it contractually requires apps to comply with data protection laws. 

To Verve’s credit, the HyBid SDK is open source, so careful developers can check the code instead of relying on documentation alone. HyBid’s open-source code shows that latitude and longitude coordinates are rounded to two decimal places, and that it does only collect and share network-derived location data, confirming the statement the company sent to us. If an app has precise location permissions, networked-derived location data rounded to two decimal places could be accurate within approximately 0.5 square miles, which is still more precise than the 1.2 square miles typically revealed with Android’s approximate location permission. But even coarse location data, especially when collected repeatedly over time, can reveal movements that should remain private by default.

Verve’s response also conveyed a willingness to revise their documentation: “As part of our ongoing commitment to providing clear and comprehensive developer resources, we continually review and enhance our documentation, and we will take your observations into account as part of that process.”

Huawei Highlights Financial Incentives for Location Data Sharing Before Showing Developers How to Opt Out

Huawei has claimed its Petal Ads SDK is embedded in more than 85,000 apps worldwide.

Huawei’s “Integrating the Petal Ads SDK into an Android App” guide begins with a recommendation that developers obtain location permissions to increase app revenue and an acknowledgement that location sharing will happen by default in apps with location permissions.


[Observed on “Integrating the Petal Ads SDK into an Android App,” 7/31/26]

A separate “Use of Location Data for Ads” page repeats that the Petal Ads SDK will include users’ location information in ad requests if an app has access to location information. Neither of those pages mention that developers can use the setRequestLocation method to disable the default collection of location information (this setting is referenced in the last section of the Ads SDK Compliance Guide). Huawei’s Ads SDK Privacy Statement states that “The SDK and its services will not store precise location information, and will only use it to determine the approximate device location.” However, the guide does not specify how Huawei defines approximate versus precise location data. 


[Observed on “Use of Location Data for Ads,” 7/31/26]

Location Data Sharing Can Happen Without Users’ Knowledge or Meaningful Consent 

In some cases, after an app itself obtains location permission, advertising SDKs can separately obtain and share users’ location information without their knowledge or meaningful consent. Neither app that EFF observed sharing precise location data with BidMachine (QR Scanner and GPS Speedometer) showed a notice or requested consent before doing so. Additionally, neither apps’ Google Play Store “Data safety” section includes location data under “This app may share these data types with third parties.” The lack of transparency and control that users have over their location on mobile apps is dangerous. QR Scanner and GPS Speedometer are just two examples of apps that quietly share users’ location data through advertising SDKs, but they have been downloaded more than 50 million and 10 million times, respectively. 

App-level location permissions alone cannot signal meaningful consent to location collection and sharing by third-party advertising SDKs.

Even if users’ were to grant these apps permission to obtain their location data, they would likely not expect their location data to be shared with third parties. Many users don’t know that granting location permissions to an app grants the same permissions to third-party SDKs embedded in the app, or that an app they're using contains code from outside companies. And many apps that request location permissions, like GPS Speedometer, require it for core functionality. App-level location permissions alone cannot signal meaningful consent to location collection and sharing by third-party advertising SDKs.

Location Privacy Issues Extend Beyond These Four SDKs

Our initial focus on four advertising SDKs does not mean that other SDKs adequately protect location data or that developers never choose to share location data when it’s not the default. Advertising SDKs not discussed in this report have been criticized and sued for allegations that they collect location data without valid user consent. 

The issues we’ve highlighted around privacy-invasive defaults, financial incentives, and unclear documentation extend beyond the specific SDKs we analyzed. Multiple studies have found that advertising SDKs often steer developers toward increased data collection through their design and documentation. A 2021 study found that popular advertising SDKs used dark patterns to nudge developers towards sharing more sensitive data. A 2024 study identified discrepancies between several SDKs’ documentation and their actual data collection practices. And a 2025 study concluded that developers have minimal influence over SDKs’ data transmission, often leaving them with the choice of accepting SDKs' invasive data collection or avoiding them entirely. 

Fighting Back Against AdTech Companies That Enable and Encourage Location Data Sharing 

EFF’s analysis shows that advertising SDKs don’t just allow developers to share location data–they often encourage it. Default settings, financial incentives, and unclear documentation can make sharing users’ location the easiest option for developers.

Users can take extra steps to defend their location privacy, but they shouldn’t have to. Developers, regulators, and legislators must act to stop apps from leaking users’ location to advertising companies and data brokers.

Developers

Developers should carefully evaluate all third-party SDKs they include in their apps and disable unnecessary data collection whenever possible. Regardless of advertising SDKs’ default settings, developers have a responsibility to protect their users’ location data. But protecting users’ privacy shouldn’t depend on developers reading the right piece of SDK documentation. Advertising SDKs should not make sharing personal data the default, especially for data as sensitive as a person’s location. 

