We'd all like the internet to be a better place—for kids and adults alike. But in the name of online safety, governments around the world are racing to impose a dangerous new system of control. Are age gates the silver bullet to the internet's problems they're being promoted as? Or are we being sold a bill of goods? We're answering this question and more in our latest EFFector newsletter.

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For over 35 years, EFFector has been your guide to understanding the intersection of technology, civil liberties, and the law. This latest issue covers an attack on VPNs in Utah, a livestream on how to disenshittify the internet, and California's proposed social media ban that could set a dangerous new precedent for online censorship.

Prefer to listen in? EFFector is now available on all major podcast platforms. This time, we're having a conversation with EFF Legislative Analyst Molly Buckley on why social media bans can't sidestep the U.S. constitution. You can find the episode and subscribe on your podcast platform of choice:

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The federal SECURE Data Act is not a serious consumer privacy bill, and its provisions—if enacted—would be a retreat from already insufficient state protections.

Republicans on the House Energy and Commerce Committee released a draft of the bill late last month without bipartisan support. The bill is weaker than congressional proposals in prior years, as well as most of the 21 state consumer privacy laws already on the books.

The bill could wipe out hundreds of  state privacy protections.

Most troubling for EFF: the bill would preempt dozens, if not hundreds, of state laws that regulate related topics, and it would not allow consumers to sue to protect their own rights (commonly called a private right of action). And it comes nowhere close to banning online behavioral advertising—a practice that fuels technology companies’ always increasing hunt for personal data.

The bill also suffers from many other flaws including weak opt-out defaults, inadequate data minimization requirements, and large definitional loopholes for companies.

Key Provisions

The bill would give consumers some rights to take action to control their personal data— like access, correction, deletion, and limited portability. These rights have become standard in all data privacy proposals in recent years.

The bill would also require companies to obtain your consent before processing your sensitive data, or using any of your personal data for a previously undisclosed purpose. Absent your consent, a company couldn’t do these things.

Further, the bill would allow you to opt out of (1) targeted third-party advertising, (2) the sale of your personal data, and (3) profiling of you that has a legal, healthcare, housing, or employment effect. Unfortunately, a company could keep doing these invasive things to you, unless you opted out.

The bill would also require data brokers that make at least 50 percent of their profits from the sale of personal data to register in a public database maintained by the Federal Trade Commission (FTC).

Preemption of Too Many State Laws

Federal privacy laws should allow states to build ever stronger rights on top of the federal floor. Many federal privacy laws allow this, including the Health Insurance Portability and Accountability Act, the Video Privacy Protection Act, and the Electronic Communications Privacy Act.

The SECURE Data Act would not do that. Instead, it would wipe out dozens, if not hundreds, of existing state privacy protections. Section 15 of the bill would preempt any “law, rule, regulation, requirement, standard, or other provision [that] relates to the provisions of this Act.” This would kill the 21 state consumer privacy laws passed in the past few years. These state bills aren’t strong enough, but they are still better than this federal proposal. For example, California maintains a data broker deletion tool and requires companies to comply with automatic opt-out signals—including one that is built into EFF’s Privacy Badger.

Because the SECURE Data Act has provisions that relate to data privacy and security, it could preempt all 50 state data breach laws and many others. It could also preempt state laws related to specific pieces of sensitive data, like bans on the sale of biometric or location information. Some states like California have constitutional provisions that protect an individual’s right to privacy, which can be enforced against companies. That constitutional provision, as well as state privacy torts, could also be in danger if this bill passed.

No Private Enforcement, A New Cure Period, and Vague Security Powers

Strong consumer privacy laws should allow consumers to take companies to court to defend their own rights. This is essential because regulators do not have the resources to catch every violation, and federal consumer enforcement agencies have been gutted during the current administration.

The SECURE Data Act does not have a private right of action. The FTC, along with state attorneys general, have primary enforcement authority. The law also gives companies 45 days to “cure” any violation with no penalty after they are caught.

Moreover, Section 8 of the bill creates a vaguely defined self-regulatory scheme in which companies can apply to be audited by an “independent organization” that will apply a “code of conduct.” Following this code of conduct would give companies a presumption that they are complying with the law. This provision is an implicit acknowledgement that the bill does not provide regulators with any new resources to enforce new protections.

