Pledge is a lightweight reactive programming framework for Swift designed to be simpler and more performant than RxSwift. It aims to provide a more accessible entry point to reactive programming by offering a reduced API surface, focusing on core functionalities like observables, operators, and subjects. Pledge avoids the overhead associated with RxSwift, leading to improved compile times and runtime performance, particularly beneficial for smaller projects or those where resource constraints are a concern. The framework embraces Swift's concurrency features, enabling seamless integration with async/await for modern Swift development. Its goal is to offer the benefits of reactive programming without the complexity and performance penalties often associated with larger frameworks.
This blog post explores the architecture and evolution of Darwin, Apple's open-source operating system foundation, and its XNU kernel. It explains how Darwin, built upon the Mach microkernel, incorporates components from BSD and Apple's own I/O Kit. The post details the hybrid kernel approach of XNU, combining the message-passing benefits of a microkernel with the performance advantages of a monolithic kernel. It discusses key XNU subsystems like the process manager, memory manager, file system, and networking stack, highlighting the interplay between Mach and BSD layers. The post also traces Darwin's history, from its NeXTSTEP origins through its evolution into macOS, iOS, watchOS, and tvOS, emphasizing the platform's adaptability and performance.
Hacker News users generally praised the article for its clarity and depth in explaining a complex topic. Several commenters with kernel development experience validated the information presented, noting its accuracy and helpfulness for understanding the evolution of XNU. Some discussion arose around specific architectural choices made by Apple, including the Mach microkernel and its interaction with the BSD environment. One commenter highlighted the performance benefits of the hybrid kernel approach, while others expressed interest in the challenges of maintaining such a system. A few users also pointed out areas where the article could be expanded, such as delving further into I/O Kit details and exploring the security implications of the XNU architecture.
This blog post details the process of emulating an iPhone 11 running iOS 14.4.2 using QEMU, specifically highlighting the complexities involved. The author explains the necessity of using a pre-built kernel and device tree, obtained through a jailbreak, and emphasizes that building these components from source is not currently feasible. The post walks through setting up the necessary files, including the kernel, device tree, ramdisk, and a signed IPSW, and configuring QEMU for ARM virtualization. While the emulation achieves a basic boot, the author acknowledges significant limitations, such as lack of GPU acceleration, networking, and a functional touchscreen, ultimately rendering the emulated environment impractical for general use but potentially useful for low-level debugging or research.
HN commenters generally praised the technical achievement of emulating iOS 14 on QEMU, calling it "impressive" and "quite a feat." Some discussed the potential for security research and malware analysis, while others speculated about the possibility of running iOS apps on other platforms, though acknowledging Apple's legal stance against this. Several commenters questioned the practicality and performance of the emulation, pointing out the slow speed and limited hardware support. One highlighted the difficulty of getting the GPU to work properly, emphasizing the complexity of fully emulating a modern mobile operating system. The legality of distributing iOS firmware was also a point of discussion.
Apple's "Cubify Anything" introduces a new approach to 3D object detection within indoor scenes using monocular RGB images. It leverages a pre-trained 2D object detector to identify objects and then fits a cuboid to each detected object by estimating its 3D pose and dimensions. This method, dubbed "cubification," efficiently generates dense 3D models of indoor environments, suitable for applications like augmented reality and scene understanding. The approach simplifies the 3D detection pipeline by directly predicting cuboids instead of complex meshes or point clouds, enabling real-time performance on mobile devices. Importantly, Cubify Anything is designed to work on diverse indoor scenes without requiring specific training data for each scene.
Hacker News users discussed Apple's Cubify research, expressing excitement about its potential applications in AR/VR and robotics. Some questioned the practical use cases given the computational demands, suggesting mobile deployment would be challenging. Several commenters compared it to existing 3D modeling techniques like NeRF, noting Cubify's focus on cuboid representations might offer advantages in certain scenarios, like robot manipulation. There was also interest in the dataset used for training and the possibility of open-sourcing it. Finally, some users expressed skepticism about Apple's history of releasing research code, while others countered that their recent track record had improved.