Regulators

Regulators should continue to hold app developers accountable when they unlawfully share personal data and include libraries which subject users to privacy harms, as they have in the past. But they should also scrutinize the companies whose SDKs encourage these practices at scale. Otherwise, companies can continue to design SDKs that make invasive data sharing the default while shifting the responsibility and consequences to developers who include their tools. 

Legislators

The US is in dire need of a federal law to protect all Americans’ location privacy, one which doesn’t preempt stronger state privacy laws, and has a private right of action empowering individuals to sue those who violate their privacy. Countries across the globe should likewise enact legislation that protects their users’ location privacy. Everyone deserves privacy as a universal human right.

Legislators can address the root of the problem by banning online behavioral advertising. This would remove the primary incentive for companies to track and share your personal data. It would also prevent users' precise locations from being broadcast to data brokers through RTB auctions. 

Until then, developers should be wary of ad libraries that betray their users’ location privacy.

Notes on Methodology

We were interested in looking at network traffic for various Android ads SDKs that send precise location by default when granted location permissions. We chose Android for this investigation because of the relative openness of and our familiarity with analysis on the platform. We’ve used publicly available resources like Exodus Privacy and AppBrain to identify popular ads SDKs and the apps which include them.

In a lab setting, we set up a machine to view our own http(s) traffic using mitmproxy from our test device, and connect the test device to that machine in order to view our real-time traffic.  Where needed, we use the dynamic instrumentation toolkit Frida to ensure the traffic we generate can be analyzed.

We’ve included flows files in this post, which can be opened in mitmproxy to show the requests we’ve observed with location coordinates.

Measuring LLMs’ Ability to Perform Cryptanalysis

29 July 2026 at 03:47

There’s new benchmark measuring AI’s ability to perform mathematical cryptanalysis. Anthropic’s frontier model actually found new attacks.

The benchmark: “CryptanalysisBench: Can LLMs do Cryptanalysis?” The idea is to benchmark the ability of LLMs to discover new mathematical cryptanalytic attacks against a series of historical algorithms.

Abstract: Cryptanalysis—the task of finding attacks against cryptographic schemes—its at the intersection of mathematical reasoning and cybersecurity, two areas where LLMs have advanced fastest. Cryptanalysis represents both a clean testbed for frontier reasoning (as practical attacks can be automatically verified) and a domain with unusually high stakes, since the primitives under study underpin our digital security. In this paper we ask whether LLMs can do cryptanalysis, and find that the answer is increasingly yes. We introduce CryptanalysisBench, 191 tasks across six families of cryptographic primitives (block ciphers, hash functions, etc.) drawn primarily from four NIST standardization competitions. Our benchmark consists of three tiers: (i) primitives with known practical breaks; (ii) primitives with no known practical break, evaluated both at full strength and as scaled-down variants; and (iii) a challenge set of production primitives at the frontier of cryptanalysis. Five frontier models (Claude Opus 4.8, Sonnet 5, Mythos 5, GPT-5.5, and the open-weights GLM-5.2) break 65%­86% of Tier 1 schemes, 6­12 Tier-2 schemes at full strength, and 24­61 across all scaled-down variants. Beyond deriving known results, models produce novel cryptanalysis, such as a key-recovery attack that exploits a design flaw in the SpoC AEAD and an error in KINDI’s published CCA-security proof, both to the best of our knowledge not previously known.

We release CryptanalysisBench as a tool to help track if (or when) AI cryptanalysis becomes a serious factor and as a scaffold for stress-testing candidate schemes before deployment. The attacks that the benchmark already surfaces are an early snapshot of a fast-moving frontier that may soon match, and in places exceed, the published state of the art.

Anthropic used the benchmark to test Mythos Preview, and found new vulnerabilities in Hawk and reduced-round AES.

Still early results, but this is definitely something to watch.

SlashDot thread.

The Fourth Circuit Says Border Agents Can Search Your Phone By Hand, No Suspicion Required

23 July 2026 at 00:30

Legal intern Suzanne Castillo was the principal author of this post.

The Fourth Circuit issued a disappointing opinion in U.S. v. Belmonte Cardozo, a case in which EFF filed an amicus brief, alongside the national ACLU, its Maryland, North Carolina, South Carolina, and Virginia affiliates, and the National Association of Criminal Defense Lawyers (NACDL).

We argued that electronic device searches at the border should require a warrant based on probable cause, but at minimum, regardless of whether an officer searches by hand or with forensic software that plugs into a device and downloads its entire contents for search, the same Fourth Amendment standard should apply to all device searches at the border.