Section 9 of the bill would give the Secretary of Commerce broad power to “take any action necessary and appropriate to support the international flow of personal data,” including assessing “security interests of the United States.” The scope of this amorphous provision is unclear, but it likely does not belong in a consumer protection bill.

Weak Privacy Defaults

Your online privacy should not depend on whether you have the time, patience, and knowledge to navigate a website and turn off invasive tracking. Good privacy laws build in data minimization requirements—meaning there should be a default standard that prevents companies from processing your data for purposes that are not needed to provide you with the service you asked for.

The SECURE Data Act puts the burden on you to opt out of invasive company practices, like targeted third-party advertising, the sale of your personal data, and profiling. The bill at least requires companies to obtain your consent before processing your sensitive data (like selling your precise location). These consent requirements, however, are often an invitation for companies to trick you into clicking a button to give away your rights in hard-to-read policies. Indeed, few people would knowingly agree to let a company sell their personal data to a broker who turns around and sells it to the government.

Section 3 of the bill uses the term “data minimization,” but it is done in name only. The provision does not limit a company’s processing of data to only what is necessary to provide the customer with the good or service they asked for. Instead, the provision limits processing of data to only what a company “disclosed to the customer”—meaning if it is in the confusing privacy policy that nobody reads, it is okay.

And the bill would not even allow you to restrict certain uses of your data. As companies seek more data for AI systems, many internet users do not want their private personal data to be used to train those models. However, the bill makes clear that “nothing in this Act may be construed to restrict” a company from collecting, using, or retaining your data to “develop” or “improve” a new technology.

Other Flawed Definitions and Loopholes

The bill has numerous loopholes that technology companies would exploit if the bill were to become law. Below is just a sampling:

• Government contractors: Under Section 13(b)(2), government contractors are exempt from the bill, which could be wrongly interpreted to exempt certain data brokers from sale restrictions when those sales are made to the government. This type of exemption could benefit surveillance companies like Clearview AI, which previously argued it was exempt from Illinois’ strict biometric law using a similar contractor exception. This is likely not the authors’ intention, since the definition of sale includes those made “to a government entity.”
  Sale definition: The definition in Section 16(28) is defined too narrowly. A sale should mean any exchange for monetary “or other valuable” consideration, as in some other privacy laws.
• Biometric information definition: The definition in Section 16(4) excludes data generated from a photo or video, and the definition excludes face scans not meant to “identify a specific individual.” This could be wrongly interpreted to allow biometric identification from security camera footage, or biometric use for sentiment or demographic analysis.
• Personal data definition: The definition in Section 16(21) exempts “de-identified data” from the definition of personal data, which could allow companies to do anything with de-identified data because that data is not protected by the law. The problem with de-identified data is that many times it is not.
• Deletion requests: With regard to data that a company obtained from a third-party, Section 2(d)(5) would treat a consumer’s deletion request merely as an opt-out request. And even if a customer requested deletion, a company might be able to retain the data for research purposes under section 11(a)(9)(A).
• Profiling definition: Under the definition in Section 16(25), companies could profile so long as the profiling is not “solely automated.” The flimsiest human review would exempt highly automated profiling.

Congress is long overdue to enact a strong comprehensive consumer data privacy law, and we have sketched what it should look like. But the SECURE Data Act is woefully inadequate. In fact, it would cause even more corporate surveillance of our personal information, by wiping out state laws that are more protective than this federal bill. Even worse, this bill would block state legislatures from protecting their residents from the privacy threats of tomorrow that are unforeseeable today. 

A new rowhammer attack gives complete control of NVIDIA CPUs.

On Thursday, two research teams, working independently of each other, demonstrated attacks against two cards from Nvidia’s Ampere generation that take GPU rowhammering into new—­and potentially much more consequential—­territory: GDDR bitflips that give adversaries full control of CPU memory, resulting in full system compromise of the host machine. For the attack to work, IOMMU memory management must be disabled, as is the default in BIOS settings.

