Blank spaces could hold danger - Kaspersky report warns of the dangers of 'parked domains' and empty pages where hackers could be lurking

• Kaspersky says empty web pages are watching you, and the research backs up the warning
• Over 90% of parked domains now send visitors somewhere malicious, and clearing your cookies will not help
• Blank pages are also a problem: many 'Coming Soon' placeholders are quietly fingerprinting your device

Kaspersky has unveiled a rather underreported attack vector which is increasingly being used by threat actors to harvest private data from unsuspecting victims: registered websites that are yet to be developed.

Its warning focuses on parked domains, the registered web addresses that have no real website behind them yet, arguing that the blank screens and "Coming Soon" placeholders users dismiss as harmless are frequently doing work in the background.

The company says simply loading one of these pages can trigger silent collection of a visitor's IP address, approximate location, User-Agent string and cookie identifiers, and that operators go further by building browser fingerprints through other techniques, then feeding the result into advertising networks to assemble targeted profiles without consent from users.

Browser fingerprinting sans the permissions

The mechanics Kaspersky describes are worth understanding, because fingerprinting is the part most readers will not have encountered, and the part that conventional privacy habits do not touch.

For context, a cookie is a file placed on your machine that you can delete, thereby limiting tracking. A fingerprint is not stored on your machine at all. It is derived from how your specific hardware and software combination renders a test image, draws 3D graphics, or processes an audio signal, producing a value distinctive enough to identify the same device across unrelated sites.

Browser fingerprinting, the method used to capture such data within a browser session, is attractive to trackers because it is considerably harder to shake off. A private browsing window prevents your machine from keeping a local record of the visit, but it does not change how your hardware renders the test image, so the fingerprint it produces remains largely the same.

Such domains can also cause more direct damage than selling one's information to advertisers. Kaspersky says threat actors embed scripts that bounce visitors onward to fraudulent platforms, adult content, or online casinos. It flags typosquatting as a particularly acute risk, in which a domain differing from a well-known brand by a letter or two can capture mistyped traffic, landing the user on a phishing page or triggering a drive-by download.

This isn't the first time the problem has been reported, either, as recent research from Infoblox finding that in large-scale experiments, over 90% of the time, a visitor to a parked domain was routed to illegal content, scams, scareware, antivirus subscription traps, or malware.

Kaspersky recommends several ways to mitigate the risk, including avoiding suspicious links, clearing cache and cookies after an unintended visit, and using software that blocks web tracking.

Clearing cookies is worth noting, though: it addresses the cookie identifiers Kaspersky mentions, but by the company's own explanation it does nothing about fingerprinting, because there is nothing stored locally to clear.

Parked domains, including blank pages that appear inert, are now a routine part of criminal infrastructure rather than digital litter and should be treated with caution. At best, you give away more information than you meant to. At worst, you become the victim of an attack you never saw coming.

from Latest from TechRadar https://ift.tt/IwZPKLC

'A disk in a planet-scale computer': Meta has so many expensive GPUs that it's buying SSDs to kill idle time

• Meta rebuilt storage systems after slow data repeatedly stalled expensive AI GPUs
• SSD caching dramatically reduced AI dataset loading times from hours to minutes
• Meta replaced complex metadata lookups with a faster unified storage architecture

Meta says storage systems have failed to keep pace with AI computing power, creating delays that leave costly GPUs waiting instead of processing workloads efficiently.

According to the company's engineers, storage bottlenecks remain a major cause of GPU stalls, increasing operating costs while slowing research progress and extending development timelines.

To address those delays, Meta redesigned its storage architecture, arguing that faster movement of data can unlock greater value from expensive AI hardware investments.

Meta rebuilds storage architecture to keep GPUs working

Meta's engineers explained that the company operates hundreds of exabyte-scale storage clusters supporting Facebook, Instagram, Reality Labs, Meta AI, advertising systems, databases, and internal data warehouses.

Those services rely on a foundational storage layer called Tectonic, which manages object storage, file systems, block devices, and data placement across HDDs and SSDs.

The company has increasingly shifted from traditional file storage toward BLOB storage because massive AI datasets require unified access methods with significantly higher performance.

When GPU servers request information from storage, repeated metadata lookups across several layers create latency that interrupts AI training pipelines and delays overall processing.

Meta responded by rebuilding the metadata subsystem into a unified schema backed by ZippyDB while allowing clients to retrieve data directly from storage servers.

Instead of routing every transfer through application servers, the redesigned software uses an embedded client capable of streaming information directly from the Tectonic storage layer.

To support distributed AI deployments, Meta placed regional BLOB-storage systems beside GPU clusters, reducing delays associated with transferring information across distant infrastructure.

It introduced distributed caching using unused GPU host memory, producing an average cache hit rate of 80%, while metadata became accessible within 1 to 2 ms.

The engineers further added hedged reads alongside dynamic concurrency controls, stating that "the new BLOB-storage stack is now capable of serving AI workloads without causing GPU stalls."

SSD caching cuts hours from AI data ingestion

Meta examined lengthy delays experienced before AI training even began, when researchers transferred enormous dataset snapshots from BLOB storage into regional GPU facilities.

Instead of loading every dataset directly from slower storage drives, Meta created multiple cache layers that keep frequently used data much closer to GPU servers.

That approach introduced multiple caching layers, using GPU memory as L1, SSDs inside GPU hosts as L2, and regional flash-backed BLOB storage as L3.

Traditional HDD storage remained the authoritative data source, while faster cache layers supplied frequently requested information before slower disks became necessary during processing.

Meta’s redesign produced sharp gains in ingestion speed, cutting a previous 150-minute loading process down to just 10 minutes.

A separate job that once required 89 hours to complete now finishes in just over three hours from start to finish.

Citrini analyst Jukan notes that high-capacity storage has traditionally been judged mainly by its cost per terabyte of capacity alone.

He argues that idle GPU time can outweigh any savings gained from cheaper storage if data arrives too slowly each day.

This suggests that the cost of flash storage is economically rational whenever eliminating idle time costs more than the flash itself each hour.

Via Blocks and Files

from Latest from TechRadar https://ift.tt/T6XJ9od