Unfortunately, the court rejected that argument and ruled that a lower standard applies to manual searches, allowing the government to conduct extraordinarily invasive electronic device searches without any suspicion of wrongdoing, simply because the border officer chooses to search by hand rather than with a forensic tool.

The Border Search Exception Meets Your Phone

The Fourth Amendment requires that government searches of persons or property be reasonable, which usually means obtaining a warrant based on probable cause from a judge.

But a warrantless search can still be reasonable if it falls within an exception to the warrant requirement, including the exception that allows officers to search your belongings at the border. The border search exception allows warrantless searches of persons or property crossing the U.S. border, including the functional equivalent of the border such as international airports, given the government’s interests in controlling who and what may enter the country.

Historically, courts have categorized border searches of luggage, vehicles, and personal effects as “routine” and thus reasonable even if conducted without any suspicion that the traveler has engaged in wrongdoing; courts have also held that more invasive “nonroutine” searches, such as certain body searches and searches that damage property, require reasonable suspicion.

But a person’s privacy interests in the personal data on a phone or laptop are extraordinarily different than their limited privacy interests in the contents of their suitcase.

The Supreme Court addressed cell phone privacy in Riley v. California (2014), holding that the search-incident-to-arrest exception to the warrant requirement did not apply to cell phones, thereby generally requiring a warrant for phone searches, at least at the interior of the country. The court recognized the unprecedented privacy interests people have in their cell phones and how even brief manual searches can reveal the “sum of an individual’s private life,” including our political affiliations, religious beliefs, sexuality, and more. Accordingly, the Supreme Court held that because electronic device searches bear “little resemblance” to searches of bags or physical containers, they should be evaluated differently.

Following Riley, the Fourth Circuit considered two border device search cases involving forensic searches, in which border officers used external software to extract and analyze a device’s data.

In U.S. v. Kolsuz (2018), the Fourth Circuit held that a forensic search of a cell phone at the border “must be considered a nonroutine border search, requiring some measure of individualized suspicion” of a transnational offense, but the court declined to decide whether the standard is only reasonable suspicion or instead a probable cause warrant.

Then in U.S. v. Aigbekaen (2019), the Fourth Circuit held that a forensic device search at the border in support of a purely domestic law enforcement investigation requires a warrant. The court also reiterated the general Kolsuz rule for a forensic border-related device search: the “Government must have individualized suspicion of an offense that bears some nexus to the border search exception's purposes of protecting national security, collecting duties, blocking the entry of unwanted persons, or disrupting efforts to export or import contraband.”

In Belmonte Cardozo, manual searches were finally before the court.

A Disappointing Decision

Jose Belmonte Cardozo was already on the U.S. government’s radar when he traveled from Bolivia to the U.S. and was met by a U.S. Customs and Border Protection (CBP) officer at Washington Dulles International Airport. The officer manually searched his cell phone and found child sexual abuse material (CSAM), considered “digital contraband,” leading to Belmonte Cardozo’s arrest and criminal prosecution.

At issue on appeal was what standard should apply to manual device searches at the border. The Fourth Circuit held that, unlike forensic searches, manual searches are “routine” and thus reasonable under the Fourth Amendment without a warrant or individualized suspicion.

The court’s holding hinged on four differences between manual and forensic searches: (1) in a manual search, a person does the searching, not a machine; (2) a manual search’s breadth depends on the officer’s time and energy, while forensic searches are comprehensive; (3) manual searches reveal only what a user can typically access, while forensic searches can uncover deleted files, cached fragments, metadata, and more; and (4) manual searches are subject to an officer’s fading memory or imperfect notes, while forensic searches create a permanent copy.

But in identifying these technical differences, the court never explains why they justify a lower standard for manual searches.

The Fourth Circuit’s holding is problematic because, as we argued in our amicus brief, manual searches reach the same categories of data as forensic searches—data that can reveal highly personal aspects of our identities and our lives. It does not matter if a search is conducted by an agent’s thumbs or by software: the end result is equally as invasive, therefore all device searches should fall under the warrant requirement, or at least the same Fourth Amendment standard.

The court repeatedly emphasized that the search here lasted only two minutes, suggesting that the time-limited search was not privacy-invasive. But an individual’s privacy interests in their personal data don’t change based on how their phone is searched or how long. Scrolling for two minutes through someone’s personal text messages or photos is an invasion of privacy that may reveal intimate details about the person even in that short period of time.

Moreover, as devices’ native search functions improve, manual searches can surface personal information in seconds through keyword searches, even for photos, where it might have taken an hour of scrolling to find the same information, further showing that a time-limited search is not necessarily less privacy-invasive. What matters is not the breadth of the search itself, but the unprecedented (and growing) breadth of data on our phones.