“Our work shows that Rowhammer, which is well-studied on CPUs, is a serious threat on GPUs as well,” said Andrew Kwong, co-author of one of the papers. “...

The Trump administration is suing Vermont and New York for using novel tactics to curb greenhouse gas emissions.

A plan to postpone the retirement of the Ray Nixon Power Plant comes as Colorado wrestles with its climate targets.

A surge in diesel costs is set to ripple through the U.S. economy, raising prices on everything from groceries to housing and adding new political risk for Republicans.

New research shows that trees are cutting urban temperatures from climate change in half worldwide.

Never implemented amid a spate of legal challenges, the policy required companies to report material risks to their business due to a changing climate, as well as carbon emissions for some firms.

Record-breaking gold prices, driven largely by investor demand for safe assets amid rising global risks, have provided a strong incentive for illegal mining.

Electric vehicle sales and solar panel imports have surged since the conflict in the Middle East began.

Japan’s offer of energy transition assistance for South Africa adds to about $10 billion in climate finance pledged to the continent’s biggest economy.

Researchers from MIT and elsewhere have developed a more user-friendly and efficient method to help networking engineers identify potential system failures before they cause major problems, like a cloud service outage that leaves millions of users unable to access applications. 

The technique uncovers hidden blind spots that might cause a shortcut algorithm to fail unexpectedly when it is deployed. 

This new approach can identify worse-case scenarios that an engineer might miss if they use a traditional method that compares an algorithm against a set of human-designed past test cases. It is also less labor-intensive than other verification tools that require engineers to rewrite an algorithm in a complex mathematical code each time they want to test it.

Instead of needing a mathematical reformulation, the new method reads the algorithm’s source code directly and automatically searches for worse-case scenarios that lead to the highest level of underperformance.

By helping engineers quickly and easily stress-test a networking algorithm before deployment, the method could catch failure modes that might otherwise only appear in a real outage. The technique could also be used to analyze the risks of deploying AI-generated code.

“We need to have good tools to measure the worse-case scenario performance of our algorithms so we know what could happen before we put them into production. This is an easy-to-use tool that can be plugged into current systems so we can find the best algorithm to use and ensure the worse-case scenarios are identified in advance,” says Pantea Karimi, an electrical engineering and computer science (EECS) graduate student and lead author of a paper on this new technique. 

She is joined on the paper by senior authors Mohammad Alizadeh, an associate professor of EECS and a member of the Computer Science and Artificial Intelligence Laboratory (CSAIL); and Behnaz Arzani, a principal researcher at Microsoft Research; along with Ryan Beckett, Siva Kesava Reddy Karkarla, and Pooria Namyar, researchers at Microsoft Research; and Santiago Segarra, a professor at Rice University. The research will be presented at the USENIX Symposium on Networked Systems Design and Implementation. 

Assessing algorithms

In large systems like cloud servers, the tried-and-true algorithms that route data from one place to another or are often too computationally intensive to run in a feasible amount of time. 

So, engineers and researchers develop suboptimal algorithms called heuristics that can run much faster. However, there could be unexpected but plausible circumstances that will cause a heuristic to underperform or fail when deployed.

A heuristic can route millions of data requests across a cloud network in seconds, but under the wrong conditions — like an unusual traffic pattern or a sudden spike in demand — the shortcut can break down in ways the designer never anticipated.

When these problems occur, a company may have no choice but to drop some requests that can’t be processed. 

The firm could also deliberately allocate more resources in advance to head-off a potential disaster, leading to higher overall costs and wasted electricity from underutilization.

“This is really bad for a company because, either way, they are going to lose a lot of money. If this particular scenario hasn’t happened before and was never tested, how would a developer know in advance before it happens?” Karimi says.

Stress-testing heuristics typically involves running a new algorithm in simulation using a set of human-designed test cases and manually comparing the performance with a previous algorithm. But this is time-consuming and can leave blind spots if an engineer doesn’t know to test for certain situations.

Alternatively, engineers could use a verification tool to evaluate the performance of their heuristic more systematically. However, these tools require the engineer to encode the algorithm into a complex, mathematical formula that can take days to flesh out. The process, which doesn’t work for every type of heuristic, must be repeated each time the engineer changes the code.