Verichains' analysis reveals that several Vietnamese banking apps improperly use private iOS APIs, potentially jeopardizing user security and app stability. These apps employ undocumented functions to gather device information, bypass sandbox restrictions, and manipulate UI elements, likely in pursuit of enhanced functionality or anti-fraud measures. However, reliance on these private APIs violates Apple's developer guidelines and creates risks, as these APIs can change without notice, leading to app crashes or malfunctions. Furthermore, this practice exposes users to potential security vulnerabilities that malicious actors could exploit. The report details specific examples of private API usage within these banking apps and emphasizes the need for developers to adhere to official guidelines for a safer and more reliable user experience.
Several Hacker News commenters discuss the implications of the Verichains blog post, focusing on the potential security risks of using private APIs. Some express surprise at the prevalence of this practice, while others point out that using private APIs is a common, though risky, way to achieve certain functionalities not readily available through public APIs. The discussion touches on the difficulty of Apple enforcing its private API rules, particularly in regions like Vietnam where regulatory oversight might be less stringent. Commenters also debate the ethics and pragmatism of this practice, acknowledging the pressure developers face to deliver features quickly while also highlighting the potential for instability and security vulnerabilities. The thread includes speculation about whether the use of private APIs is intentional or due to a lack of awareness among developers.
Google's Project Zero discovered a zero-click iMessage exploit, dubbed BLASTPASS, used by NSO Group to deliver Pegasus spyware to iPhones. This sophisticated exploit chained two vulnerabilities within the ImageIO framework's processing of maliciously crafted WebP images. The first vulnerability allowed bypassing a memory limit imposed on WebP decoding, enabling a large, controlled allocation. The second vulnerability, a type confusion bug, leveraged this allocation to achieve arbitrary code execution within the privileged Springboard process. Critically, BLASTPASS required no interaction from the victim and left virtually no trace, making detection extremely difficult. Apple patched these vulnerabilities in iOS 16.6.1, acknowledging their exploitation in the wild, and has implemented further mitigations in subsequent updates to prevent similar attacks.
Hacker News commenters discuss the sophistication and impact of the BLASTPASS exploit. Several express concern over Apple's security, particularly their seemingly delayed response and the lack of transparency surrounding the vulnerability. Some debate the ethics of NSO Group and the use of such exploits, questioning the justification for their existence. Others delve into the technical details, praising the Project Zero analysis and discussing the exploit's clever circumvention of Apple's defenses. The complexity of the exploit and its potential for misuse are recurring themes. A few commenters note the irony of Google, a competitor, uncovering and disclosing the Apple vulnerability. There's also speculation about the potential legal and political ramifications of this discovery.
"Notes" is an iOS app designed to help musicians improve their sight-reading skills. Available on the App Store for 10 years, the app presents users with randomly generated musical notation, covering a range of clefs, key signatures, and rhythms. Users can customize the difficulty level, focusing on specific areas for improvement. The app provides instant feedback on accuracy and tracks progress over time, helping musicians develop their ability to quickly and accurately interpret and play music.
HN users discussed the app's longevity and the developer's persistence, praising the 10-year milestone. Some shared their personal sight-reading practice methods, including using apps like Functional Ear Trainer and various websites. A few users suggested potential improvements for the app, such as adding support for other instruments beyond piano and offering more customization options like adjustable clefs. Others questioned the efficacy of pure note-reading practice without rhythmic context. The overall sentiment was positive, acknowledging the app's niche and the developer's commitment.
Apple's imposed limitations hinder the Pebble smartwatch's functionality on iPhones. Features like interactive notifications, sending canned replies, and using the microphone for dictation or voice notes are blocked by Apple's restrictive APIs. While Pebble can display notifications, users can't interact with them directly from the watch, forcing them to pull out their iPhones. This limited integration significantly diminishes the Pebble's usability and convenience for iPhone users, compared to the Apple Watch which enjoys full access to iOS features. The author argues that these restrictions are intentionally imposed by Apple to stifle competition and promote their own smartwatch.
HN commenters largely agree with the author's premise that Apple intentionally crippled Pebble's functionality on iOS. Several users share anecdotes of frustrating limitations, like the inability to reply to messages or use location services effectively. Some point out that Apple's MFi program, while ostensibly about quality control, serves as a gatekeeping mechanism to stifle competition. Others discuss the inherent tension between a closed ecosystem like Apple's and open platforms, noting that Apple prioritizes its own products and services, even if it means a degraded experience for users of third-party devices. A few commenters suggest the limitations are technically unavoidable, but this view is largely dismissed by others who cite examples of better integration on Android. There's also cynicism about Apple's purported security and privacy concerns, with some suggesting these are merely pretexts for anti-competitive behavior.