A Silver Lining

There’s one silver lining: by relying on the fact that the search lasted two minutes, the Fourth Circuit left open the possibility that lengthier manual searches could trigger heightened suspicion requirements. But until a clear line is drawn, border officers within the Fourth Circuit’s jurisdiction can use manual searches to sidestep heightened Fourth Amendment standards that would otherwise apply. In the meantime, EFF will keep fighting against extraordinarily invasive warrantless, suspicionless device searches at the border, and for robust privacy standards to protect our most personal data.

EFF and Allies: X’s FTC Petition to Waive Privacy Violation Order Should be Rejected

2 July 2026 at 17:04

X Corp. should not be able to escape privacy compliance because it changed its name. 

On May 15, X Corp. filed a petition before the Federal Trade Commission (FTC) to set aside or modify an order issued in 2022 requiring the company to report regularly to the FTC for its violations of user data. The order or “consent decree” is a result of misleading the platforms’ 140 million users by using private information given to secure accounts, like phone numbers and email addresses, for targeted advertising. It also fined the company $150 million for the infraction. As part of an open comments period, EFF and allies including Demand Progress Education Fund (DPEF), National Consumers League (NCL) and Electronic Privacy Information Center (EPIC) call on the FTC to reject this petition.

The 2022 order was a renewal of an order stemming from a previous violation. Back in 2011, Twitter (now X) reached a settlement with the FTC after the regulator found Twitter had failed to secure users’ personal information, resulting in exposure of that data to hackers. The settlement banned the company from misrepresenting its data protection measures, required it to set up safeguards on user data, and regularly report its security posture for twenty years. The renewal updated the expiration of X’s obligations to 2042, but if the FTC accepts X's petition, it would end much sooner.

In arguing to set aside the order, X remarks that since the order in 2011 it has “built an entirely new privacy and information security program staffed by new personnel operating under new leadership with a … philosophy grounded on the importance of privacy and information security.” 

These sweeping assurances that corporate restructuring led to a fundamental change in X’s policy and practices around user data should be met with a healthy dose of skepticism, given evidence to the contrary. For example, the company’s quiet rollout integrated its AI model Grok with the platform in 2024, trained (without meaningful consent) on X user data. The company was also subject to a massive data breach in 2025. Even if a rotation of leadership led to prioritizing privacy and information security, our letter highlights that this would not be sufficient grounds to remove the order, “because the FTC orders bind the corporate entity. Those obligations do not dissolve when the employees who negotiated or administered it depart.”

X argues that its entry into the AI space should be reason not to continue the oversight, claiming that “terminating the Order is critical to advancing American leadership in artificial intelligence.” Here again, broad-stroke claims that the guardrails in place “[diverts] engineering resources from innovation to compliance paperwork” ignores the dangers that AI introduces to user data. Far from being a reason to waive the order, clever attacks on models trained on user data has the ability to supercharge the types of secondary use violations that led to the 2022 order renewal. After all, an entire art has been developed around engineering LLM prompts to reveal the data a model was originally trained on.

Our response to X’s petition debunks many claims the company uses in its arguments. For example, there’s little evidence the order placed an undue financial burden on X. In our letter, we note that the compliance cost is merely “a rounding error against the $200 billion valuation of X Corp. following the xAI merger.”

Strong safeguards on our information require eagle-eyed oversight when that data is abused and misused for profiteering ventures. X’s actions not only showed us this in the past, but continue to do so in the present day. We and our civil society partners urge the FTC to take the clear, sensible path and reject X’s petition.

Move Fast, Surveil Things

4 June 2026 at 22:08

Update, June 8, 2026: Following widespread public scrutiny and WIRED’s critical reporting, Meta has stripped the unactivated facial recognition code from its latest Meta AI app update.

Meta has deployed facial recognition code to millions of their always-on surveillance glasses, according to new reporting by Wired. EFF’s Threat Lab was able to confirm that the facial recognition code is present through static analysis of the application. 

This dangerous new Meta functionality stores faceprints as a series of 2,048 numbers uniquely representing the positioning of a person’s facial features. When this feature is activated, it will convert every new face in the sightlines of the surveillance glasses into a series of numbers, and compare it to all the existing faceprints in the user’s database.

Wired and EFF confirmed that the code is present and active, though not yet exposed to consumers. Another researcher confirmed that when they manually added a face to the app database by connecting the phone to a computer in debug mode and issuing a few commands, the glasses would subsequently detect that face when it came into view. 

Meta has already paid $650 million to settle a BIPA lawsuit challenging mass facial recognition of every photo posted to its platform, a feature which it has since shut down. 