Instead, the researchers developed a more user-friendly and efficient verification tool, called MetaEase, that analyzes the heuristic’s existing implementation code directly to identify the biggest risks of deploying it.

“This would reduce the friction of using these heuristic analysis tools,” Karimi says.

She began this work during an internship at Microsoft Research, where the team previously developed MetaOpt, a heuristic analyzer that requires engineers to rewrite their algorithms as formal optimization models. MetaEase grew out of the desire to remove that barrier.

Maximizing the gap

MetaEase is driven by two key innovations. First, it uses a technique called symbolic execution to map out the different decision points in the heuristic's code. These are places where the algorithm might behave differently depending on the input.

This technique produces a set of representative starting points, each corresponding to a distinct behavior the heuristic could exhibit.

Second, from these starting points, MetaEase utilizes a guided search to systematically move toward inputs that make the heuristic perform as poorly as possible, compared to the optimal algorithm.

In machine learning, for instance, an input could be a set of user queries to an AI chatbot at a given time.

“In this way, we have exploited every possible heuristic behavior and used special techniques to move in the direction where we think the performance gap is going to increase,” Karimi explains.

In the end, MetaEase identifies the input that maximizes the performance gap between the heuristic and an optimal benchmark.

With this information, a heuristic developer could inspect the input to understand what went wrong and incorporate safeguards that will prevent the problem from happening during deployment.

In simulated experiments, MetaEase often identified inputs with larger performance gaps than traditional methods — pinpointing more catastrophic worse-case scenarios. And it did so much more efficiently. 

It was also able to analyze a recent networking heuristic that no state-of-the-art method could handle.

In the future, the researchers want to enhance MetaEase so it can process additional types of types of data, like categorical inputs. They also want to improve the scalability of their method and adapt MetaEase to evaluate more complex heuristics.

“Reasoning about the worst-case performance of deployed heuristics is a hard and longstanding problem. MetaEase makes tangible progress by analyzing heuristics directly from source code, eliminating the need for formal models that have historically limited who can use such analysis tools. I was pleasantly surprised that it handles non-convex and randomized heuristics by combining symbolic execution with gradient-based search in a practical and effective way,” says Ratul Mahajan of the University of Washington Paul G. Allen School of Computer Science and Engineering, who was not involved with this research.

This research was funded, in part, by a Microsoft Research internship and the U.S. National Science Foundation (NSF).

Nature Climate Change, Published online: 06 May 2026; doi:10.1038/s41558-026-02626-9

Assessing risk and adverse impacts associated with climate change is essential to inform adaptation efforts. However, this Perspective argues that knowledge of potentially beneficial impacts is also crucial for adaptation, requiring modifications of current impact and adaptation research frameworks.

Gabriele Farina grew up in a small town in a hilly winemaking region of northern Italy. Neither of his parents had college degrees, and although both were convinced they “didn’t understand math,” Farina says, they bought him the technical books he wanted and didn’t discourage him from attending the science-oriented, rather than the classical, high school.

By around age 14, Farina had focused on an idea that would prove foundational to his career.

“I was fascinated very early by the idea that a machine could make predictions or decisions so much better than humans,” he says. “The fact that human-made mathematics and algorithms could create systems that, in some sense, outperform their creators, all while building on simple building blocks, has always been a major source of awe for me.”

At age 16, Farina wrote code to solve a board game he played with his 13-year-old sister.

“I used game after game to compute the optimal move and prove to my sister that she had already lost long before either of us could see it ourselves,” Farina says, adding that his sister was less enthralled with his new system.

Now an assistant professor in MIT’s Department of Electrical Engineering and Computer Science (EECS) and a principal investigator at the Laboratory for Information and Decision Systems (LIDS), Farina combines concepts from game theory with such tools as machine learning, optimization, and statistics to advance theoretical and algorithmic foundations for decision-making.

Enrolling at Politecnico di Milano for college, Farina studied automation and control engineering. Over time, however, he realized that what activated his interest was not “just applying known techniques, but understanding and extending their foundations,” he says. “I gradually shifted more and more toward theory, while still caring deeply about demonstrating concrete applications of that theory.”