Apple is reportedly planning to add support for encrypted Rich Communication Services (RCS) messaging between iPhones and Android devices. This means messages, photos, and videos sent between the two platforms will be end-to-end encrypted, providing significantly more privacy and security than the current SMS/MMS system. While no official timeline has been given, the implementation appears to be dependent on Google updating its Messages app to support encryption for group chats. This move would finally bring a modern, secure messaging experience to cross-platform communication, replacing the outdated SMS standard.
Hacker News commenters generally expressed skepticism about Apple's purported move towards supporting encrypted RCS messaging. Several doubted Apple's sincerity, suggesting it's a PR move to deflect criticism about iMessage lock-in, rather than a genuine commitment to interoperability. Some pointed out that Apple benefits from the "green bubble" effect, which pressures users to stay within the Apple ecosystem. Others questioned the technical details of Apple's implementation, highlighting the complexities of key management and potential vulnerabilities. A few commenters welcomed the move, though with reservations, hoping it's a genuine step toward better cross-platform messaging. Overall, the sentiment leaned towards cautious pessimism, with many anticipating further "Apple-style" limitations and caveats in their RCS implementation.
The blog post urges Apple to implement disappearing messages in iMessage, arguing it's a crucial privacy feature already offered by competitors like Signal and WhatsApp. The author emphasizes that ephemerality is essential for protecting user privacy against device seizure, data breaches, and unwanted surveillance, citing real-world scenarios where sensitive information shared via iMessage has been exposed. They highlight the inherent risk of permanent message storage and propose that Apple offer user-configurable expiration times, similar to existing self-destructing media features. This would empower users to control the lifespan of their messages and minimize the potential for misuse or unintended exposure.
Hacker News users generally supported the idea of ephemeral messages in iMessage, citing privacy benefits and the existing precedent set by other messaging platforms. Some commenters raised concerns about the potential for misuse, particularly regarding evidence preservation in legal cases or investigations. Others discussed technical implementation details, questioning the reliability and security of such a feature, and suggesting potential solutions like server-side deletion or client-side cryptography. A few pointed out Apple's historical resistance to features perceived as hindering law enforcement access to data, speculating that this might be a factor in the absence of ephemeral messaging in iMessage. Finally, some questioned the effectiveness of disappearing messages given the possibility of screenshots and screen recordings.
Lynx is an open-source, high-performance cross-platform framework developed by ByteDance and used in production by TikTok. It leverages a proprietary JavaScript engine tailored for mobile environments, enabling faster startup times and reduced memory consumption compared to traditional JavaScript engines. Lynx prioritizes a native-first experience, utilizing platform-specific UI rendering for optimal performance and a familiar user interface on each operating system. It offers developers a unified JavaScript API to access native capabilities, allowing them to build complex applications with near-native performance and a consistent look and feel across different platforms like Android, iOS, and other embedded systems. The framework also supports code sharing with React Native for increased developer efficiency.
HN commenters discuss Lynx's performance, ease of use, and potential. Some express excitement about its native performance and cross-platform capabilities, especially for mobile and desktop development. Others question its maturity and the practicality of using JavaScript for computationally intensive tasks, comparing it to React Native and Flutter. Several users raise concerns about long-term maintenance and community support, given its connection to ByteDance (TikTok's parent company). One commenter suggests exploring Tauri as an alternative for native desktop development. The overall sentiment seems cautiously optimistic, with many interested in trying Lynx but remaining skeptical until more real-world examples and feedback emerge.
Eliseo Martelli's blog post argues that Apple's software quality has declined, despite its premium hardware. He points to increased bugs, regressions, and a lack of polish in recent macOS and iOS releases as evidence. Martelli contends that this decline stems from factors like rapid feature iteration, prioritizing marketing over engineering rigor, and a potential shift in internal culture. He ultimately calls on Apple to refocus on its historical commitment to quality and user experience.