Despite the billions of reasons not to, Meta seems to have created the capacity to turn their customers into a distributed surveillance machine. This is just one more reason to think twice before buying or using Meta’s surveillance glasses. 

Considering that Meta previously wrote in an internal document that they want to launch facial recognition “during a dynamic political environment where many civil society groups that we would expect to attack us would have their resources focused on other concerns," this invasive new feature doesn't come as a surprise. But Meta's surveillance plans won't escape public scrutiny that easily, and we'll be watching if this feature is rolled out to the public. 

Getting Digital Fairness Right: EFF's Recommendations for the EU's Digital Fairness Act

4 May 2026 at 17:33

Digital Fairness in the EU

The next few years will be decisive for EU digital policymaking. With major laws like the Digital Services Act, the Digital Markets Act, and the AI Act now in place, the EU is entering an enforcement era that will show whether these rules are rights-respecting or drift toward overreach and corporate control. With the proposed EU’s Digital Fairness Act (DFA), the Commission is now turning to increasingly visible risks for users, such as dark patterns and exploitative personalization. Its “Digital Fairness Fitness Check” makes clear that existing consumer rules need updating to reflect how digital markets operate today.

But not all proposed solutions point in the right direction. Regulators are already flirting with measures that rely on expanded surveillance, such as age verification mandates—surface-level fixes that risk undermining fundamental rights while offering little more than a false sense of protection.

For EFF, digital fairness means addressing the root causes of harm, not requiring platforms to exert more control over their users. It means safeguarding privacy, freedom of expression, and the rights of users and developers.

If the DFA is to make a real difference, it must tackle structural imbalances. Lawmakers should focus on two interlocking principles. First, prioritize privacy. Reforms should address harms driven by surveillance-based business models, alongside deceptive design practices that impair informed choices. Second, strengthen user sovereignty, which is also a necessary precondition for European digital sovereignty more broadly. Strengthening user sovereignty means taking measures that address user lock-in, coercive contract terms, and manipulative defaults that limit users’ ability to freely choose how they use digital products and services.

Together, these principles would support the EU’s objectives of consistent consumer protection, fair markets, and a more coherent legal framework. If implemented properly, the EU could address power imbalances and build trust in Europe’s digital economy.

Ban Dark Patterns

Dark patterns are practices that impair users’ ability to make informed and autonomous decisions. Many companies deploy these tactics through interface design to steer choices and influence behavior. Their impact goes beyond poor consumer decisions. Dark patterns push users to share personal data they would not otherwise disclose and undermine autonomy by making alternatives harder to access.

The DFA should address this by clearly prohibiting misleading interfaces that distort user choice in commercial contexts. While the Digital Services Act introduced a definition, it only partially bans such practices and leaves gaps across existing consumer law rules. The DFA should close these gaps by, at the very least, introducing explicit prohibitions and clearer enforcement rules, without resorting to design mandates.

Tackle Commercial Surveillance

At the core of digital unfairness lies the pervasive collection and use of personal data. Surveillance and profiling drive many of the harms regulators are trying to address, from dark patterns to exploitative personalization. The DFA should tackle these incentives directly by reducing reliance on surveillance-based business models. These practices are fundamentally incompatible with privacy and fairness, and they distort digital markets by rewarding data exploitation rather than quality of service. At a minimum, the DFA should address unfair profiling and surveillance advertising by strengthening privacy rights and banning pay-for-privacy schemes. Users should not have to trade their data or pay extra to avoid being tracked. Accordingly, the DFA should support the recognition of automated privacy signals by web browsers and mobile operating systems, which give users a better way to reject tracking and exercise their rights. Practices that override such signals through banners or interface design should be considered unfair.

Addressing surveillance and profiling also protects children, since many online harms are tied to the collection and exploitation of their data. Systems that serve ads or curate content often rely on intrusive profiling practices, raising concerns about privacy and fairness, particularly when applied to minors. Rather than turning to invasive age verification, the focus should be on limiting data use by default.

Strengthen User Sovereignty

There is a major gap in how EU law addresses user autonomy in digital markets: many digital products and services still restrict what people can do with what they pay for through opaque or one-sided licensing terms, technical protection measures, and remote controls. These mechanisms increasingly limit lawful use, modification, or access after purchase, allowing providers to revoke access, disable functionalities, or degrade performance over time. In practice, this turns ownership into a conditional rental.

Consumers must be able to use and resell digital goods without hidden limitations and with clear licensing terms. Too often, technical and contractual lock-ins, including remote lockouts and unilateral restrictions on functionality, erode that control. Recent legal reforms show that progress is possible. Rules such as those under the Digital Markets Act have begun to curb technical and contractual barriers and promote user choice. However, many restrictions persist.

