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Frostbyte10 Bugs Put Thousands of Refrigerators At Major Grocery Chains At Risk
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Chrome Increases Its Overwhelming Market Share, Now Over 70%
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SAP To Invest Over 20 Billion Euros In 'Sovereign Cloud'
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OpenAI To Acquire Product Testing Startup Statsig, Appoints CTO of Applications
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Google Gets To Keep Chrome But Is Barred From Exclusive Search Deals, Judge Rules
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Hackers Threaten To Submit Artists' Data To AI Models If Art Site Doesn't Pay Up
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New Study Proves EVs Are Always Cleaner Than Gas Cars
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Summer 2025 is the Warmest on Record for the UK
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Laravel Inventor Tells Devs To Quit Writing 'Cathedrals of Complexity'
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Poor Amazon Rains Linked To Brazil Deforestation
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YouTube Is Pausing Premium Family Plans if You Aren't Watching From the Same Address
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32GB of RAM On Track To Become the New Majority For Gamers
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Americans Lose Faith That Hard Work Leads to Economic Gains, WSJ-NORC Poll Finds
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Amazon Ends Shared Prime Free Shipping Outside Your Home
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What Every Argument About Sideloading Gets Wrong
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[$] Removing Guix from Debian
As a rule, if a package is shipped with a Debian release, users can count on it being available, and updated, for the entire life of the release. If package foo is included in the stable release—currently Debian 13 ("trixie")—a user can reasonably expect that it will continue to be available with security backports as long as that release is supported, though it may not be included in Debian 14 ("forky"). However, it is likely that the Guix package manager will soon be removed from the repositories for Debian 13 and Debian 12 ("bookworm", also called oldstable).
The hidden vulnerabilities of open source (FastCode)
Open source maintainers, already overwhelmed by legitimate contributions, have no realistic way to counter this threat. How do you verify that a helpful contributor with months of solid commits isn't an LLM generated persona? How do you distinguish between genuine community feedback and AI created pressure campaigns? The same tools that make these attacks possible are largely inaccessible to volunteer maintainers. They lack the resources, skills, or time to deploy defensive processes and systems.
The detection problem becomes exponentially harder when LLMs can generate code that passes all existing security reviews, contribution histories that look perfectly normal, and social interactions that feel authentically human. Traditional code analysis tools will struggle against LLM generated backdoors designed specifically to evade detection. Meanwhile, the human intuition that spot social engineering attacks becomes useless when the "humans" are actually sophisticated language models.
The US Population Could Shrink in 2025, For the First Time Ever
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Security updates for Tuesday
Amazon US Prime Sign-Ups Slow Despite Expanded Promotion, Data Shows
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