HN commenters largely agree with the author's premise that Apple's software quality has declined. Several point to specific examples like bugs in macOS Ventura and iOS, regressions in previously stable features, and a perceived lack of polish. Some attribute the decline to Apple's increasing focus on services and new hardware at the expense of refining existing software. Others suggest rapid feature additions and a larger codebase contribute to the problem. A few dissenters argue the issues are overblown or limited to specific areas, while others claim that software quality is cyclical and Apple will eventually address the problems. Some suggest the move to universal silicon has exacerbated the problems, while others point to the increasing complexity of software as a whole. A few comments mention specific frustrations like poor keyboard shortcuts and confusing UI/UX choices.
WebShield is a new, free, and open-source content blocker for Safari designed to provide comprehensive protection against a wide range of online annoyances. Leveraging a constantly updated blocklist, it tackles intrusive ads, trackers, cryptocurrency miners, EU cookie banners, and other unwanted content, aiming for a cleaner and faster browsing experience. Users can customize their blocking preferences and add their own custom rules. Built using only native WebKit APIs, WebShield emphasizes performance and privacy by ensuring all processing is done locally on the device.
HN users generally expressed interest in WebShield, praising its open-source nature and potential effectiveness. Several commenters appreciated the developer's focus on privacy and the detailed explanation of the blocking process. Some raised concerns about the reliance on JavaScript and the potential for performance impact, suggesting native implementation would be preferable. Others questioned the long-term maintainability of the project and the feasibility of keeping the block lists updated. A few users mentioned existing content blockers and questioned WebShield's differentiation, while others welcomed it as a valuable addition to the Safari ecosystem. The developer actively engaged with the comments, addressing questions and clarifying the project's goals.
A new Safari extension allows users to set ChatGPT as their default search engine. The extension intercepts search queries entered in the Safari address bar and redirects them to ChatGPT, providing a conversational AI-powered search experience directly within the browser. This offers an alternative to traditional search engines, leveraging ChatGPT's ability to synthesize information and respond in natural language.
Hacker News users discussed the practicality and privacy implications of using a ChatGPT extension as a default search engine. Several questioned the value proposition, arguing that search engines are better suited for information retrieval while ChatGPT excels at generating text. Privacy concerns were raised regarding sending every search query to OpenAI. Some commenters expressed interest in using ChatGPT for specific use cases, like code generation or creative writing prompts, but not as a general search replacement. Others highlighted potential benefits, like more conversational search results and the possibility of bypassing paywalled content using ChatGPT's summarization abilities. The potential for bias and manipulation in ChatGPT's responses was also mentioned.
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HN commenters are generally skeptical of the iPhone 16e's value proposition. Several express disappointment that it uses the older A16 Bionic chip rather than the A17, questioning the "powerful" claim in the press release. Some see it as a cynical move by Apple to segment the market and push users towards the more expensive standard iPhone 16. The price point is also a source of contention, with many feeling it's overpriced for the offered specifications, especially compared to competing Android devices. A few commenters, however, appreciate Apple offering a smaller, more affordable option, acknowledging that not everyone needs the latest processor. The lack of a USB-C port is also criticized.
The blog post "Biases in Apple's Image Playground" reveals significant biases in Apple's image suggestion feature within Swift Playgrounds. The author demonstrates how, when prompted with various incomplete code snippets, the Playground consistently suggests images reinforcing stereotypical gender roles and Western-centric beauty standards. For example, code related to cooking predominantly suggests images of women, while code involving technology favors images of men. Similarly, searches for "person," "face," or "human" yield primarily images of white individuals. The post argues that these biases, likely stemming from the datasets used to train the image suggestion model, perpetuate harmful stereotypes and highlight the need for greater diversity and ethical considerations in AI development.
Hacker News commenters largely agree with the author's premise that Apple's Image Playground exhibits biases, particularly around gender and race. Several commenters point out the inherent difficulty in training AI models without bias due to the biased datasets they are trained on. Some suggest that the small size and specialized nature of the Playground model might exacerbate these issues. A compelling argument arises around the tradeoff between "correctness" and usefulness. One commenter argues that forcing the model to produce statistically "accurate" outputs might limit its creative potential, suggesting that Playground is designed for artistic exploration rather than factual representation. Others point out the difficulty in defining "correctness" itself, given societal biases. The ethics of AI training and the responsibility of companies like Apple to address these biases are recurring themes in the discussion.