The DFA must address these practices by targeting unfair post-sale restrictions and strengthening users’ ability to control and switch services. This means setting clear limits on unfair terms and misleading practices, alongside robust transparency on how digital services function over time. It should also strengthen interoperability and support user control, allowing people to access third-party applications and to let trusted applications act on their behalf, reducing lock-in and expanding meaningful choice in how users interact with digital services.

EFF to 9th Circuit (Again): App Stores Shouldn’t Be Liable for Processing Payments for User Content

24 April 2026 at 00:05

EFF filed an amicus brief for the second time in the U.S. Court of Appeals for the Ninth Circuit, arguing that allowing cases against the Apple, Google, and Facebook app stores to proceed could lead to greater censorship of users’ online speech.

Our brief argues that the app stores should not lose Section 230 immunity for hosting “social casino” apps just because they process payments for virtual chips within those apps. Otherwise, all platforms that facilitate financial transactions for online content—beyond app stores and the apps and games they distribute—would be forced to censor user content to mitigate their legal exposure.

Social casino apps are online games where users can buy virtual chips with real money but can’t ever cash out their winnings. The three cases against Apple, Google, and Facebook were brought by plaintiffs who spent large sums of money on virtual chips and even became addicted to these games. The plaintiffs argue that social casino apps violate various state gambling laws.

At issue on appeal is the part of Section 230 that provides immunity to online platforms when they are sued for harmful content created by others—in this case, the social casino apps that plaintiffs downloaded from the various app stores and the virtual chips they bought within the apps.

Section 230 is the foundational law that has, since 1996, created legal breathing room for internet intermediaries (and their users) to publish third-party content. Online speech is largely mediated by these private companies, allowing all of us to speak, access information, and engage in commerce online, without requiring that we have loads of money or technical skills.

The lower court hearing the case ruled that the companies do not have Section 230 immunity because they allow the social casino apps to use the platforms’ payment processing services for the in-app purchasing of virtual chips.

However, in our brief we urged the Ninth Circuit to reverse the district court and hold that Section 230 does apply to the app stores, even when they process payments for virtual chips within the social casino apps. The app stores would undeniably have Section 230 immunity if sued for simply hosting the allegedly illegal social casino apps in their respective stores. Congress made no distinction—and the court shouldn’t recognize one—between hosting third-party content and processing payments for the same third-party content. Both are editorial choices of the platforms that are protected by Section 230.

We also argued that a rule that exposes internet intermediaries to potential liability for facilitating a financial transaction related to unlawful user content would have huge implications beyond the app stores. All platforms that facilitate financial transactions for third-party content would be forced to censor any user speech that may in any way risk legal exposure for the platform. This would harm the open internet—the unique ability of anyone with an internet connection to communicate with others around the world cheaply, easily, and quickly.

The plaintiffs argue that the app stores could preserve their Section 230 immunity by simply refusing to process in-app purchases of virtual chips. But the plaintiffs’ position fails to recognize that other platforms don’t have such a choice. Etsy, for example, facilitates purchases of virtual art, while Patreon enables artists to be supported by memberships. Platforms like these would lose Section 230 immunity and be exposed to potential liability simply because they processed payments for user content that a plaintiff argues is illegal. That outcome would threaten the entire business models of these services, ultimately harming users’ ability to share and access online speech.

The app stores should be protected by Section 230—a law that protects Americans’ freedom of expression online by protecting the intermediaries we all rely on—irrespective of their role as payment processors.

Banning New Foreign Routers Mistargets Products to Fix Real Problem

8 April 2026 at 21:24

On March 23, the FCC issued an update to their Covered List, a list of equipment banned from obtaining regulatory approval necessary for U.S. sale (and thus effectively a ban on sale of new devices), to include all new routers produced in foreign countries unless they are specifically given an exception by the Department of Defense (DoD) or DHS. The Commission cited “security gaps in foreign-made routers” leading to widespread cyberattacks as justification for the ban, mentioning the high-profile attacks by Chinese advanced persistent threat actors Volt, Flax, and Salt Typhoon. Although the stated intention is to stem the very real threat of domestic residential routers being commandeered to initiate attacks and act as residential proxies, this sweeping move serves as a blunt instrument that will impact many harmless products. In addition to being far too broad, it won’t even affect many vulnerable devices that are most active in these types of attacks: IoT and connected smart home devices.

Previously, the FCC had changed the Covered List to ban hardware by specific vendors, such as telecom equipment produced by companies Huawei and Hytera in 2021. This new blanket ban, in contrast, affects the importation and sale of almost all new consumer routers. It does not affect consumer routers produced in the United States, like Starlink in Texas. While some of the affected routers will be vulnerable to compromises that hijack the devices and use them for cybercrime and attacks, this ban does not distinguish between companies with a track-record of producing vulnerable products and those without. As a result, instead of incentivizing security-minded production, this will only limit the options consumers have to US-based manufacturers not affected by the ban—even those that lack stellar security reputations themselves.