Farina’s advisor at Politecnico di Milano, Nicola Gatti, professor and researcher in computer science and engineering, introduced Farina to research questions in computational game theory and encouraged him to apply for a PhD. At the time, being the first in his immediate family to earn a college degree and living in Italy, where doctoral degrees are handled differently, Farina says he didn’t even know what a PhD was.

Nevertheless, one month after graduating with his undergraduate degree, Farina began a doctoral degree in computer science at Carnegie Mellon University. There, he won distinctions for his research and dissertation, as well as a Facebook Fellowship in Economics and Computation.

As he was finishing his doctorate, Farina worked for a year as a research scientist in Meta’s Fundamental AI Research Labs. One of his major projects was helping to develop Cicero, an AI that was able to beat human players in a game that involves forming alliances, negotiating, and detecting when other players are bluffing.

Farina says, “when we built Cicero, we designed it so that it would not agree to form an alliance if it was not in its interest, and it likewise understood whether a player was likely lying, because for them to do as they proposed would be against their own incentives.”

A 2022 article in the MIT Technology Review said Cicero could represent advancement toward AIs that can solve complex problems requiring compromise.

After his year at Meta, Farina joined the MIT faculty. In 2025, he was distinguished with the National Science Foundation CAREER Award. His work — based on game theory and its mathematical language describing what happens when different parties have different objectives, and then quantifying the “equilibrium” where no one has a reason to change their strategy — aims to simplify massive, complex real-world scenarios where calculating such an equilibrium could take a billion years.

“I research how we can use optimization and algorithms to actually find these stable points efficiently,” he says. “Our work tries to shed new light on the mathematical underpinnings of the theory, better control and predict these complex dynamical systems, and uses these ideas to compute good solutions to large multi-agent interactions.”

Farina is especially interested in settings with “imperfect information,” which means that some agents have information that is unknown to other participants. In such scenarios, information has value, and participants must be strategic about acting on the information they possess so as not to reveal it and reduce its value. An everyday example occurs in the game of poker, where players bluff in order to conceal information about their cards.

According to Farina, “we now live in a world in which machines are far better at bluffing than humans.”

A situation with “massive amounts of imperfect information,” has brought Farina back to his board-game beginnings. Stratego is a military strategy game that has inspired research efforts costing millions of dollars to produce systems capable of beating human players. Requiring complex risk calculation and misdirection, or bluffing, it was possibly the only classical game for which major efforts had failed to produce superhuman performance, Farina says.

With new algorithms and training costing less than $10,000, rather than millions, Farina and his research team were able to beat the best player of all time — with 15 wins, four draws, and one loss. Farina says he is thrilled to have produced such results so economically, and he hopes “these new techniques will be incorporated into future pipelines,” he says.

“We have seen constant progress towards constructing algorithms that can reason strategically and make sound decisions despite large action spaces or imperfect information. I am excited about seeing these algorithms incorporated into the broader AI revolution that’s happening around us.”

On April 10, MIT marked its first official Robert R. Taylor Day with a program centered on the life and work of Robert Robinson Taylor (Class of 1892), the Institute’s first Black graduate and the first academically trained Black architect in the United States.

After graduating from MIT, Taylor joined Tuskegee Institute (now Tuskegee University), where he designed campus buildings, developed a curriculum, and helped establish an approach to architectural education grounded in making and community life — an orientation that continues to shape the relationship between MIT and Tuskegee today. 

Taylor returned to MIT on April 10, 1911, to speak at the 50th anniversary of the Institute’s founding — the date now observed as Robert R. Taylor Day. Reflecting on his education, he credited MIT with the “methods and plans” he carried to Tuskegee Institute. “Certainly the spirit,” he said, was found “in the love of doing things correctly, of putting logical ways of thinking into the humblest task … to build up the immediate community in which the persons live.”

One hundred fifteen years later, at the MIT Museum, students and faculty gathered around Taylor’s original thesis, “A Soldiers Home.” The work was presented alongside archival materials from Taylor’s time at MIT by Jonathan Duval, assistant curator of architecture and design. Rather than framing Taylor as a distant historical figure, the encounter with the work itself — its drawings, assumptions, and ambitions — set the terms for the day, bringing forward not only his accomplishments but the ideas and methods that continue to inform teaching and collaboration today. Attendees then gathered for a lunch-and-learn session including a hybrid panel involving MIT and Tuskegee University faculty. 