This blog post explores improving type safety and reducing boilerplate when communicating between iOS apps and WatchOS complications using Swift. The author introduces two Domain Specific Languages (DSLs) built with Swift's result builders. The first DSL simplifies defining data models shared between the app and complication, automatically generating the necessary Codable conformance and WatchConnectivity transfer code. The second DSL streamlines updating complications, handling the asynchronous nature of data transfer and providing compile-time checks for supported complication families. By leveraging these DSLs, the author demonstrates a cleaner, safer, and more maintainable approach to iOS/WatchOS communication, minimizing the risk of runtime errors.
HN commenters generally praised the approach outlined in the article for its type safety and potential to reduce bugs in iOS/WatchOS communication. Some expressed concern about the verbosity of the generated code and suggested exploring alternative approaches like protobuf or gRPC, while acknowledging their added complexity. Others questioned the necessity of a DSL for this specific problem, suggesting that Swift's existing features might suffice with careful design. The potential benefits for larger teams and complex projects were also highlighted, where the enforced type safety could prevent subtle communication errors. One commenter pointed out the similarity to Apache Thrift. Several users appreciated the author's clear explanation and practical example.
Taner Şener, the creator of FFmpegKit, a commercial wrapper around FFmpeg for mobile development, announced that he's ceasing development and support. Due to complexities in maintaining FFmpeg across various architectures and operating systems, increasing maintenance burden, and inadequate revenue to justify continued development, he's chosen to shut down. Existing clients can continue using their purchased licenses, but future updates and support are discontinued. The core issue is the difficulty of sustainably supporting a complex project like FFmpegKit, even as a paid product, given the rapid pace of mobile development and the substantial engineering effort required for compatibility. While acknowledging the disappointment this will cause some users, Şener emphasizes the unsustainable nature of the project's current trajectory and thanks users for their support over the years.
Hacker News users discuss the author's decision to discontinue FFmpegKit, an iOS/Android FFmpeg library. Several commenters express disappointment, highlighting FFmpegKit's ease of use compared to alternatives like MobileFFmpeg. Some suggest the decision stems from the difficulty of maintaining cross-platform compatibility and the complex build process involved with FFmpeg. Others speculate about the author's motivation, including burnout or lack of financial viability. A few offer alternative solutions or express hope for a successor project. The lack of clear documentation for building FFmpeg directly is also a recurring concern, reinforcing the value of projects like FFmpegKit.
A UK watchdog is investigating Apple's compliance with its own App Tracking Transparency (ATT) framework, questioning why Apple's first-party apps seem exempt from the same stringent data collection rules imposed on third-party developers. The Competition and Markets Authority (CMA) is particularly scrutinizing how Apple gathers and uses user data within its own apps, given that it doesn't require user permission via the ATT pop-up prompts like third-party apps must. The probe aims to determine if this apparent double standard gives Apple an unfair competitive advantage in the advertising and app markets, potentially breaching competition law.
HN commenters largely agree that Apple's behavior is hypocritical, applying stricter tracking rules to third-party apps while seemingly exempting its own. Some suggest this is classic regulatory capture, where Apple leverages its gatekeeper status to stifle competition. Others point out the difficulty of proving Apple's data collection is for personalized ads, as Apple claims it's for "personalized experiences." A few commenters argue Apple's first-party data usage is less problematic because the data isn't shared externally, while others counter that the distinction is irrelevant from a privacy perspective. The lack of transparency around Apple's data collection practices fuels suspicion. A common sentiment is that Apple's privacy stance is more about marketing than genuine user protection. Some users also highlight the inherent conflict of interest in Apple acting as both platform owner and app developer.
Hotline is a macOS menu bar application that enables quick and easy access to remote terminals and SSH connections. It stores connection details securely in the Keychain and allows users to organize them into customizable groups. With a simple click from the menu bar, users can establish SSH connections or launch other terminal applications like iTerm, Terminal, or Warp with pre-configured settings. This streamlines the workflow for developers and system administrators who frequently connect to remote servers.
HN users generally express interest in Hotline, praising its simplicity and ease of use compared to more complex MDM solutions. Several commenters appreciate the focus on privacy and local control, particularly the lack of cloud dependencies. Some discuss potential use cases, like managing home devices or small business networks. A few users raise concerns, including the limited documentation and the project's early stage of development. Others suggest improvements like mobile device configuration and SSH key management. The developer engages with the comments, answering questions and acknowledging suggestions for future features.
