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.

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.

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
• How Advertising SDKs Leak Location Data
• EFF Identified Advertising SDKs That Share Location Data by Default
• InMobi Encourages Keeping Location Sharing Enabled By Highlighting Financial Incentives
• BidMachine Updates Previously Inaccurate Developer Documentation After EFF's Technical Analysis Observed Precise Location Data Collection
• Verve Emphasizes Consent More in its Play Store Language Than its Configuration Guide
• Huawei Highlights Financial Incentives for Location Data Sharing Before Showing Developers How to Opt Out
• Location Data Sharing Can Happen Without Users’ Knowledge or Meaningful Consent
• Location Privacy Issues Extend Beyond These Four SDKs
• Fighting Back Against AdTech Companies That Enable and Encourage Location Data Sharing
• Developers
• Regulators
• Legislators

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.

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.

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.

Last week, Senators Ted Cruz and Ron Wyden introduced the Justice Against Weaponized Bureaucratic Overreach to Networked Expression, or JAWBONE Act. The bipartisan legislation creates a federal cause of action against government officials who coerce or attempt to coerce broadcasters, interactive computer services, or AI providers into taking actions against lawful, First-Amendment-protected speech, and establishes a transparency system for government communications with those intermediaries about user expression.

We thank the Senators for their leadership on this important issue. Jawboning occurs when the government pressures private companies to censor speech protected by the First Amendment, and it’s not always obvious to the public or to the victims what has actually happened. Deleting posts or cancelling accounts because a government official or agency demanded it or even made threats in making those demands—just like spying on people’s communications on behalf of the government—raises serious free speech concerns. Among other things, this bill would provide a new legal right to bring claims against the government in federal court, in addition to what the First Amendment provides.

At EFF, we’re continuing to fight back on behalf of those censored by government coercion. One recent example: we represent the creator of ICEBlock, an app that allows the public to report immigration enforcement activity in their communities. In June 2025, high-ranking federal officials began threatening to investigate and prosecute the creator of ICEBlock, Joshua Aaron. In October 2025, the U.S. Attorney General demanded Apple remove ICEBlock from the App Store, and the company complied. The government’s coercion violated Aaron’s First Amendment rights.

We’ve also filed a Freedom of Information Act lawsuit against the same government agencies that threatened Aaron and other services that provided forums to report ICE activity. The lawsuit seeks the disclosure of the government’s communications with Apple, Google, and Meta that forced the services to remove lawful speech.

When federal officials pressure private companies into censoring protected speech, it can violate the First Amendment. But, not every communication from a government agency to a platform is unconstitutionally coercive. Treating legitimate communication and information-sharing between the government and private actors as though it were always unconstitutional would chill the valuable, good-faith engagement that supports a healthier and safer internet and nation for all Americans. This is a complex issue, and one that is important for Congress and the courts to get right. 

Finally, contrary to what many in Congress have been saying, social media platforms and other internet intermediaries have their own First Amendment rights to decide how they moderate users’ speech. They are not “state actors” and do not have an obligation under the First Amendment to allow all user speech on their platforms. EFF filed an amicus brief setting out our position in 2018, and we’ve said it in many cases since. The Supreme Court recognized again in the Netchoice cases that these services have a right to curate and edit their users’ speech, whether or not it aligns with the government’s position. And, it’s important to defend that First Amendment right so that governments cannot dictate how to edit a company’s site according to the government’s wishes and desires. To prevent jawboning by default, companies must be free to curate their platforms as they wish.

EFF applauds Senators Cruz and Wyden for taking this critical issue seriously, and we look forward to working with Congress on this bipartisan bill as it moves through the process. We hope it lands on the right balance to provide additional protections for everyday users around freedom of expression. 

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. 

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 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.