While the sale of vulnerable routers in the U.S. will not stop, the announcement quoted an Executive Branch determination that foreign produced routers introduce “a supply chain vulnerability that could disrupt the U.S. economy, critical infrastructure, and national defense.” Yet this move does nothing to address the growing number of connected devices involved in the attacks this ban aims to address. As we have previously pointed out, supply chain attacks have resulted in no-name Android TV boxes preloaded with malware, sold by retail giants like Amazon, fuelling the massive Kimwolf and BADBOX 2 fraud and residential proxy botnets. Banning the specific models and manufacturers we know produce dangerous devices putting its purchasers at risk, rather than issuing blanket bans punishing reputable brands that do better, should be the priority.

With the FCCs top commissioner appointed by the President, this ban comes as other parts of the administration impose tariffs and issue dozens of trade-related executive orders aimed at foreign goods. A few larger companies with pockets deep enough to invest in manufacturing plants within the U.S. may see this as an opportune moment, while others not as well poised to begin U.S. operations may attempt to curry enough favor to be added to the DoD or DHS exception lists. At best, this will result in the immediate effect of an ill-targeted policy that does little to improve domestic cybersecurity posture. At worst, it entrenches existing players and deepens problematic quid-pro-quo arrangements.

American consumers deserve better. They deserve the assurance that the devices they use, whether routers or other connected smart home devices, are built to withstand attacks that put themselves and others at risk, no matter where they are manufactured. For this, a nuanced, careful consideration of products (such as was part of the FCC’s 2023-proposed U.S. Cyber Trust Mark) is necessary, rather than blanket bans.

Another Court Rules Copyright Can’t Stop People From Reading and Speaking the Law

8 April 2026 at 20:13

Another court has ruled that copyright can’t be used to keep our laws behind a paywall. The U.S. Court of Appeals for the Third Circuit upheld a lower court’s ruling that it is fair use to copy and disseminate building codes that have been incorporated into federal and state law, even though those codes are developed by private parties who claim copyright in them. The court followed the suggestions EFF and others presented in an amicus brief, and joined a growing list of courts that have placed public access to the law over private copyright holders’ desire for control.

UpCodes created a database of building codes—like the National Electrical Code—that includes codes incorporated by reference into law. ASTM, a private organization that coordinated the development of some of those codes, insists that it retains copyright in them even after they have been adopted into law, and therefore has the right to control how the public accesses and shares them. Fortunately, neither the Constitution nor the Copyright Act support that theory. Faced with similar claims, some courts, including the Fifth Circuit Court of Appeals, have held that the codes lose copyright protection when they are incorporated into law. Others, like the D.C. Circuit Court of Appeals in a case EFF defended on behalf of Public.Resource.Org, have held that, whether or not the legal status of the standards changes once they are incorporated into law, making them fully accessible and usable online is a lawful fair use.

In this case, the Third Circuit found that UpCodes’s copying of the codes was a fair use, in a decision closely following the D.C. Circuit’s reasoning. Fair use turns on four factors listed in the Copyright Act, and the court found that all four favored UpCodes to some degree.

On the first factor, the purpose and character of the use, the court found that UpCodes’s use was “transformative” because it had a separate and distinct purpose from ASTM—informing people about the law, rather than just best practices in the building industry. No matter that UpCodes was copying and disseminating entire safety codes verbatim—using the codes for a different purpose was enough. And UpCodes being a commercial venture didn’t change the outcome either, because UpCodes wasn’t charging for access to the codes.

On the second factor, the nature of the copyrighted work, the Third Circuit joined other appeals courts in finding that laws are facts, and stand at “the periphery of copyright’s core protection.” And this included codes that were “indirectly” incorporated—meaning that they were incorporated into other codes that were themselves incorporated into law.

The third factor looks at the amount and substantiality of the material used. The court said that UpCodes could not have accomplished its purpose—providing access to the current binding laws governing building construction—without copying entire codes, so the copying was justified. Importantly, the court noted that UpCodes was justified in copying optional parts of the codes as well as “mandatory” sections because both help people understand what the law is.