Tapestry is a new, minimalist menubar app for macOS designed to declutter and streamline your menu bar. It allows users to hide less-frequently used menu bar icons, organizing them into a customizable dropdown menu accessible with a single click. This helps keep the menu bar clean and focused while still providing quick access to all your apps and utilities. Tapestry offers granular control, allowing you to choose exactly which icons to hide and the order they appear in the dropdown. It also boasts smart features like automatic hiding of rarely used icons and the ability to pin favorites for constant visibility.
HN commenters generally expressed positive sentiment towards Tapestry, praising its clean design, speed, and focus on privacy. Several appreciated the lack of algorithmic feeds and the chronological presentation of followed accounts. Some compared it favorably to Twitter, finding it a refreshing alternative. The pricing model, a one-time purchase, also received positive feedback, with some expressing willingness to pay even more. A few commenters raised concerns, including the potential difficulty of attracting a large user base and the lack of a web interface. Others questioned the long-term viability of a small, independent social network. The overall tone, however, leaned towards cautious optimism about Tapestry's potential to offer a calmer, more user-focused social media experience.
The blog post details the reverse engineering process of Apple's proprietary Typed Stream format used in various macOS features like Spotlight search indexing and QuickLook previews. The author, motivated by the lack of public documentation, utilizes a combination of tools and techniques including analyzing generated Typed Stream files, using class-dump on relevant system frameworks, and examining open-source components like CoreFoundation, to decipher the format. They ultimately discover that Typed Streams are essentially serialized property lists with a specific header and optional compression, allowing for efficient storage and retrieval of typed data. This reverse engineering effort provides valuable insight into the inner workings of macOS and potentially enables interoperability with other systems.
HN users generally praised the author's reverse-engineering effort, calling it "impressive" and "well-documented." Some discussed the implications of Apple using a custom format, speculating about potential performance benefits or tighter integration with their hardware. One commenter noted the similarity to Google's Protocol Buffers, suggesting Apple might have chosen this route to avoid dependencies. Others pointed out the difficulty in reverse-engineering these formats, highlighting the value of such work for interoperability. A few users discussed potential use cases for the information, including debugging and data recovery. Some also questioned the long-term viability of relying on undocumented formats.
The Asurion article outlines how to manage various Apple "intelligence" features, which personalize and improve user experience but also collect data. It explains how to disable Siri suggestions, location tracking for specific apps or entirely, personalized ads, sharing analytics with Apple, and features like Significant Locations and personalized recommendations in apps like Music and TV. The article emphasizes that disabling these features may impact the functionality of certain apps and services, and offers steps for both iPhone and Mac devices.
HN commenters largely express skepticism and distrust of Apple's "intelligence" features, viewing them as data collection tools rather than genuinely helpful features. Several comments highlight the difficulty in truly disabling these features, pointing out that Apple often re-enables them with software updates or buries the relevant settings deep within menus. Some users suggest that these "intelligent" features primarily serve to train Apple's machine learning models, with little tangible benefit to the end user. A few comments discuss specific examples of unwanted behavior, like personalized ads appearing based on captured data. Overall, the sentiment is one of caution and a preference for maintaining privacy over utilizing these features.
A developer created a minimalist podcast player for iOS called Podcatcher, built using the Racket programming language. It supports basic features like subscribing to RSS feeds, downloading episodes, and background playback. The project aims to explore the viability of Racket for iOS development, focusing on a simple, functional app with a small footprint. The developer highlighted the challenges of working with Racket on iOS, including compilation times and integrating with native APIs, but ultimately found the experience positive and plans further development, including potential Android support.
HN users generally praised the developer's choice of Racket, expressing interest in its capabilities for iOS development. Some questioned the viability of Racket for mobile development, citing concerns about performance and community size compared to established options like Swift. A few users shared their own experiences with Racket and suggested improvements for the app, such as adding iPad support and offline playback. Several commenters expressed interest in trying the app or exploring the source code. The overall sentiment was one of curiosity and encouragement for the project.
Malimite is a free and open-source decompiler designed specifically for iOS and macOS applications. It aims to reconstruct the original Objective-C code from compiled Mach-O binaries, assisting in security research, software analysis, and understanding the inner workings of closed-source apps. Built using Swift, Malimite leverages a custom intermediate representation and features a modular architecture for easy extensibility and improvement. The project is actively under development and welcomes contributions from the community.