“It is so important to continue to develop the MIT-Tuskegee relationship begun by Robert R. Taylor,” says Kwesi Daniels, associate professor and head of the architecture department at Tuskegee University. “MIT students are provided an opportunity to experience the campus Taylor designed and his ethos of social architecture. For the Tuskegee students, they are able to appreciate the foundation Taylor received at MIT. The engagement epitomizes the ‘mind and hand’ philosophy of MIT and the head, hand, heart philosophy of Tuskegee.”

An ongoing exchange

Student and faculty exchanges, launched by the architecture departments at both institutions, have extended these connections in recent years. MIT students travel to Tuskegee for work in historic preservation and community engagement, sampling Daniels’ scanning and drone equipment, while Tuskegee students come to MIT to engage with digital fabrication and entrepreneurship.

For Nicholas de Monchaux, professor and head of the Department of Architecture at MIT, the relationship reflects continuity. “We are not uniting. We’re reuniting,” he says. “This year’s celebration should really be seen as the kickoff of a year of reflecting on Robert Taylor’s legacy and imagining what the day, and his legacy, can become over time.”

The day’s program — the vision for which originally emerged from a suggestion made by MIT literature professor Joshua Bennett during a meeting at Tuskegee with de Monchaux, Daniels, and Tuskegee President Mark Brown — moved into a broader effort among faculty and collaborators across architecture, history, and the humanities. As Bennett put it, “The primary aim of Robert R. Taylor Day is to lift up not only Taylor’s accomplishments, but his ideas — and the fact that his ideas live on in those of us who have inherited his legacy.”

That emphasis is also visible in the dedicated coursework and research that has accompanied the exchange since 2022. In class 4.s12 (Brick x Brick: Drawing a Particular Survey), taught by Carrie Norman, assistant professor in architecture at MIT, students document buildings on the Tuskegee campus through measured drawings and archival interpretation. Working from limited historical material, they reconstruct both form and intent.

“My role has been to structure this work pedagogically,” Norman says, “guiding students in methods of close looking, measured drawing, and archival interpretation.” She describes Taylor’s work as “an ongoing research agenda,” adding that “the broader aim is not only to deepen engagement with Taylor’s legacy, but to build on it through new forms of design research.”

Related work has contributed to a recent exhibition on the Tuskegee Chapel at the National Building Museum, curated by Helen Bechtel of the Yale School of Architecture. Building on research conducted in Norman’s course, students developed large-scale models that form part of the exhibition. New 3D fabrications use a limited set of archival materials to reconstruct the chapel originally designed by Taylor as the first electrified building in Alabama’s Macon County, which was destroyed by fire in 1957.

Looking ahead

Timothy Hyde, professor in the MIT Department of Architecture, has also been involved in the ongoing MIT–Tuskegee collaboration and in efforts to situate Taylor’s work within a broader historical context. He notes that Taylor’s training at MIT helped shape the curriculum he later developed at Tuskegee. “The other influence I would like to mention is the city of Boston itself,” Hyde adds. “Boston was a prosperous city with a wealth of civic architecture that Taylor would have seen and studied.” 

A documentary project on Taylor’s life, supported by the MIT Human Insight Collaborative and led by Hyde and historian Christopher Capozzola, senior associate dean for MIT Open Learning, is currently in development.

For some students, these encounters shape longer trajectories. As an undergraduate at Tuskegee, Myles Sampson participated in the MIT Summer Research Program (MSRP), where he began to connect architecture with a growing interest in computation. He later enrolled in MIT’s Master of Science in Architecture Studies (SMArchS) computation program, working with Professor Larry Sass, who introduced him to robotic fabrication.

“I never looked back,” Sampson says. “Without that hands-on research experience, I would never have looked past contemporary architectural practice.” He is now pursuing a doctorate in computational design at Carnegie Mellon University, focused on the role of automation in architecture and construction.