Finally, the fourth factor looks at potential harm to the market for the original work, balanced against the public interest in allowing the challenged use. The court rejected an argument frequently raised by copyright holders—that harm can be assumed any time materials are posted to the internet for all to access. Instead, the court held that when a use is transformative, a rightsholder has to bring evidence of harm, and that harm will be balanced against the public benefit. Because “enhanced public access to the law is a clear and significant public benefit,” and ASTM hadn’t shown significant evidence that UpCodes had meaningfully reduced ASTM’s revenues, the fourth factor was at least neutral. It didn’t matter to the court that ASTM offered to provide copies of legally binding standards to the public on request, because “the mere possibility of obtaining a free technical standard does not nullify the public benefits associated with enhanced access to law.”

This is a good result that will expand the public’s access to the laws that bind us—something that’s more important than ever given recent assaults on the rule of law. In the future, we hope that courts will recognize that codes and standards lose copyright when they are incorporated into law, so that people don’t have to spend years and legal fees litigating fair use just to exercise their rights.

Congress Is Dropping the Ball with a Clean Extension of FISA

20 March 2026 at 23:20

Two years ago, Congress passed the “Reforming Intelligence and Securing America” Act (RISAA) that included nominal reforms to Section 702 of the Foreign Intelligence Surveillance Act (FISA). The bill unfortunately included some problematic expansions of the law—but it also included a relatively big victory for civil liberties advocates: Section 702 authorities were only extended for two years, allowing Congress to continue the important work of negotiating a warrant requirement for Americans as well as some other critical reforms. 

However, Congress clearly did not continue this work. In fact, it now appears that Congress is poised to consider another extension of this program without even attempting to include necessary and common sense reforms. Most notably, Congress is not considering a requirement to obtain a warrant before looking at data on U.S. persons that was indiscriminately and warrantlessly collected. House Speaker Mike Johnson confirmed that “the plan is to move a clean extension of FISA … for at least 18 months.” 

Even more disappointing, House Judiciary Chair Jim Jordan, who has previously been a champion of both the warrant requirement and closing the data broker loophole, told the press he would vote for a clean extension of FISA, claiming that RISAA included enough reforms for the moment.

It’s important to note RISAA was just a reauthorization of this mass surveillance program with a long history of abuse. Prior to the 2024 reauthorization, Section 702 was already misused to run improper queries on peaceful protesters, federal and state lawmakers, Congressional staff, thousands of campaign donors, journalists, and a judge reporting civil rights violations by local police. RISAA further expanded the government’s authority by allowing it to compel a much larger group of people and providers into assisting with this surveillance. As we said when it passed, overall, RISAA is a travesty for Americans who deserve basic constitutional rights and privacy whether they are communicating with people and services inside or outside of the US.

Section 702 should not be reauthorized without any additional safeguards or oversight. Fortunately, there are currently three reform bills for Congress to consider: SAFE, PLEWSA, and GSRA. While none of these bills are perfect, they are all significantly better than the status quo, and should be considered instead of a bill that attempts no reform at all. 

Mass spying—accessing a massive amount of communications by and with Americans first and sorting out targets second and secretly—has always been a problem for our rights.  It was a problem at first when President George W. Bush authorized it in secret without Congressional or court oversight. And it remained a problem even after the passage of Section 702 in 2008 created the possibility of  some oversight. Congress was right that this surveillance is dangerous, and that's why it set Section 702 up for regular reconsideration. That reconsideration has not occurred, even as the circumstances of the NSA, Justice Department, and FBI leadership, have radically changed. Reform is long overdue, and now it's urgent.  

Possible New Result in Quantum Factorization

16 March 2026 at 10:46

I’m skeptical about—and not qualified to review—this new result in factorization with a quantum computer, but if it’s true it’s a theoretical improvement in the speed of factoring large numbers with a quantum computer.

Malware Analysis, Threat Intelligence and Reverse Engineering: workshop slides

By: Bart
8 February 2018 at 21:31

Last month I gave a workshop for a group of 20-25 enthusiastic women, all either starting in infosec, or with an interest to start in this field.

For that purpose, I had created a full workshop: slides or a presentation introducing the concepts of Malware Analysis, Threat Intelligence and Reverse Engineering.

The idea was to convey these topics in a clear and approachable manner, both theory and in practice; for the latter, I had set up a custom VM, with Labs, including my own created applications, some with simple obfuscation.

All participants were very enthusiastic, and I hope to have sparkled most, if not some of them to pursue a career in this field. For this exact same reason, I am now releasing the presentation to the public - the VM and recordings however will not be published, as I created these solely for CWF.

You may however download the LAB material from Github below:
https://github.com/bartblaze/MaTiRe

Without any further ado, you may find the slides below, on SlideShare:


Any feedback is always appreciated.

I would also like to thank Nathalie for putting me in touch with Rosanna, the organiser of the CyberWayFinder program. And of course, my gratitude to all the attendees for making it!

Mind the disclaimer for the slides. License: CC Attribution-NonCommercial-NoDerivs License
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