HN commenters generally express interest in Malimite's capabilities, particularly its potential for reverse engineering Swift and SwiftUI. Some highlight the difficulty of decompiling Swift and applaud any progress in this area. Others question its effectiveness compared to existing tools like Hopper, mentioning limitations in reconstructing complex control flow and higher-level language constructs. A few raise ethical concerns about the potential for misuse in piracy and intellectual property theft, while others emphasize the importance of such tools for security research and understanding closed-source software. The developer's choice to keep the tool closed-source is also a point of discussion, with some arguing for open-sourcing it to foster community development and scrutiny.
This project introduces a Tailwind CSS plugin called corner-smoothing that allows developers to easily create Apple-like smooth rounded corners without complex SVG filters or excessive markup. It provides a set of pre-defined utility classes for various corner radii, inspired by Apple's design language, that can be applied directly to HTML elements. The plugin aims to simplify the process of achieving this subtle but polished visual effect, making it readily accessible through familiar Tailwind syntax.
HN commenters generally praised the smooth corner implementation for Tailwind CSS, finding it a clever and useful approach. Several appreciated the use of a single div and the avoidance of pseudo-elements, considering it elegant and performant. Some pointed out potential limitations, like the inability to control individual corner rounding and challenges with background images or borders. A few users offered alternative solutions, including using SVG filters or leveraging specific Tailwind features. The overall sentiment was positive, with many expressing interest in using the technique in their projects.
A vulnerability (CVE-2024-54507) was discovered in the XNU kernel, affecting macOS and iOS, which allows malicious actors to leak kernel memory. The flaw resides in the sysctl interface, specifically the kern.hv_vmm_vcpu_state handler. This handler failed to properly validate the size of the buffer provided by the user, resulting in an out-of-bounds read. By crafting a request with a larger buffer than expected, an attacker could read data beyond the intended memory region, potentially exposing sensitive kernel information. This vulnerability was patched by Apple in October 2024 and is relatively simple to exploit.
Hacker News commenters discuss the CVE-2024-54507 vulnerability, focusing on the unusual nature of the vulnerable sysctl and the potential implications. Several express surprise at the existence of a sysctl that directly modifies kernel memory, questioning why such a mechanism exists and speculating about its intended purpose. Some highlight the severity of the vulnerability, emphasizing the ease of exploitation and the potential for privilege escalation. Others note the fortunate aspect of the bug manifesting as a kernel panic rather than silent memory corruption, making detection easier. The limited practical impact due to System Integrity Protection (SIP) is also mentioned, alongside the difficulty of exploiting the vulnerability remotely. A few commenters also delve into the technical details of the exploit, discussing the specific memory manipulation involved and the resulting kernel crash. The overall sentiment reflects concern about the unusual nature of the vulnerability and its potential implications, even with the mitigating factors.
This project describes a method to use an Apple device (iPhone or Apple Watch) as an access card even with unsupported access control systems. It leverages the device's NFC capabilities to read the card's data, then emulates the card using an Arduino and RFID reader/writer. The user taps their physical access card on the RFID reader connected to the Arduino, which then transmits the card data to an Apple device via Bluetooth. The Apple device then stores and transmits this data wirelessly to the Arduino when presented to the reader, effectively cloning the original card's functionality. This allows users to unlock doors and other access points without needing their physical card.
HN users discuss the practicality and security implications of using an Apple device as an access card in unsupported systems. Several commenters point out the inherent security risks, particularly if the system relies solely on NFC broadcasting without further authentication. Others highlight the potential for lock-in and the difficulties in managing lost or stolen devices. Some express skepticism about the reliability of NFC in real-world scenarios, while others suggest alternative solutions like using a Raspberry Pi for more flexible and secure access control. The overall sentiment leans towards caution, with many emphasizing the importance of robust security measures in access control systems.
A developer created "Islet", an iOS app designed to simplify diabetes management using GPT-4-Turbo. The app analyzes blood glucose data, meals, and other relevant factors to offer personalized insights and predictions, helping users understand trends and make informed decisions about their diabetes care. It aims to reduce the mental burden of diabetes management by automating tasks like logbook analysis and offering proactive suggestions, ultimately aiming to improve overall health outcomes for users.