Sampson contributed significant work to the National Building Museum’s exhibition. His installation, Brick Parable, brings together historical reference and robotic construction. As de Monchaux notes, the project reflects the long arc of Taylor’s legacy: “bricks were fired by students as part of Taylor’s training program … Myles [Sampson]’s piece, made with a robotic assembly of bricks, explores the architectural idea of the chapel in contemporary form.”

For Daniels, the continued circulation of students between the two institutions remains central. Viewing Taylor’s thesis in particular offers a shared point of reference. “Whether the student is from Tuskegee or MIT, they are able to appreciate the quality of work Taylor completed as a student,” he says, “and how he built on that work by creating a college campus, beginning at age 25.”

Across these activities, Taylor’s work is approached not as a fixed legacy, but as a set of methods and commitments that continue to be tested. As Catherine Armwood, dean of Tuskegee University Robert R. Taylor School of Architecture and Construction Science, describes it: “While our students leverage [the design and entrepreneurship program] MITdesignX to turn architectural concepts into social enterprises through advanced fabrication and venture mentorship, MIT students come to Tuskegee for an immersion in historic preservation. By surveying buildings handcrafted by our founding students, they learn a legacy of self-reliance and community impact that can’t be found anywhere else,” Armwood says. “Together, we are bridging technical innovation with deep-rooted heritage to train a new generation of visionary leaders.” 

DarkSword is a sophisticated piece of malware—probably government designed—that targets iOS.

Google Threat Intelligence Group (GTIG) has identified a new iOS full-chain exploit that leveraged multiple zero-day vulnerabilities to fully compromise devices. Based on toolmarks in recovered payloads, we believe the exploit chain to be called DarkSword. Since at least November 2025, GTIG has observed multiple commercial surveillance vendors and suspected state-sponsored actors utilizing DarkSword in distinct campaigns. These threat actors have deployed the exploit chain against targets in Saudi Arabia, Turkey, Malaysia, and Ukraine...

EFF joins 18 organizations in writing a letter to UK policymakers urging them to address the root causes of online harm—rather than undermining the open web through blunt restrictions.

The coalition, which includes Mozilla, Tor Project, and Open Rights Group, warns that proposed measures following the passage of the Children’s Wellbeing and Schools Bill risk fundamentally reshaping the internet in harmful ways. Chief among these proposals are sweeping age-gating requirements and access restrictions that would apply not only to young people, but effectively to all users.

While framed as efforts to protect children online, these policies rely heavily on age assurance technologies that are either inaccurate, privacy-invasive, or both. As the letter notes, mandating such systems across a wide range of services—from social media and video games to VPNs and even basic websites—would force users to verify their identity simply to access the web. This creates serious risks, including expanded surveillance, data breaches, and the erosion of anonymity.

Beyond privacy concerns, the signatories argue that these measures threaten the core architecture of the open internet. Age-gating at scale could fragment the web into a patchwork of restricted jurisdictions, limit access to information, and entrench the dominance of powerful gatekeepers like app stores and platform ecosystems. In doing so, policymakers risk weakening the very qualities—interoperability, accessibility, and openness—that have made the internet a global public resource.

The letter also emphasizes what’s missing from the current policy approach: meaningful efforts to address the underlying drivers of online harm. Many digital platforms are designed to maximize engagement and profit through pervasive data collection and targeted advertising, often at the expense of user safety and autonomy. Rather than imposing access bans, the coalition calls on UK policymakers to hold companies accountable for these systemic practices and to prioritize user rights by design.

Importantly, the signatories highlight that the internet remains a vital space for young people: offering access to information, support networks, and opportunities for expression that may not exist offline. Policies that restrict access risk cutting off these lifelines without meaningfully reducing harm.

The message is clear: protecting users online requires more than heavy-handed restrictions. It demands thoughtful, rights-respecting policies that tackle the business models and design choices driving harm, while preserving the open, global nature of the web.

Federal courts aren't buying DOJ's argument that climate liability lawsuits undermine U.S. energy policy.

Utah, Oklahoma and Tennessee also have passed laws shielding polluters.

Cooling a home could cost on average as much as $900 between June and September in Southern states.