AntiMalware•August 26, 2026•🇷🇺Translated from Russian

Aeroflot to Accept Digital Rubles for Ticket Purchases Starting September 2026

Aeroflot will begin accepting digital rubles for the purchase of airline tickets starting 1 September 2026. The new payment option will be available both on the carrier’s website and at its own sales offices across Russia.

When buying a ticket online, passengers will be offered the choice “Digital ruble”. The site will then generate a QR code that must be scanned inside a bank application supporting the new form of currency. After confirmation, funds are debited from the digital wallet on the Bank of Russia platform and the ticket is issued with an electronic receipt sent to the customer’s email.

The process closely resembles payments made through the Fast Payments System (SBP) and does not require passengers to carry any physical form of digital cash to the airport. At Aeroflot ticket offices the same QR-code mechanism will appear on the cashier terminal for the customer to scan and authorise.

To use the service travellers must open a digital wallet with a bank already connected to the Bank of Russia digital-ruble platform. Existing bank cards and other payment methods will continue to be accepted without change.

On the same date MTS will begin accepting digital rubles for services linked to MTS Pay. Rostelecom and Megafon have also confirmed they are preparing their systems for the new currency. Authorities have reiterated that the digital ruble is not a cryptocurrency but the third official form of the Russian national currency alongside cash and non-cash money.

Related articles

AntiMalware•Other

RemoveMacAI Utility Appears on GitHub to Disable Apple Intelligence and Free Disk Space on macOS

A new open-source tool called RemoveMacAI has been released on GitHub, allowing macOS users to fully disable Apple Intelligence features and remove associated AI models from their systems. The utility addresses the lack of a single toggle in macOS 27 for turning off generative AI capabilities while also reclaiming storage space occupied by downloaded models. It supports Apple silicon devices and works by leveraging Apple's own system services rather than directly modifying protected directories. Users can selectively disable components such as Siri, Writing Tools, Genmoji, Image Playground, ChatGPT integration, smart replies, photo cleanup, and Xcode predictive code completion. The tool also installs a configuration profile that prevents models from being redownloaded automatically. Reversion is possible via the removemacai revert command, though this comes at the cost of losing access to certain Apple Intelligence-powered functions in third-party apps and Shortcuts. The project is licensed under MIT and leaves Dictation untouched as it is managed separately.

Habr•Other

Secure Personalization of Java Card Applets Using Issuer Security Domain and SCP02

The article explains how to leverage the Issuer Security Domain mechanisms on GlobalPlatform cards to establish secure channels for applet personalization without implementing custom ECDH-based key exchange. It addresses limitations of prior approaches that lacked authentication and required extensive PKI support. The solution uses SCP02 with specific security levels such as C_MAC and C_DECRYPTION to protect commands that store AES-128 keys and personal data on the card. Detailed code walkthroughs cover the applet constructor, process method, mutual authentication via SecureChannel.processSecurity, and unwrap operations for decrypting and verifying APDUs. Practical testing on NXP Java Cards demonstrates installation via FunGP library scripts that allow configurable security levels during mutual authentication. The implementation ensures that secret key updates enforce C_DECRYPTION while personal data writes accept C_MAC, with encrypted reads performed using AES-CBC.

AntiMalware•Other

IT Jobs at Major Tech Firms Turn Into Dating Red Flags for Some Women

Working in IT used to be seen as a strong advantage in dating due to high salaries and prestigious employers. However, employees at companies like Palantir and Tesla now report that their jobs trigger uncomfortable conversations about ethics and politics instead of romantic interest. A Palantir engineer named Gary has started hiding his employer after facing sharp reactions from women and even requests from friends to avoid mentioning the company at social events. Tesla employee James encounters questions about his political views simply because of his association with Elon Musk's company. Dating specialist Amy Laurent notes that tech giants face backlash over issues like surveillance, inequality, and AI displacing workers, forcing professionals to present their careers with caveats. The article from Wired highlights how an employer's reputation now overshadows individual values during initial meetings. While IT roles remain attractive in many ways, the automatic boost from big tech brands appears to be fading in personal contexts.

Securitylab•Other

Neuromorphic Chips: Event-Driven Architectures Aim to Cut Energy Use in Always-On AI and Sensor Systems

Modern processors and GPUs excel at massive parallel math yet remain inefficient for continuous sensor streams where little changes most of the time. Neuromorphic chips borrow principles such as local memory, sparse spiking communication and threshold-based activation from biological nervous systems to reduce data movement and idle computation. The approach replaces constant matrix multiplications with asynchronous spikes that propagate only when meaningful events occur, lowering both power and latency for edge devices. Spiking neural networks encode information in the timing and frequency of pulses rather than dense numeric tensors, making them suitable for vibration monitoring, robotic vision and wearable health sensors. Hybrid systems are expected to pair conventional CPUs and NPUs for heavy training workloads with neuromorphic accelerators that stay dormant until events arrive. The architecture does not replace existing accelerators but targets the niche of always-on, battery-constrained perception tasks where conventional von Neumann designs hit the memory wall.