HN users generally expressed interest in the Islet diabetes management app and its use of GPT-4. Several questioned the reliance on a closed-source LLM for medical advice, raising concerns about transparency, data privacy, and the potential for hallucinations. Some suggested using open-source models or smaller, specialized models for specific tasks like carb counting. Others were curious about the app's prompt engineering and how it handles edge cases. The developer responded to many comments, clarifying the app's current functionality (primarily focused on logging and analysis, not direct medical advice), their commitment to user privacy, and future plans for open-sourcing parts of the project and exploring alternative LLMs. There was also a discussion about regulatory hurdles for AI-powered medical apps and the importance of clinical trials.
iOS 18 introduces a new feature that automatically reboots devices after a prolonged period of inactivity. Reverse engineering revealed this is managed by the SpringBoard process, which monitors user interaction and triggers a reboot after approximately 72 hours of inactivity. The reboot is signaled by setting a specific flag in a system property and is considered a "soft" reboot, likely to maintain device state where possible. This feature seems primarily targeted at corporate devices enrolled in Mobile Device Management (MDM) systems, as a way to clear temporary states and potentially address performance issues resulting from prolonged uptime without requiring manual intervention. The exact conditions for triggering the reboot, beyond inactivity time, are still being investigated.
Hacker News users discussed the potential reasons behind iOS 18's automatic reboot after extended inactivity, with some speculating it's related to memory management, specifically clearing caches or resetting background processes. Others suggested it could be a security measure to mitigate potential exploits or simply a bug. A few commenters expressed concern about the reboot happening without warning, potentially interrupting ongoing tasks or data syncing. Some highlighted the lack of official documentation on this behavior and the author's reverse engineering efforts to uncover the cause. The discussion also touched on similar behavior observed in other operating systems and the overall complexity of modern OS architectures.
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https://news.ycombinator.com/item?id=43641576
HN commenters generally expressed skepticism towards Pledge's performance claims, particularly regarding the "no Rx overhead" assertion. Several pointed out the difficulty of truly eliminating the overhead associated with reactive programming patterns and questioned whether a simpler approach using Combine, Swift's built-in reactive framework, wouldn't be preferable. Some questioned the need for another reactive framework in the Swift ecosystem given the existing mature options. A few users showed interest in the project, acknowledging the desire for a lighter-weight alternative to Combine, but emphasized the need for robust benchmarks and comparisons to substantiate performance claims. There was also discussion about the project's name and potential trademark issues with Adobe's Pledge image format.
The Hacker News post discussing Pledge, a lightweight reactive framework for Swift, has generated a moderate amount of discussion, with several commenters expressing interest and raising pertinent questions.
One of the most compelling threads revolves around the performance comparisons between Pledge and Combine, Apple's built-in reactive framework. A commenter questions the benchmark presented in the project's README, specifically pointing out that Combine's performance is known to be suboptimal when dealing with a large number of subscribers and frequent updates. They suggest that a more realistic benchmark would involve scenarios with a substantial subscriber count and rapid value changes to accurately gauge Pledge's performance advantage. The author of Pledge responds to this, acknowledging the feedback and indicating their intention to incorporate more comprehensive benchmarks in the future. They also discuss the inherent difficulties in creating a completely fair comparison given the differences in the frameworks' architectures.
Another significant point of discussion is the project's scope and goals. A commenter asks whether Pledge intends to be a full-fledged reactive framework like Combine or a more focused solution addressing specific use cases. The project author clarifies that Pledge prioritizes simplicity and performance, aiming to provide a lightweight alternative for common reactive patterns without the complexity and overhead of Combine. They emphasize that Pledge isn't designed to be a complete replacement for Combine but rather a more streamlined option for specific scenarios.
Several commenters express general interest in the project and commend its approach. Some suggest potential improvements, including exploring alternative implementation strategies and considering compatibility with Swift's existing concurrency features.
Finally, there's a brief discussion regarding the project's license. A commenter notes the absence of a license file and inquires about the intended licensing terms. The author promptly addresses this by adding an MIT license to the repository.
Overall, the comments on the Hacker News post reflect a positive reception of Pledge. The discussion focuses primarily on performance comparisons with Combine, the project's overall goals, and potential areas for improvement. The author actively engages with commenters, addressing their questions and demonstrating a willingness to incorporate feedback.